Systems and methods for pelvic floor disorder screening and diagnosis

Abstract

Provided herein is a magnetic resonance imaging (MRI) system for the screening of pelvic organ prolapse (POP), comprising: (a) a housing comprising a surface for contact with a subject; and (b) a radio frequency receive (RF RX) coil network; wherein the RF RX coil network is configured to enable imaging in a region of interest, wherein the region of interest is external to the surface of the housing by a distance ranging from about 80 mm to about 120 mm.

Description

Atty Dkt No.: 49880-722601SYSTEMS AND METHODS FOR PELVIC FLOOR DISORDER SCREENING AND DIAGNOSISCROSS-REFERENCE

[0001] This application claims the benefit of U.S. Provisional Application No. 63 / 712,959, filed October 28, 2024, which application is incorporated herein by reference.BACKGROUND OF THE INVENTION

[0002] Pelvic organ prolapse (POP) affects up to 50% of women, with risk factors including multiparity, vaginal delivery, older age, menopause, connective tissue disorders, and higher BMI. Weakening of the pelvic floor muscles and other tissues holding pelvic organs in place causes pelvic organs to prolapse and bulge into the vagina. An earlier diagnosis allows patients to begin treatment earlier and prevent further progression of POP.SUMMARY OF THE INVENTION

[0003] In an aspect, provided herein is a magnetic resonance imaging (MRI) system for the screening of pelvic organ prolapse (POP), the MRI system comprising: (a) a housing comprising a surface for contact with a subject; and (b) a radio frequency receive (RF RX) coil network; wherein the RF RX coil network is configured to enable imaging in a region of interest, wherein the region of interest is external to the surface of the housing by a distance ranging from about 80 mm to about 120 mm.

[0004] In some embodiments, the RF RX coil network is configured to fully cover the surface such that there is no access aperture on the surface nearest the region of interest. In some embodiments, the RF RX coil network is configured for imaging external to the surface by a distance of about 100 mm. In some embodiments, the RF RX coil network comprises a plurality of RF RX coils. In some embodiments, the RF RX coil network comprises a plurality of interconnected RF RX coils. In some embodiments, the RF RX coil network comprises a plurality of coupled RF RX coils. In some embodiments, a number of turns and loops of the RF RX coil is configured to be adjustable to cover an entire space between legs of the subject such that the region of interest is entirely or partially covered. In some embodiments, the housing further comprises a radio frequency transmit (RF TX) coil proximate to the surface of the housing, wherein the RF TX coil is configured to generate an electromagnetic field in the region of interest. In some embodiments, the RF TX coil comprises a plurality of figure-8 coils arranged proximal the surface. In some embodiments, the plurality of figure-8 coils are configured to generate a varying magnetic RF field within the region of interest. In some embodiments, theAtty Dkt No.: 49880-722601 plurality of figure-8 coils are orthogonal to each other. In some embodiments, the plurality of figure-8 coils are tunable to same radiofrequency (RF) resonant frequencies. In some embodiments, the plurality of figure-8 coils are tunable to different RF resonant frequencies. In some embodiments, the plurality of figure-8 coils are configured to generate a uniform magnetic RF field within the region of interest. In some embodiments, the system further comprises an electromagnet configured to generate an electromagnetic field in the region of interest.

[0005] In some embodiments, the housing further comprises a gradient coil set positioned proximate to the surface, wherein the gradient coil set is configured to generate an electromagnetic field in the region of interest. In some embodiments, the gradient coil set comprises a single-sided gradient coil set.

[0006] In some embodiments, the MRI system is configured to be used for one or more of diagnosis, grading, treatment planning, or monitoring of POP. In some embodiments, the MRI system comprises a magnetic field strength of less than about 0.5 T. In some embodiments, the MRI system comprises one or more of an open or single-sided MRI. In some embodiments, the housing comprises a bore. In some embodiments, the MRI system is configured to be used in an office setting without shielding or floor reinforcements. In some embodiments, the MRI system comprises at least one permanent magnet configured for use without superconducting material. In some embodiments, the RF RX coil is configured to capture images of the subject when the subject is in a position in front of or on top of the MRI, wherein the position is a high lithotomy, an inclined lithotomy, or a seated position over the MRI. In some embodiments, the RF RX coil is configured to capture images of the subject when the subject is in contact with the surface of the MRI in the high lithotomy, the inclined lithotomy, or the seated position. In some embodiments, the housing is configured to be positioned such that a central axis thereof is perpendicular to a floor when capturing images of the subject in the high lithotomy or the inclined lithotomy. In some embodiments, the housing is configured to be positioned such that a central axis thereof is parallel to a floor when capturing images of the subject in the seated position. In some embodiments, the MRI system is configured to be usable in a first mode and a second mode, wherein the first mode comprises capturing images of the subject in the high lithotomy or the inclined lithotomy when the housing is positioned such that a central axis thereof is perpendicular to a floor, and wherein the second mode comprises capturing images of the subject in the seated position when the housing is positioned such that a central axis thereof is parallel to the floor. In some embodiments, the MRI system is configured to record dynamic imaging of activities applying pressure to pelvic organs of the subject.Atty Dkt No.: 49880-722601

[0007] In some embodiments, the system further comprises a processor configured to run a computer-implemented method, wherein the computer-implemented method comprises one or more of automatically screening, diagnosing, or grading POP. In some embodiments, the computer-implemented method comprises employing a machine learning based system trained on at least one training dataset. In some embodiments, the training dataset comprises at least one of a dataset comprising data from multiple subjects, a dataset comprising longitudinal data from one subject, or a combination thereof. In some embodiments, the computer-implemented method comprises analyzing images comprising the dataset comprising longitudinal data from one subject acquired over time to manually detect and quantify anatomical changes over time. In some embodiments, the computer-implemented method comprises analyzing images comprising the dataset comprising longitudinal data from one subject acquired over time to automatically detect and quantify anatomical changes over time. In some embodiments, the computer- implemented method comprises detecting and quantifying anatomical changes over time automatically through co-registrations with prior images or predefined protocols. In some embodiments, the computer-implemented method comprises determining whether the anatomical changes are of a normal or an abnormal characteristic and grading the anatomical changes if a prolapse is detected. In some embodiments, the computer-implemented method comprises employing one or more of an Al-based segmentation, classification, or regression model to assess POP via one or more of detection, grading, surveillance, or treatment recommendations. In some embodiments, the computer-implemented method comprises providing treatment recommendations based on a POP determination and grade. In some embodiments, the computer-implemented method comprises detecting early anatomical changes. In some embodiments, the computer-implemented method comprises detecting the early anatomical changes automatically. In some embodiments, the computer-implemented method comprises monitoring progress of the POP via images of the subject acquired during a treatment, after a treatment, or a combination thereof. In some embodiments, the computer-implemented method comprises recommending at least one alternative treatment if a predetermined treatment progress threshold is not achieved, wherein a predetermined treatment progress is determined based on the monitored progress of the POP. In some embodiments, the computer-implemented method comprises providing feedback to a user, wherein the user is different from the subject, wherein the feedback comprises a progress of a treatment, wherein the feedback is determined from analyzed changes in anatomy across multiple images. In some embodiments, the computer- implemented method comprises recommending a treatment to aid a physician in decision making. In some embodiments, the computer-implemented method comprises training aAtty Dkt No.: 49880-722601 classifier model on one or more of MR images of normal anatomy, different types and grades of POP, or images of POP progressing over time from early onset to proper diagnosis. In some embodiments, the computer-implemented method comprises using an Al model to perform segmentation and landmark identification on low field MRI comprising a static component or a dynamic component for grading of POP. In some embodiments, the computer-implemented method comprises using a classification model for determination of POP based on continuous distance metrics from one or more of a static low field MRI exam, a dynamic low field MRI exam, or a physical examination. In some embodiments, the computer-implemented method comprises using an Al model for visualization of longitudinal low field MRI data with a static component or a dynamic component. In some embodiments, the computer-implemented method comprises using an Al model for identification of hotspots indicating progressing prolapse or resolving prolapse. In some embodiments, the computer-implemented method comprises using a spatio-temporal model using longitudinal low field MRI data with a static component or a dynamic component for prediction of anatomical segmentation masks at a future time point. In some embodiments, the computer-implemented method comprises using a spatio-temporal model using longitudinal low field MRI data with a static component or a dynamic component for prediction of low field MRI at a future time point. In some embodiments, the computer- implemented method comprises using a classification model and the low field MRI prediction model to compare low field MRI at the future time point and predicted low field MRI at the future time point to evaluate whether a health condition deviated from an expected trajectory. In some embodiments, the computer-implemented method comprises using a classification model and the low field MRI prediction model to compare low field MRI at the future time point and predicted low field MRI at the future time point to evaluate whether prolapse deviated from an expected trajectory. In some embodiments, the computer-implemented method comprises using a spatio-temporal model for generating trajectory and velocity metrics from longitudinal low field MRI with a static component or a dynamic component. In some embodiments, the computer- implemented method comprises using a prognostic model for one or more of risk stratification or outcome prediction via one or more of a) trajectory and velocity metrics derived from low field MRI, b) physical examination-based metrics, c) clinical variables, or d) symptom and quality of life scores.

[0008] In some embodiments, the MRI system is configured to be rotatable 90 degrees such that the system has an imaging field of view on top of the MRI system. In some embodiments, the MRI system is configured for static and dynamic magnetic resonance (MR) imaging.Atty Dkt No.: 49880-722601

[0009] In some embodiments, the MRI system is configured to not contain a through-bore access aperture.

[0010] In some embodiments, a shape and orientation of the housing are configured to use gravity and intra-abdominal natural pressures to increase MR imaging access to the region of interest during static MR imaging. In some embodiments, the static MR imaging comprises a first imaging protocol. In some embodiments, the first imaging protocol comprises a scout scan configured to determine a position of the subject within a field of view of the MRI system. In some embodiments, the first imaging protocol comprises T2-weighted fast spin echo imaging of about 24 cm to about 30 cm in the axial or coronal plane and about 30 to about 40 cm in the sagittal plane. In some embodiments, the T2-weighted fast spin echo imaging comprises from about a 3 mm to about a 5 mm static slice thickness with less than about a 1 mm gap. In some embodiments, the first imaging protocol comprises T1 fast spin echo imaging. In some embodiments, the first imaging protocol comprises fat saturated T1 imaging. In some embodiments, the first imaging protocol comprises diffusion weighted imaging. In some embodiments, the static MR imaging is configured to screen for early onset of POP and to detect one or more of cystocele tendencies, uterine / vault descent, perineal descent, or levator ballooning.

[0011] In some embodiments, the dynamic MR imaging is configured to provide an equivalent quantitative pelvic organ prolapse quantification (POP-Q) score. In some embodiments, the dynamic MR imaging comprises a second imaging protocol. In some embodiments, the second imaging protocol comprises T2 static fast spin echo imaging. In some embodiments, the second imaging protocol comprises T1 static fast spin echo imaging.

[0012] In another aspect, provided herein is a method of performing magnetic resonance (MR) imaging, the method comprising: (a) inputting patient parameters into a magnetic resonance imaging (MRI) system, the system comprising: (i) a housing comprising a surface for contact with a subject; and (ii) a radio frequency receive (RF RX) coil network; (b) activating the RF RX coil network to obtain imaging data in the region of interest, wherein the region of interest is external to the surface of the housing by a distance ranging from about 80 mm to about 120 mm; (c) reconstructing obtained imaging data to produce an output image for analysis; and (d) displaying the output image for user review and annotation.

[0013] In some embodiments, the RF RX coil network is configured to fully cover the surface such that there is no access aperture on the surface nearest the region of interest. In some embodiments, the region of interest is external to the surface of the housing by about 100 mm. In some embodiments, the RF RX coil network comprises a plurality of RF RX coils. In someAtty Dkt No.: 49880-722601 embodiments, the RF RX coil network comprises a plurality of interconnected RF RX coils. In some embodiments, the RF RX coil network comprises a plurality of coupled RF RX coils. In some embodiments, a number of turns and loops of the RF RX coil is configured to cover an entire space between legs of the subject such that the region of interest is entirely or partially covered. In some embodiments, the housing further comprises a radio frequency transmit (RF TX) coil proximate to the surface of the housing, wherein the RF TX coil is configured to generate an electromagnetic field in the region of interest.

[0014] In some embodiments, the RF TX coil comprises a plurality of figure-8 coils arranged proximal the surface. In some embodiments, the plurality of figure-8 coils are configured to generate a varying magnetic RF field within the region of interest. In some embodiments, the plurality of figure-8 coils are orthogonal to each other. In some embodiments, the method further comprises tuning the plurality of figure-8 coils to same radiofrequency (RF) resonant frequencies. In some embodiments, the method further comprises tuning the plurality of figure-8 coils to different RF resonant frequencies. In some embodiments, the method further comprises generating, via the plurality of figure-8 coils, a uniform magnetic RF field within the region of interest.

[0015] In some embodiments, the method further comprises generating an electromagnetic field in the region of interest via activating an electromagnet in the MRI system. In some embodiments, the method further comprises generating an electromagnetic field in the region of interest via activating a gradient coil set disposed in the housing and positioned proximate to the surface. In some embodiments, the gradient coil set comprises a single-sided gradient coil set.

[0016] In some embodiments, the method further comprises, using the MRI system for one or more of diagnosis, grading, treatment planning, or monitoring of POP. In some embodiments, the MRI system comprises a magnetic field strength of less than about 0.5 T. In some embodiments, the MRI system comprises one or more of an open or single-sided MRI. In some embodiments, the housing comprises a bore. In some embodiments, the MRI system is configured to be used in an office setting without shielding or floor reinforcements. In some embodiments, the method further comprises using at least one permanent magnet configured without superconducting material. In some embodiments, the method further comprises capturing images of the subject, via the RF RX coil, when the subject is in a position in front of or on top of the MRI, wherein the position is a high lithotomy, an inclined lithotomy, or a seated position over the MRI. In some embodiments, the method further comprises capturing images of the subject, via the RF RX coil, when the subject is in contact with the surface of the MRI in the high lithotomy, the inclined lithotomy, or the seated position. In some embodiments, the methodAtty Dkt No.: 49880-722601 further comprises positioning the housing such that a central axis thereof is perpendicular to a floor when capturing images of the subject in the high lithotomy or the inclined lithotomy. In some embodiments, the method further comprises positioning the housing such that a central axis thereof is parallel to a floor when capturing images of the subject in the seated position. In some embodiments, the method further comprises using the MRI system in a first mode and a second mode, wherein the first mode comprises capturing images of the subject in the high lithotomy or the inclined lithotomy when the housing is positioned such that a central axis thereof is perpendicular to a floor, and wherein the second mode comprises capturing images of the subject in the seated position when the housing is positioned such that a central axis thereof is parallel to the floor. In some embodiments, the method further comprises recording, via the MRI system, dynamic imaging of activities applying pressure to pelvic organs of the subject. In some embodiments, the method further comprises one or more of automatically screening, diagnosing, or grading POP.

[0017] In some embodiments, the method further comprises employing a machine learning based system trained on at least one training dataset. In some embodiments, the training dataset comprises at least one of a dataset comprising data from multiple subjects, a dataset comprising longitudinal data from one subject, or a combination thereof. In some embodiments, the method further comprises analyzing images comprising the dataset comprising longitudinal data from one subject acquired over time to manually detect and quantify anatomical changes over time. In some embodiments, the method further comprises analyzing images comprising the dataset comprising longitudinal data from one subject acquired over time to automatically detect and quantify anatomical changes over time. In some embodiments, the method further comprises detecting and quantifying anatomical changes over time automatically through co-registrations with prior images or predefined protocols. In some embodiments, the method further comprises determining whether the anatomical changes are of a normal or an abnormal characteristic and grading the anatomical changes if a prolapse is detected. In some embodiments, the method further comprises employing one or more of an Al-based segmentation, classification, or regression model to assess POP via one or more of detection, grading, surveillance, or treatment recommendations.

[0018] In some embodiments, the method further comprises providing treatment recommendations based on a POP determination and grade. In some embodiments, the method further comprises detecting early anatomical changes. In some embodiments, the method further comprises detecting the early anatomical changes automatically. In some embodiments, the method further comprises monitoring progress of the POP via images of the subject acquiredAtty Dkt No.: 49880-722601 during a treatment, after a treatment, or a combination thereof. In some embodiments, the method further comprises recommending at least one alternative treatment if a predetermined treatment progress threshold is not achieved, wherein a predetermined treatment progress is determined based on the monitored progress of the POP. In some embodiments, the method further comprises providing feedback to a user, wherein the user is different from the subject, wherein the feedback comprises a progress of a treatment, wherein the feedback is determined from analyzed changes in anatomy across multiple images. In some embodiments, the method further comprises recommending a treatment to aid a physician in decision making.

[0019] In some embodiments, the method further comprises training a classifier model on one or more of MR images of normal anatomy, different types and grades of POP, or images of POP progressing over time from early onset to proper diagnosis. In some embodiments, the method further comprises using an Al model to perform segmentation and landmark identification on low field MRI comprising a static component or a dynamic component for grading of POP. In some embodiments, the method further comprises using a classification model for determination of POP based on continuous distance metrics from one or more of a static low field MRI exam, a dynamic low field MRI exam, or a physical examination. In some embodiments, the method further comprises using an Al model for visualization of longitudinal low field MRI data with a static component or a dynamic component. In some embodiments, the method further comprises using an Al model for identification of hotspots indicating progressing prolapse or resolving prolapse.

[0020] In some embodiments, the method further comprises using a spatio-temporal model using longitudinal low field MRI data with a static component or a dynamic component for prediction of anatomical segmentation masks at a future time point. In some embodiments, the method further comprises using a spatio-temporal model using longitudinal low field MRI data with a static component or a dynamic component for prediction of low field MRI at a future time point. In some embodiments, the method further comprises using a classification model and the low field MRI prediction model to compare low field MRI at the future time point and predicted low field MRI at the future time point to evaluate whether a health condition deviated from an expected trajectory. In some embodiments, the method further comprises using a classification model and the low field MRI prediction model to compare low field MRI at the future time point and predicted low field MRI at the future time point to evaluate whether prolapse deviated from an expected trajectory. In some embodiments, the method further comprises using a spatiotemporal model for generating trajectory and velocity metrics from longitudinal low field MRI with a static component or a dynamic component. In some embodiments, the method furtherAtty Dkt No.: 49880-722601 comprises using a prognostic model for one or more of risk stratification or outcome prediction via one or more of a) trajectory and velocity metrics derived from low field MRI, b) physical examination-based metrics, c) clinical variables, or d) symptom and quality of life scores.

[0021] In some embodiments, the MRI system is configured to be rotatable 90 degrees such that the system has an imaging field of view on top of the MRI system. In some embodiments, the method further comprises executing, via the MRI system, static and dynamic magnetic resonance (MR) imaging. In some embodiments, a shape and orientation of the housing are configured to use gravity and intra-abdominal natural pressures to increase MR imaging access to the region of interest during static MR imaging.

[0022] In some embodiments, the static MR imaging comprises a first imaging protocol. In some embodiments, the method further comprises determining, via a scout scan, a position of the subject within a field of view of the MRI system. In some embodiments, the first imaging protocol comprises T2-weighted fast spin echo imaging of about 24 cm to about 30 cm in the axial or coronal plane and about 30 to about 40 cm in the sagittal plane. In some embodiments, the T2-weighted fast spin echo imaging comprises from about a 3 mm to about a 5 mm static slice thickness with less than about a 1 mm gap. In some embodiments, the first imaging protocol comprises T1 fast spin echo imaging. In some embodiments, the first imaging protocol comprises fat saturated T1 imaging. In some embodiments, the first imaging protocol comprises diffusion weighted imaging. In some embodiments, the method further comprises screening for early onset of POP and detecting one or more of cystocele tendencies, uterine / vault descent, perineal descent, or levator ballooning via the static MR imaging.

[0023] In some embodiments, the method further comprises providing an equivalent quantitative pelvic organ prolapse quantification (POP-Q) score via the dynamic MR imaging. In some embodiments, the dynamic MR imaging comprises a second imaging protocol. In some embodiments, the second imaging protocol comprises T2 static fast spin echo imaging. In some embodiments, the second imaging protocol comprises T1 static fast spin echo imaging. In some embodiments, the method further comprises executing a subject positioning protocol comprising running at least one scan. In some embodiments, the method further comprises running at least one static scan. In some embodiments, the method further comprises running at least one dynamic scan.INCORPORATION BY REFERENCE

[0024] All publications, patents, and patent applications mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent, or patent application was specifically and individually indicated to be incorporated by reference.Atty Dkt No.: 49880-722601BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The novel features of the invention are set forth with particularity in the appended claims. A better understanding of the features and advantages of the present invention will be obtained by reference to the following detailed description that sets forth illustrative embodiments, in which the principles of the invention are utilized, and the accompanying drawings of which:

[0026] FIG. 1 shows a perspective view of a non-limiting example of a female patient being imaged in a high lithotomy, in accordance with example embodiments described herein.

[0027] FIG. 2 shows a perspective view of a non-limiting example of a female patient being imaged in a seated position, in accordance with example embodiments described herein.

[0028] FIG. 3 illustrates a process chart for a routine check-up with a manual assessment of anatomy and / or any anatomical changes by the physician, in accordance with example embodiments described herein.

[0029] FIG. 4 illustrates a cross-sectional side view of normal pelvic anatomy comparison to progression to bladder prolapse, in accordance with example embodiments described herein.

[0030] FIG. 5 illustrates a process chart for a routine check-up with an automatic assessment of anatomy and / or any anatomical change, in accordance with example embodiments described herein.

[0031] FIGS. 6A-6B are schematic illustrations of an example method of diagnosing a patient presenting with pelvic organ prolapse (POP)-related symptoms involving: (a) automatic progress assessment and (b) manual progress assessment, in accordance with example embodiments described herein.

[0032] FIG. 7 shows a schematic illustration of an example image processing pipeline for automatic diagnosis of POP using resting state, low field MRI, in accordance with example embodiments described herein.

[0033] FIG. 8 shows a schematic illustration of an example artificial intelligence (Al) classification pipeline for diagnosis of POP using low field MRI and Physical Examination, in accordance with example embodiments described herein.

[0034] FIG. 9 shows a schematic illustration of an example Al-based risk stratification using longitudinal, low field MRI exams to identify POP development or progression, in accordance with example embodiments described herein.

[0035] FIG. 10 shows a schematic illustration of an example pipeline for prediction of POP treatment response using a multimodal Al regression model and low field MRI derived velocity metrics, in accordance with example embodiments described herein.Atty Dkt No.: 49880-722601

[0036] FIG. 11 shows a schematic illustration of an example Al model for assisting the clinician in assessing longitudinal changes in pelvic anatomy, in accordance with example embodiments described herein.

[0037] FIG. 12A shows a schematic illustration of a magnetic resonance imaging system, in accordance with various embodiments.

[0038] FIG. 12B illustrates an exploded view of the magnetic resonance imaging system shown in FIG. 12A

[0039] FIG. 12C shows a schematic front view of the magnetic resonance imaging system shown in FIG. 12A, in accordance with various embodiments.

[0040] FIG. 12D shows a schematic side view of the magnetic resonance imaging system shown in FIG. 12A, in accordance with various embodiments.

[0041] FIG. 13 shows a schematic view of an implementation of a magnetic imaging apparatus, according to various embodiments.

[0042] FIG. 14 shows a schematic view of an implementation of a magnetic imaging apparatus, according to various embodiments.

[0043] FIG. 15 shows a schematic front view of a magnetic resonance imaging system 500, according to various embodiments.

[0044] FIG. 16A shows an example schematic illustration of a radio frequency receive coil (RF- RX) array including individual coil elements, in accordance with various embodiments.

[0045] FIG. 16B shows an example illustration of a loop coil along with example calculations for a loop coil magnetic field, in accordance with various embodiments.

[0046] FIG. 16C shows an example X-Y chart illustrating the magnetic field as a function of radius of a loop coil, in accordance with various embodiments disclosed herein.

[0047] FIG. 16D shows a cross-sectional illustration of a portion of the human body, namely in the area of the prostate.

[0048] FIG. 17 shows a flowchart for a method of performing magnetic resonance imaging, according to various embodiments.

[0049] FIG. 18 shows a flowchart for another method of performing magnetic resonance imaging, according to various embodiments.

[0050] FIG. 19 shows a flowchart for a method of performing a scan on a magnetic resonance imaging system, according to various embodiments.

[0051] FIG. 20 shows a flowchart for another method of performing a scan on a magnetic resonance imaging system, according to various embodiments.Atty Dkt No.: 49880-722601

[0052] FIGS. 21A-21X illustrate various positions of patient depending on the type of anatomical scan for imaging in a magnetic resonance imaging system, according to various embodiments.

[0053] FIG. 22 shows a schematic view of figure-8 coils described herein disposed within the housing of an MRI system in accordance with example embodiments described herein.

[0054] FIG. 23 shows an example computer system that is programmed or otherwise configured to implement methods provided herein in accordance with example embodiments described herein.DETAILED DESCRIPTION OF THE INVENTIONOverview

[0055] Pelvic organ prolapse may occur when the pelvic floor muscles and connective tissues that normally support pelvic organs weaken - resulting in one or more organs (bladder, uterus, vaginal vault, rectum or small intestine) descending into or protruding from the vaginal canal. This may manifest as specific types like cystocele (bladder prolapse), rectocele (rectum prolapse), enterocele (small intestine prolapse) or uterine prolapse. The documented history dates back to over 4000 years but remains largely under-discussed due to associated stigma. Key causes may include vaginal childbirth (may injure the pelvic floor), aging, menopause (hormonal changes and tissue weakening), obesity, chronic increases in abdominal pressure from coughing, constipation or heavy lifting, prior pelvic surgery like hysterectomy and genetic factors. Many of these factors may accumulate over a person’s lifetime and may become more evident postmenopause. =

[0056] Diagnosing pelvic organ prolapse (POP) can include a simple pelvic exam and a discussion of the patient’s symptoms and medical history. Imaging, such as ultrasound, dynamic pelvic MRI, and fluoroscopic cystocolpoproctography (CCP) may occasionally be used to aid in diagnosis or help with surgical planning. However, ultrasound may not be useful due to its inherent limitations related to image quality. MRI can be prohibitively expensive and inaccessible to most patients, while fluoroscopy can be undesirable due to exposure to unnecessary ionizing radiation and minimal benefit. The primary diagnostic can involve visual inspection and measurement using pelvic disorder scoring systems like POP-Q with optional aid of speculum.

[0057] Magnetic resonance imaging (MRI) systems have primarily been focused on leveraging an enclosed form factor. This form factor includes surrounding the imaging region with electromagnetic field producing materials and imaging system components. An MRI system can include a cylindrical bore magnet where the patient is placed within the tube of the magnet forAtty Dkt No.: 49880-722601 imaging. Components, such as radio frequency (RF) transmission (TX) and reception (RX) coils, gradient coils and permanent magnet can be positioned accordingly to produce the necessary magnetic field within the tube for imaging the patient.

[0058] Some MRI systems can thus have multiple disadvantages, some examples of which are provided as follows. First, the footprint for these systems can be substantial, often requiring that MRI systems be housed in hospitals or external imaging centers. Second, closed MRI systems can make interventions (e.g., image guided interventions such as MRI guided biopsies, treatment planning, robotic surgeries and radiation treatments) much more difficult. Third, the placement of the primary magnet components discussed above may need to surround the patient, which can severely limit the movement of the patient, and may cause panic in patients situated inside the MRI system or additional discomfort during situating or removing the patient to and from within the imaging region. In some MRI systems, the patient can be placed between two large plates to relieve some physical restrictions on patient placement. Further, for POP applications, the supine position in MRIs can underestimate pelvic organ prolapse because gravity and intra-abdominal pressures that exacerbate prolapse in daily life are absent or even reversed. Dynamic MRI protocols that attempt to capture Valsalva or defecation phases, patient compliance and space constraint may limit accurate diagnosis. Regardless, a need exists to provide imaging configurations in MRI systems to reduce footprint, allowing for in office MRI procedures across various regions of interest. A need also exists to provide MRI system designs that allow for various image guided interventions. Moreover, a need exists to provide MRI system designs that improve the patient experience and ease at which a patient can be scanned.

[0059] Provided herein are systems and methods to aid in the diagnosis, grading, and screening for pelvic organ prolapse (POP). The systems and methods can be performed by tracking POP onset and progression over time using an office-based portable MRI system. Screening, diagnosis, and progression analysis may be performed by analyzing pelvic organ and pelvic floor muscle positions and dimensions. In addition, the systems and methods can provide treatment recommendations to a physician based on a diagnosis and grade of the prolapse. Using the systems and methods described herein, pelvic MRI imaging can be performed as part of a routine patient check-up and prolapse can be diagnosed earlier and before symptoms may start to appear. An earlier diagnosis may allow patients to begin treatment (e.g., a pelvic floor physical therapy) earlier and prevent POP from progressing further. Furthermore, the systems and methods described herein can be used to monitor a patient’s progress once POP is diagnosed and a treatment is prescribed, allowing a physician to change the treatment plan if progress is not being made.Atty Dkt No.: 49880-722601

[0060] Described herein is a method for pelvic floor prolapse screening, diagnosis, grading, and treatment planning using an office-based portable MRI. Imaging can be performed with a patient positioned in front of the MRI (e.g., in high lithotomy, as shown in FIG. 1) or in a seated position with the MRI in a horizontal orientation (as shown in FIG. 2). FIG. 1 shows a screening system 100 with a subject positioned in high lithotomy 105 in front of a portable MRI 110. FIG. 2 shows a screening system 200 with a subject in a seated position 205 positioned on a portable MRI in a horizontal orientation 210. In some embodiments, the portable MRI comprises a commode. In some embodiments, the subject can sit on the commode during operation of the portable MRI. In some cases, the commode can comprise an intermediate contact between the MRI and the patient, such that the surface of the MRI is in indirect contact with the patient. Various metrics, such as relative positions, angles, and dimensions of pelvic organs and pelvic floor muscles, can be used to screen for early signs of prolapse onset, or diagnose for the degree of prolapse. Images of the same patient acquired over time can be overlaid and analyzed to detect anatomical changes and determine the progression or regression of prolapse. These analyses may be done manually by the physician, or automatically using an Al-based classifier described herein. The classifier can be trained on MR images of normal anatomy, different types and grades of POP, and images of POP over time progressing from its early onset to a proper diagnosis in the same patients. Ground truth labels of organs, types, and grades of POP can be established by experts (e.g., radiologists) specializing in interpretation of female pelvic MRIs.

[0061] FIG. 3 illustrates an example schematic of a system for a female subject visiting a physician for a routine checkup 300. When the subject visits their physician for a routine checkup, they may undergo pelvic MR imaging 302. Compared to conventional MRIs, the MR imager presented is a small form-factor permanent magnet based low-field scanner that can easily be placed in an office and does not require the setup of a radiology lab. Upon completion of the MR scan 304, the physician will assess and interpret the images 306. If an early onset is suspected 310, the patient may be able to obviate a surgical intervention through physical therapy of the pelvis and may come back for rescans to track the progress or deterioration of the condition (as shown in FIG. 4) through comparison with previously acquired images (314, 316, 318, 320). If the patient anatomy is normal 308, the patient may be rescreened at a periodic check-up 302. Comparison with previously acquired images will be performed through co-regi strati on and manual assessment of changes by the physician. If POP is already present 312, the physician will diagnose and stage the disease based on the images and decide upon a treatment appropriate for the disease condition, location and the grade (328, 326, 324, 322). Further, the imager may beAtty Dkt No.: 49880-722601 used to manually assess recovery after the treatment and enables the physician to intervene sooner if needed (320, 322).

[0062] An example illustration of progression 400 of normal pelvic anatomy 405 to bladder prolapse 410 is shown in FIG. 4. Progression analysis may be made by comparison with previously acquired images. Comparison with previously acquired images can be performed through co-regi strati on and manual assessment of changes by the physician. If POP is already present, the physician can diagnose and stage the disease based on the images and decide upon a treatment appropriate for the disease condition, location and the grade. Further, the imager may be used to manually assess recovery after the treatment and enables the physician to intervene sooner if needed.

[0063] FIG. 5 illustrates the process flow chart for a routine check-up with an automatic assessment of anatomy and / or any anatomical changes 500. Upon completion of the MR scan 504, the Al-based classifier 506 analyzes the images and distinguishes normal anatomical variations 508 from any abnormalities 510, 512. The classifier classifies the images into normal 508, early onset 510, and POP diagnosis 512 which may include staging. If an early onset 519 is suspected, the patient may be able to obviate a surgical intervention through physical therapy of the pelvis 514 and may come back for rescans to track the progress or deterioration of the condition through comparison with previously acquired images. If POP is diagnosed 512, the classifier also provides the staging, and combined imaging and staging provides the physician with the information to decide upon a treatment 514, 522 appropriate for the disease condition, location and the grade. Further, the imager may be used to assess recovery after the treatment and enables the physician to intervene sooner if needed 516, 518, 520, 522.

[0064] FIGS. 6A-6B illustrate the process chart for a female patient presenting with POP -related symptoms and being diagnosed with POP involving automatic progress assessment 600 and manual progress assessment 610. When the subject visits their physician for an assessment of their symptoms, they may also go through pelvic MR and / or ultrasound imaging. In FIG. 6A, an Al-based classifier can analyze the image and may provide a diagnosis and stage for the prolapse, and combined imaging and staging may provide the physician with the information to decide upon a treatment option appropriate for the disease condition, location and the grade. Further, the imager may be used to automatically assess recovery after the treatment and enables the physician to intervene sooner if needed. In the process shown in FIG. 6B, the aforementioned process can be performed using co-registration with previously acquired images and manual assessment of anatomy and / or anatomical changes by the physician.Atty Dkt No.: 49880-722601Systems and Methods

[0065] Provided herein is a magnetic resonance imaging (MRI) system for the screening of pelvic organ prolapse (POP). In some embodiments, the MRI system comprises (a) a housing comprising a surface for contact with a subject and (b) a radio frequency receive (RF RX) coil network. In some embodiments, the RF RX coil network is configured to enable imaging in a region of interest. In some embodiments, the region of interest is external to the surface of the housing by a distance. In some embodiments, the distance ranges from about 80 mm to about 120 mm.

[0066] In some embodiments, the RF RX coil network is configured to fully cover the surface such that there is no access aperture or bore on the surface nearest the region of interest or through the housing. In some embodiments, the RF RX coil network is configured for imaging external to the surface by a distance of about 100 mm.

[0067] In some embodiments, the RF RX coil network comprises a plurality of RF RX coils. In some embodiments, the RF RX coil network comprises a plurality of interconnected RF RX coils. In some embodiments, the RF RX coil network comprises a plurality of coupled RF RX coils. In some embodiments, a number of turns and loops of the RF RX coil is configured to be adjustable to cover an entire space between legs of the subject such that the region of interest is entirely or partially covered. In some embodiments, the housing further comprises a radio frequency transmit (RF TX) coil proximate to the surface of the housing. In some embodiments, the RF TX coil is configured to generate an electromagnetic field in the region of interest.

[0068] In some embodiments, the RF TX coil comprises a plurality of figure-8 coils arranged proximal the surface. In some embodiments, the plurality of figure-8 coils are configured to generate a varying magnetic RF field within the region of interest. In some embodiments, the plurality of figure-8 coils are orthogonal to each other. In some embodiments, the plurality of figure-8 coils are tunable to same radiofrequency (RF) resonant frequencies. In some embodiments, the plurality of figure-8 coils are tunable to different RF resonant frequencies. In some embodiments, the plurality of figure-8 coils are configured to generate a uniform magnetic RF field within the region of interest. In some embodiments, the system further comprises an electromagnet configured to generate an electromagnetic field in the region of interest.

[0069] In some embodiments, the housing further comprises a gradient coil set positioned proximate to the surface. In some embodiments, the gradient coil set is configured to generate an electromagnetic field in the region of interest. In some embodiments, the gradient coil set comprises a single-sided gradient coil set.Atty Dkt No.: 49880-722601

[0070] In some embodiments, the MRI system is configured to be used for one or more of diagnosis, grading, treatment planning, or monitoring of POP. In some embodiments, the MRI system comprises a magnetic field strength of less than about 0.5 T. In some embodiments, the MRI system comprises one or more of an open or single-sided MRI. In some embodiments, the housing comprises a bore. In some embodiments, the MRI system is configured to be used in an office setting without shielding or floor reinforcements. In some embodiments, the MRI system comprises at least one permanent magnet configured for use without superconducting material.

[0071] In some embodiments, the RF RX coil is configured to capture images of the subject when the subject is in a position in front of or on top of the MRI. In some embodiments, the position is a high lithotomy, an inclined lithotomy, or a seated position over the MRI. In some embodiments, the RF RX coil is configured to capture images of the subject when the subject is in contact with the surface of the MRI in the high lithotomy, the inclined lithotomy, or the seated position. In some embodiments, the housing is configured to be positioned such that a central axis thereof is perpendicular to a floor when capturing images of the subject in the high lithotomy or the inclined lithotomy. In some embodiments, the housing is configured to be positioned such that a central axis thereof is parallel to a floor when capturing images of the subject in the seated position.

[0072] In some embodiments, the MRI system is configured to be usable in a first mode and a second mode. In some embodiments, the first mode comprises capturing images of the subject in the high lithotomy or the inclined lithotomy when the housing is positioned such that a central axis thereof is perpendicular to a floor, and wherein the second mode comprises capturing images of the subject in the seated position when the housing is positioned such that a central axis thereof is parallel to the floor. In some embodiments, the MRI system is configured to record dynamic imaging of activities applying pressure to pelvic organs of the subject.

[0073] In some embodiments, the system further comprises a processor configured to run a computer-implemented method. In some embodiments, the computer-implemented method comprises one or more of automatically screening, diagnosing, or grading POP. In some embodiments, the computer-implemented method comprises employing a machine learning based system trained on at least one training dataset. In some embodiments, the training dataset comprises at least one of a dataset comprising data from multiple subjects, a dataset comprising longitudinal data from one subject, or a combination thereof.

[0074] In some embodiments, the computer-implemented method comprises analyzing images comprising the dataset comprising longitudinal data from one subject acquired over time to manually detect and quantify anatomical changes over time. In some embodiments, theAtty Dkt No.: 49880-722601 computer-implemented method comprises analyzing images comprising the dataset comprising longitudinal data from one subject acquired over time to automatically detect and quantify anatomical changes over time. In some embodiments, the computer-implemented method comprises detecting and quantifying anatomical changes over time automatically through coregistrations with prior images or predefined protocols. In some embodiments, the computer- implemented method comprises determining whether the anatomical changes are of a normal or an abnormal characteristic and grading the anatomical changes if a prolapse is detected.

[0075] In some embodiments, the computer-implemented method comprises employing one or more of an Al-based segmentation, classification, or regression model to assess POP via one or more of detection, grading, surveillance, or treatment recommendations. In some embodiments, the computer-implemented method comprises providing treatment recommendations based on a POP determination and grade. In some embodiments, the computer-implemented method comprises detecting early anatomical changes. In some embodiments, the computer-implemented method comprises detecting the early anatomical changes automatically. In some embodiments, the computer-implemented method comprises monitoring progress of the POP via images of the subject acquired during a treatment, after a treatment, or a combination thereof. In some embodiments, the computer-implemented method comprises recommending at least one alternative treatment if a predetermined treatment progress threshold is not achieved. In some embodiments, a predetermined treatment progress is determined based on the monitored progress of the POP. In some embodiments, the computer-implemented method comprises providing feedback to a user. In some embodiments, the user is different from the subject. In some embodiments, the feedback comprises a progress of a treatment. In some embodiments, the feedback is determined from analyzed changes in anatomy across multiple images.

[0076] In some embodiments, the computer-implemented method comprises recommending a treatment to aid a physician in decision making. In some embodiments, the computer- implemented method comprises training a classifier model on one or more of MR images of normal anatomy, different types and grades of POP, or images of POP progressing over time from early onset to proper diagnosis. In some embodiments, the computer-implemented method comprises using an Al model to perform segmentation and landmark identification on low field MRI comprising a static component or a dynamic component for grading of POP. In some embodiments, the computer-implemented method comprises using a classification model for determination of POP based on continuous distance metrics from one or more of a static low field MRI exam, a dynamic low field MRI exam, or a physical examination. In some embodiments, the computer-implemented method comprises using an Al model for visualizationAtty Dkt No.: 49880-722601 of longitudinal low field MRI data with a static component or a dynamic component. In some embodiments, the computer-implemented method comprises using an Al model for identification of hotspots indicating progressing prolapse or resolving prolapse.

[0077] In some embodiments, the computer-implemented method comprises using a spatiotemporal model using longitudinal low field MRI data with a static component or a dynamic component for prediction of anatomical segmentation masks at a future time point. In some embodiments, the computer-implemented method comprises using a spatio-temporal model using longitudinal low field MRI data with a static component or a dynamic component for prediction of low field MRI at a future time point. In some embodiments, the computer- implemented method comprises using a classification model and the low field MRI prediction model to compare low field MRI at the future time point and predicted low field MRI at the future time point to evaluate whether a health condition deviated from an expected trajectory. In some embodiments, the computer-implemented method comprises using a classification model and the low field MRI prediction model to compare low field MRI at the future time point and predicted low field MRI at the future time point to evaluate whether prolapse deviated from an expected trajectory. In some embodiments, the computer-implemented method comprises using a spatio-temporal model for generating trajectory and velocity metrics from longitudinal low field MRI with a static component or a dynamic component. In some embodiments, the computer- implemented method comprises using a prognostic model for one or more of risk stratification or outcome prediction via one or more of a) trajectory and velocity metrics derived from low field MRI, b) physical examination-based metrics, c) clinical variables, or d) symptom and quality of life scores.

[0078] In some embodiments, the MRI system is configured to be rotatable 90 degrees such that the system has an imaging field of view on top of the MRI system. In some embodiments, the MRI system is configured for static and dynamic magnetic resonance (MR) imaging.

[0079] In some embodiments, a shape and orientation of the housing are configured to use gravity and intra-abdominal natural pressures to increase MR imaging access to the region of interest during static MR imaging. In some embodiments, the static MR imaging comprises a first imaging protocol. In some embodiments, the first imaging protocol comprises a scout scan configured to determine a position of the subject within a field of view of the MRI system. In some embodiments, the first imaging protocol comprises T2-weighted fast spin echo imaging of about 24 cm to about 30 cm in the axial or coronal plane and about 30 to about 40 cm in the sagittal plane. In some embodiments, the T2-weighted fast spin echo imaging comprises from about a 3 mm to about a 5 mm static slice thickness with less than about a 1 mm gap. In someAtty Dkt No.: 49880-722601 embodiments, the first imaging protocol comprises T1 fast spin echo imaging. In some embodiments, the first imaging protocol comprises fat saturated T1 imaging. In some embodiments, the first imaging protocol comprises diffusion weighted imaging. In some embodiments, the static MR imaging is configured to screen for early onset of POP and to detect one or more of cystocele tendencies, uterine / vault descent, perineal descent, or levator ballooning.

[0080] In some embodiments, the dynamic MR imaging is configured to provide an equivalent quantitative pelvic organ prolapse quantification (POP-Q) score. In some embodiments, the dynamic MR imaging comprises a second imaging protocol. In some embodiments, the second imaging protocol comprises T2 static fast spin echo imaging. In some embodiments, the second imaging protocol comprises T1 static fast spin echo imaging.

[0081] Provided herein is a method of performing magnetic resonance (MR) imaging. In some embodiments, the method comprises: (a) inputting patient parameters into a magnetic resonance imaging (MRI) system, the system comprising: (i) a housing comprising a surface for contact with a subject; and (ii) a radio frequency receive (RF RX) coil network; (b) activating the RF RX coil network to obtain imaging data in the region of interest; (c) reconstructing obtained imaging data to produce an output image for analysis; and (d) displaying the output image for user review and annotation. In some embodiments, the region of interest is external to the surface of the housing by a distance ranging from about 80 mm to about 120 mm

[0082] In some embodiments, the RF RX coil network is configured to fully or partially cover the surface such that there is no access aperture on the surface nearest the region of interest. In some embodiments, the region of interest is external to the surface of the housing by about 100 mm.

[0083] In some embodiments, the RF RX coil network comprises a plurality of RF RX coils. In some embodiments, the RF RX coil network comprises a plurality of interconnected RF RX coils. In some embodiments, the RF RX coil network comprises a plurality of coupled RF RX coils. In some embodiments, a number of turns and loops of the RF RX coil is configured to cover an entire space between legs of the subject such that the region of interest is entirely or partially covered. In some embodiments, the housing further comprises a radio frequency transmit (RF TX) coil proximate to the surface of the housing. In some embodiments, the RF TX coil is configured to generate an electromagnetic field in the region of interest.

[0084] In some embodiments, the RF TX coil comprises a plurality of figure-8 coils arranged proximal the surface. In some embodiments, the plurality of figure-8 coils are configured to generate a varying magnetic RF field within the region of interest. In some embodiments, theAtty Dkt No.: 49880-722601 plurality of figure-8 coils are orthogonal to each other. In some embodiments, the method further comprises tuning the plurality of figure-8 coils to same radiofrequency (RF) resonant frequencies. In some embodiments, the method further comprises tuning the plurality of figure-8 coils to different RF resonant frequencies. In some embodiments, the method further comprises generating, via the plurality of figure-8 coils, a uniform magnetic RF field within the region of interest.

[0085] In some embodiments, the method further comprises generating an electromagnetic field in the region of interest via activating an electromagnet in the MRI system. In some embodiments, the method further comprises generating an electromagnetic field in the region of interest via activating a gradient coil set disposed in the housing and positioned proximate to the surface. In some embodiments, the gradient coil set comprises a single-sided gradient coil set.

[0086] In some embodiments, the method further comprises, using the MRI system for one or more of diagnosis, grading, treatment planning, or monitoring of POP. In some embodiments, the MRI system comprises a magnetic field strength of less than about 0.5 T. In some embodiments, the MRI system comprises one or more of an open or single-sided MRI. In some embodiments, the housing comprises a bore. In some embodiments, the MRI system is configured to be used in an office setting without shielding or floor reinforcements. In some embodiments, the method further comprises using at least one permanent magnet configured without superconducting material. In some embodiments, the method further comprises capturing images of the subject, via the RF RX coil, when the subject is in a position in front of or on top of the MRI. In some embodiments, the position is a high lithotomy, an inclined lithotomy, or a seated position over the MRI. In some embodiments, the method further comprises capturing images of the subject, via the RF RX coil, when the subject is in contact with the surface of the MRI in the high lithotomy, the inclined lithotomy, or the seated position. In some embodiments, the method further comprises positioning the housing such that a central axis thereof is perpendicular to a floor when capturing images of the subject in the high lithotomy or the inclined lithotomy. In some embodiments, the method further comprises positioning the housing such that a central axis thereof is parallel to a floor when capturing images of the subject in the seated position. In some embodiments, the method further comprises using the MRI system in a first mode and a second mode. In some embodiments, the first mode comprises capturing images of the subject in the high lithotomy or the inclined lithotomy when the housing is positioned such that a central axis thereof is perpendicular to a floor, and wherein the second mode comprises capturing images of the subject in the seated position when the housing is positioned such that a central axis thereof is parallel to the floor. In someAtty Dkt No.: 49880-722601 embodiments, the method further comprises recording, via the MRI system, dynamic imaging of activities applying pressure to pelvic organs of the subject. In some embodiments, the method further comprises one or more of automatically screening, diagnosing, or grading POP.

[0087] In some embodiments, the method further comprises employing a machine learning based system trained on at least one training dataset. In some embodiments, the training dataset comprises at least one of a dataset comprising data from multiple subjects, a dataset comprising longitudinal data from one subject, or a combination thereof. In some embodiments, the method further comprises analyzing images comprising the dataset comprising longitudinal data from one subject acquired over time to manually detect and quantify anatomical changes over time. In some embodiments, the method further comprises analyzing images comprising the dataset comprising longitudinal data from one subject acquired over time to automatically detect and quantify anatomical changes over time. In some embodiments, the method further comprises detecting and quantifying anatomical changes over time automatically through co-registrations with prior images or predefined protocols. In some embodiments, the method further comprises determining whether the anatomical changes are of a normal or an abnormal characteristic and grading the anatomical changes if a prolapse is detected. In some embodiments, the method further comprises employing one or more of an Al-based segmentation, classification, or regression model to assess POP via one or more of detection, grading, surveillance, or treatment recommendations.

[0088] In some embodiments, the method further comprises providing treatment recommendations based on a POP determination and grade. In some embodiments, the method further comprises detecting early anatomical changes. In some embodiments, the method further comprises detecting the early anatomical changes automatically. In some embodiments, the method further comprises monitoring progress of the POP via images of the subject acquired during a treatment, after a treatment, or a combination thereof. In some embodiments, the method further comprises recommending at least one alternative treatment if a predetermined treatment progress threshold is not achieved. In some embodiments, a predetermined treatment progress is determined based on the monitored progress of the POP. In some embodiments, the method further comprises providing feedback to a user. In some embodiments, the user is different from the subject. In some embodiments, the feedback comprises a progress of a treatment. In some embodiments, the feedback is determined from analyzed changes in anatomy across multiple images. In some embodiments, the method further comprises recommending a treatment to aid a physician in decision making.Atty Dkt No.: 49880-722601

[0089] In some embodiments, the method further comprises training a classifier model on one or more of MR images of normal anatomy, different types and grades of POP, or images of POP progressing over time from early onset to proper diagnosis. In some embodiments, the method further comprises using an Al model to perform segmentation and landmark identification on low field MRI comprising a static component or a dynamic component for grading of POP. In some embodiments, the method further comprises using a classification model for determination of POP based on continuous distance metrics from one or more of a static low field MRI exam, a dynamic low field MRI exam, or a physical examination. In some embodiments, the method further comprises using an Al model for visualization of longitudinal low field MRI data with a static component or a dynamic component. In some embodiments, the method further comprises using an Al model for identification of hotspots indicating progressing prolapse or resolving prolapse.

[0090] In some embodiments, the method further comprises using a spatio-temporal model using longitudinal low field MRI data with a static component or a dynamic component for prediction of anatomical segmentation masks at a future time point. In some embodiments, the method further comprises using a spatio-temporal model using longitudinal low field MRI data with a static component or a dynamic component for prediction of low field MRI at a future time point. In some embodiments, the method further comprises using a classification model and the low field MRI prediction model to compare low field MRI at the future time point and predicted low field MRI at the future time point to evaluate whether a health condition deviated from an expected trajectory. In some embodiments, the method further comprises using a classification model and the low field MRI prediction model to compare low field MRI at the future time point and predicted low field MRI at the future time point to evaluate whether prolapse deviated from an expected trajectory. In some embodiments, the method further comprises using a spatiotemporal model for generating trajectory and velocity metrics from longitudinal low field MRI with a static component or a dynamic component. In some embodiments, the method further comprises using a prognostic model for one or more of risk stratification or outcome prediction via one or more of a) trajectory and velocity metrics derived from low field MRI, b) physical examination-based metrics, c) clinical variables, or d) symptom and quality of life scores.

[0091] In some embodiments, the MRI system is configured to be rotatable 90 degrees such that the system has an imaging field of view on top of the MRI system. In some embodiments, the method further comprises executing, via the MRI system, static and dynamic magnetic resonance (MR) imaging. In some embodiments, a shape and orientation of the housing are configured toAtty Dkt No.: 49880-722601 use gravity and intra-abdominal natural pressures to increase MR imaging access to the region of interest during static MR imaging.

[0092] In some embodiments, the static MR imaging comprises a first imaging protocol. In some embodiments, the method further comprises determining, via a scout scan, a position of the subject within a field of view of the MRI system. In some embodiments, the first imaging protocol comprises T2-weighted fast spin echo imaging of about 24 cm to about 30 cm in the axial or coronal plane and about 30 to about 40 cm in the sagittal plane. In some embodiments, the T2-weighted fast spin echo imaging comprises from about a 3 mm to about a 5 mm static slice thickness with less than about a 1 mm gap. In some embodiments, the first imaging protocol comprises T1 fast spin echo imaging. In some embodiments, the first imaging protocol comprises fat saturated T1 imaging. In some embodiments, the first imaging protocol comprises diffusion weighted imaging. In some embodiments, the method further comprises screening for early onset of POP and detecting one or more of cystocele tendencies, uterine / vault descent, perineal descent, or levator ballooning via the static MR imaging.

[0093] In some embodiments, the method further comprises providing an equivalent quantitative pelvic organ prolapse quantification (POP-Q) score via the dynamic MR imaging. In some embodiments, the dynamic MR imaging comprises a second imaging protocol. In some embodiments, the second imaging protocol comprises T2 static fast spin echo imaging. In some embodiments, the second imaging protocol comprises T1 static fast spin echo imaging. In some embodiments, the method further comprises executing a subject positioning protocol comprising running at least one scan. In some embodiments, the method further comprises running at least one static scan. In some embodiments, the method further comprises running at least one dynamic scan.Machine Learning Systems

[0094] Described herein are Al-based segmentation, classification and / or regression models for assessment of POP, including detection, diagnosis, grading, surveillance, or treatment response recommendations for POP. Outputs of the Al-based models may include recommendations, diagnosis, visualizations or tools to aid the clinician in decision making related to POP diagnosis or treatment for POP.

[0095] In some embodiments, the model performs segmentation and landmark identification on low field MRI (e.g., a static component or a dynamic component) for calculation of PC Line and distance metrics used in grading of POP. Calculation of distance metrics and binning into grades (e.g., “rule of three”, or “rule of two”) may be done manually using the segmentation masks or asAtty Dkt No.: 49880-722601 part of the algorithm, in which case the clinician is presented directly with the diagnosis, grades, and measurements. FIG. 7 is a schematic illustration of an example image processing method 700 for automatic diagnosis of POP using resting state, low field MRI. In some embodiments, the image processing method comprises acquiring static low field MRI images 702 of a subject using an MRI system described herein. The static low field MRI images can be T2-weighted, Tl- weighted, or multiparametric. Structures of interest are volumetrically segmented using an Al segmentation model. The Al segmentation model can be a 3D segmentation model. In some embodiments, the method comprises using a 3D segmentation model to segment the low field MRI images 704. The 3D segmentation model can comprise a convolutional neural network (CNN) or a vision transformer. The 3D segmentation model can generate PC Line segmentation masks 706. The PC Line segmentation masks can comprise, for example, a pubic symphysis or a sacrococcygeal joint. In some embodiments, relevant distance measurements 716 of the pubococcygeal line (PCL Line) 714 are automatically calculated and binned 718 into Grade 0 (Normal), Grade I (Mild), Grade II (Moderate), and Grade III (Severe) according to the ESUR / ESGAR working group reporting system guidelines. In some embodiments, the binning 718 comprises a cystocele or a urethrocele diagnosis and / or grading 720. In some embodiments, the 3D segmentation model 704 generates an anterior compartment segmentation mask 708. The anterior compartment segmentation mask 708 can comprise segmentation masks of structures including, for example, the bladder or the urethra of the subject. Continuous distance measurements 722 of the anterior compartment segmentation mask 708 can be automatically calculated and binned 718. The binning 718 can comprise a diagnosis or a grading of, for example, uterocervical prolapse or apical prolapse 726. In some embodiments, the 3D segmentation model 704 generates a middle compartment segmentation mask 710. The middle compartment segmentation mask 710 can comprise segmentation masks of structures including, for example, the cervix, the vagina or the vaginal apex of the subject. Continuous distance measurements 722 of the middle compartment segmentation mask 710 can be binned 724. The binning 724 can comprise a diagnosis or a grading of, for example, rectocele or enterocele 732.

[0096] FIG. 8 is a schematic illustration of an example artificial intelligence (Al) classification method 800 for diagnosis of POP using low field MRI and physical examination. In some embodiments, static, low field MRI images 802 are input into a 3D segmentation model 804. The static, low field MRI images 802 can be, for example, T2-weighted, T1 -weighted, or multiparametric. The 3D segmentation model 804 can be, for example, a CNN, or a Vision Transformer. The 3D segmentation model 804 can perform volumetric segmentations of the static low field MRI images 802. The volumetric segmentations can be independently performedAtty Dkt No.: 49880-722601 on static and dynamic MRI images using Al models described herein. The 3D segmentation model 804 can output PC Line segmentation masks 806. The PC Line segmentation masks 806 can comprise segmentation masks of, for example, pubic symphysis segmentation masks or sacrococcygeal joint segmentation masks. The PC Line segmentation 806 can output a pubococcygeal line (PCL Line) 814. Relevant distance measurements of the PCL Line 814 can be automatically calculated 816. The 3D segmentation model 804 can generate anterior compartment segmentation masks 808. The anterior compartment segmentation masks 808 can comprise segmentation masks of, for example, the bladder, or the urethra. Relevant distance measurements of the anterior compartment segmentation masks 808 can be automatically calculated 818. The 3D segmentation model 804 can generate segmentation masks of the middle compartment 810. The middle compartment segmentation masks 810 can comprise, for example, segmentation masks of the cervix, the vagina, or the vaginal apex. Relevant distance measurements 818 of the middle compartment segmentation mask 810 can be automatically calculated. The 3D segmentation model 804 can generate segmentation masks of the posterior compartment 812. The posterior compartment segmentation masks 812 can comprise, for example, segmentation masks of the rectum or the anal canal. Relevant distance measurements 820 of the posterior compartment segmentation mask 812 can be automatically calculated.

[0097] In some embodiments, dynamic, low field MRI images 822 are input into a 3D segmentation model 824. The dynamic, low field MRI images 822 can be, for example, 4D Tl- weighted images generated during squeeze or strain by the subject. The 3D segmentation model 824 can be, for example, a CNN, or a Vision Transformer. The 3D segmentation model 824 can perform volumetric segmentations of the dynamic low field MRI images 822. The 3D segmentation model 824 can output PC Line segmentation masks 826. The PC Line segmentation masks 826 can comprise segmentation masks of, for example, pubic symphysis segmentation masks or sacrococcygeal joint segmentation masks. The PC Line segmentation 826 can output a pubococcygeal line (PCL Line) 834. Relevant distance measurements of the PCL Line 834 can be automatically calculated 836. The 3D segmentation model 824 can generate anterior compartment segmentation masks 828. The anterior compartment segmentation masks 828 can comprise segmentation masks of, for example, the bladder, or the urethra. Relevant distance measurements of the anterior compartment segmentation masks 828 can be automatically calculated 838. The 3D segmentation model 824 can generate segmentation masks of the middle compartment 830. The middle compartment segmentation masks 830 can comprise, for example, segmentation masks of the cervix, the vagina, or the vaginal apex. Relevant distance measurements 838 of the middle compartment segmentation mask 830 can beAtty Dkt No.: 49880-722601 automatically calculated. The 3D segmentation model 824 can generate segmentation masks of the posterior compartment 832. The posterior compartment segmentation masks 832 can comprise, for example, segmentation masks of the rectum or the anal canal. Relevant distance measurements 840 of the posterior compartment segmentation mask 832 can be automatically calculated.

[0098] In some embodiments, the distance measurements 816, 818, 820, 836, 838, and / or 840 can be input as features to a multilabel classification model 850. The multilabel classification model 850 can be, for example, a Random Forest model, or a XGBoost model. The multilabel classification model 850 can output a diagnosis or a grading of cystocele or urethrocele 844, uterocervical prolapse or apical prolapse 846, and / or rectocele or enterocele 848. In some embodiments, the MRI-based measurements 816, 818, 820, 836, 838, and / or 840 and POP-Q measurements from physical examination 842 can be input as features to the Al classification model 800 to output a prediction and / or a grading of POP.

[0099] Provided herein is a spatio-temporal Al model using longitudinal, low field MRI data (static component, dynamic component, or static and dynamic components) for prediction of low field MRI and / or anatomical segmentation masks at a future time point. FIG. 9 is a schematic illustration of an example spatio-temporal Al model which can be used to identify POP development or progression. The spatio-temporal Al model can use low field MRI data inputs at multiple prior timepoints to generate a predicted MRI at the current timepoint. A classification model can generate a similarity score(s) between the predicted MRI and an actual follow up MRI indicative of whether abrupt anatomical changes have occurred which may necessitate intervention. Outputs of the spatio-temporal Al model may aid the clinician in decision making or serve as a triage tool to flag high-risk patients and improve operational efficiency. The classification model can be used in conjunction with an MRI prediction model for assessing similarity between low field MRI at follow-up and predicted low field MRI at the same follow up timepoint to evaluate whether prolapse has deviated from the expected trajectory. If a patient is undergoing treatment, the output may be used as early stopping criteria or to trigger a change in treatment type. If the patient is under surveillance for early signs of deterioration, the output may be used to inform early intervention or adjust follow-up interval spacing.

[0100] In some embodiments, a spatio-temporal Al model 900 can use an initial low field MRI image (tO) 902 and one (tl) 904 or more follow-up low field MRI images (tn) 906 as input features. The initial low field MRI 902 and the one or more follow-up low field MRI images 904, 906 can be input a spatio-temporal predictive model 910. The spatio-temporal predictive model 910 can be, for example, a convolutional neural network-recurrent neural network (CNN-Atty Dkt No.: 49880-722601RNN) model, a convolutional neural network-long short-term memory (CNN-LSTM) model, or a diffusion model. The spatio-temporal predictive model 910 can output a predicted MRI at follow-up 912. The predicted MRI 912 and a follow-up low field MRI 908 can be input as features to a similarity classification model 914. The similarity classification model 914 can be, for example, a CNN. The similarity classification model 914 can output a classification of unexpected progression and a recommended intervention 916 or output a classification of expected progression and recommend continued surveillance 918.

[0101] Provided herein is a spatio-temporal model for generating trajectory and velocity metrics from longitudinal, low field MRI (static component or dynamic component) which may be predictor variables of POP development, progression or treatment response. FIG. 10 is a schematic illustration of an example spatio-temporal model 1000 for prediction of POP treatment response using a multimodal Al regression model and low field MRI derived velocity metrics. A longitudinal, spatiotemporal Al model can use low field MRI data inputs at multiple timepoints to generate anatomical trajectory and velocity features. The features may be associated with a shape, a size, a position, or a signal intensity. These features can be input to a longitudinal, regression model along with symptom scores from a standard questionnaires from multiple time points, clinical predictor variables, and metrics from physical examination at the start of treatment. The regression model can output a treatment response score to aid a physician in assessing whether or not treatment is progressing effectively or is likely to succeed. The score may be further binned into classifications comprising: “low: highly effective,” “medium: potentially effective,” or “high: high risk of recurrence”. The score may be indicative of treatment response, likelihood of development of clinically significant POP, or likelihood of post-surgical recurrence.

[0102] In some embodiments, the spatio-temporal model 1000 can receive one or more of initial POP-Q measurements (e.g., from physical examination) 1002, clinical predictors of POP (e.g., age, BMI, family history of POP, history of hysterectomy, or vaginal parity) 1004, an initial low field MRI image 1006, one or more follow-up low field MRI images 1008, 1010, initial symptoms or quality of life assessments (e.g., UDI-6, IIQ-7, POPDI-6, or PFDI-20 scores) 1014, or scores from one or more additional symptoms or quality of life assessments 1016. The initial 1004 and one or more follow-up low field MRI images 1008, 1010 can be input as features to a spatio-temporal model 1016. The spatio-temporal model 1016 can be a CNN-LSTM, a Large Deformation Diffeomorphic Metric Mapping (LDDMM) with Recurrent Neural Networks (RNNs) (LDDMM-RNN), or a transformer. The spatio-temporal model 1016 can output trajectory or velocity parameters 1018. The trajectory or velocity parameters 1018 and / or theAtty Dkt No.: 49880-722601 features 1002, 1004, 1012, 1014 or 1016 can be input as features to a regression model 1020. The regression model 1020 can be, for example, a Gaussian process model, or a trained RNN. The regression model 1020 can output treatment response score 1022 described herein.

[0103] Provided herein is a model for visualization of longitudinal, low field MRI data (static component or dynamic component) and / or identification of “hotspots” indicating progressing prolapse or resolving prolapse. FIG. 11 is a schematic illustration of an example Al model 1100 for assisting the clinician in assessing longitudinal changes in pelvic anatomy. An image registration model can use low field MRI data inputs at multiple timepoints to generate a displacement vector field (DVF) showing velocity of anatomical changes over time. The DVF can be used as a visualization tool to aid the clinician in assessing an extent of change and / or a prediction of anatomical displacement. The method of visualization may include heatmaps, vector map, 4D image, and / or tabular data.

[0104] In some embodiments, the Al model 1100 receives an initial low field MRI image 1102 and one or more follow-up low field MRI images 1104, 1106, as feature inputs. The initial low field MRI image 1102 and the one or more follow-up low field MRI images 1104, 1106 can be input to a deformable image registration model 1108. The deformable image registration model 1108 can be, for example, a longitudinal voxelmorph model, a voxelmorph-diffeo model, or a CNN-LSTM model. The deformable image registration model 1108 can output an anatomy velocity field 1110. The anatomy velocity field 1110 can be provided to a physician for assessment 1112 to aid the physician in assessing an extent of change and / or a prediction of anatomical displacement.Permanent Magnet

[0105] As discussed herein, and in accordance with various embodiments, the various systems, and various combinations of features that make up the various system embodiments, can include a permanent magnet.

[0106] FIGS. 12A-12B is a schematic illustration of a magnetic resonance imaging system 1200, in accordance with various embodiments. The system 1200 includes a housing 1220. As shown in FIGS. 12A-12B, the housing 1220 includes a permanent magnet 1230, a radio frequency transmit coil 1240, a gradient coil set 1250, an optional electromagnet 1260, a radio frequency receive coil 1270, and a power source 1280. In accordance with various embodiments, the system 1200 can include various electronic components, such as for example, but not limited to a varactor, a PIN diode, a capacitor, or a switch, including a micro-electro- mechanical system (MEMS) switch, a solid-state relay, or a mechanical relay. In accordanceAtty Dkt No.: 49880-722601 with various embodiments, the various electronic components listed above can be configured with the radio frequency transmit coil 1240.

[0107] FIG. 12A is a schematic illustration of a magnetic resonance imaging system 1200, in accordance with various embodiments. FIG. 12B illustrates an exploded view of the magnetic resonance imaging system 1200. FIG. 12C is a schematic front view of the magnetic resonance imaging system 1200, in accordance with various embodiments. FIG. 12D is a schematic side view of the magnetic resonance imaging system 1200, in accordance with various embodiments. As shown in FIG. 12A and FIG. 12B, the magnetic resonance imaging system 1200 includes a housing 1220. The housing 1220 includes a front surface 1225. In accordance with various embodiments, the front surface 1225 can be a concave front surface. In accordance with various embodiments, the front surface 1225 can be a recessed front surface.

[0108] In accordance with various embodiments, the permanent magnet 1230 provides a static magnetic field in a region of interest 1290 (also referred to herein as "given field of view"). In accordance with various embodiments, the permanent magnet 1230 can include a plurality of cylindrical permanent magnets in parallel configuration as shown in FIG. 12C and FIG. 12D. In accordance with various embodiments, the permanent magnet 1230 can include any suitable magnetic materials, including but not limited, to rare-earth based magnetic materials, such as for example, Nd-based magnetic materials, and the like. As shown in FIG. 12A, the main permanent magnet might include an access aperture 1235 for accessing the patient from multiple sides of the system.

[0109] In accordance with various embodiments, the static magnetic field of the permanent magnet 230 may vary from about 50 mT to about 60 mT, about 45 mT to about 65 mT, about 40 mT to about 70 mT, about 35 mT to about 75 mT, about 30 mT to about 80 mT, about 25 mT to about 85 mT, about 20 mT to about 90 mT, about 15 mT to about 95 mT and about 10 mT to about 100 mT to a given field of view. The magnetic field may also vary from about 10 mT to about 15 mT, about 15 mT to about 20 mT, about 20 mT to about 25 mT, about 25 mT to about 30 mT, about 30 mT to about 35 mT, about 35 mT to about 40 mT, about 40 mT to about 45 mT, about 45 mT to about 50 mT, about 50 mT to about 55 mT, about 55 mT to about 60 mT, about 60 mT to about 65 mT, about 65 mT to about 70 mT, about 70 mT to about 75 mT, about 75 mT to about 80 mT, about 80 mT to about 85 mT, about 85 mT to about 90 mT, about 90 mT to about 95 mT, and about 95 mT to about 100 mT. In accordance with various embodiments, the static magnetic field of the permanent magnet 230 may also vary from about 1 mT to about 1 T, about 10 mT to about 195 mT, about 15 mT to about 900 mT, about 20 mT to about 800 mT, about 25 mT to about 700 mT, about 30 mT to about 600 mT, about 35 mT to about 500 mT,Atty Dkt No.: 49880-722601 about 40 mT to about 400 mT, about 45 mT to about 300 mT, about 50 mT to about 200 mT, about 50 mT to about 100 mT, about 45 mT to about 100 mT, about 40 mT to about 100 mT, about 35 mT to about 100 mT, about 30 mT to about 100 mT, about 25 mT to about 100 mT, about 20 mT to about 100 mT, and about 15 mT to about 100 mT.

[0110] In accordance with various embodiments, the permanent magnet 1230 can include a bore 1235 in its center. In accordance with various embodiments, the permanent magnet 1230 may not include a bore. In accordance with various embodiments, the bore 1235 can have a diameter between 1 inch and 20 inches. In accordance with various embodiments, the bore 1235 can have a diameter between 1 inch and 4 inches, between 4 inches and 8 inches, and between 10 inches and 20 inches. In accordance with various embodiments, the given field of view can be a spherical or cylindrical field of view, as shown in FIG. 12A and FIG. 12B. In accordance with various embodiments, the spherical field of view can be between 2 inches and 20 inches in diameter. In accordance with various embodiments, the spherical field of view can have a diameter between 1 inch and 4 inches, between 4 inches and 8 inches, and between 10 inches and 20 inches. In accordance with various embodiments, the cylindrical field of view is approximately between 2 inches and 20 inches in length. In accordance with various embodiments, the cylindrical field of view can have a length between 1 inch and 4 inches, between 4 inches and 8 inches, and between 10 inches and 20 inches.[OHl] In accordance with various embodiments, the permanent magnet system can be rotated 90 degrees such that the system has an imaging field of view on top of the system. This field of view can allow a patient to sit down on top of the system so that the biological material can be imaged with gravity affecting the tissues and structures. This is especially relevant for POP imaging.Radio Frequency Transmit Coil

[0112] As discussed herein, and in accordance with various embodiments, the various systems, and various combinations of features that make up the various system embodiments, can also include a radio frequency transmit coil.

[0113] FIG. 13 is a schematic view of an implementation of a magnetic imaging apparatus 1400, according to various embodiments. As shown in FIG. 13, the apparatus 1300 includes a radio frequency transmit coil 1320 that projects the RF power outwards away from the coil 1320. The coil 1320 has two rings 1322 and 1324 that are connected by one or more rungs 1326. As shown in FIG. 13, the coil 1320 is also connected to a power source 1350a and / or a power source 1350b (collectively referred to herein as "power source 1350"). In accordance with various embodiments, power sources 1350a and 1350b can be configured for power input and / or signalAtty Dkt No.: 49880-722601 input and can be referred to as coil input. In accordance with various embodiments, the power source 1350a and / or 1350b are configured to provide contact via electrical contacts 1352a and / or 1352b (collectively referred to herein as "electrical contact 1352"), and electrical contacts 1354a and / or 1354b (collectively referred to herein as "electrical contact 1354") by attaching the electrical contacts 1352 and 1354 to one or more rungs 1326. The coil 1320 is configured to project a uniform RF field within a field of view 1340. In accordance with various embodiments, the field of view 1340 is a region of interest for magnetic resonance imaging (i.e., imaging region) where a patient resides. Since the patient resides in the field of view 1340 away from the coil 1320, the apparatus 1300 is suitable for use in a single-sided magnetic resonance imaging system. In accordance with various embodiments, the coil 1320 can be powered by two signals that are 90 degrees out of phase from each other, for example, via quadrature excitation.

[0114] In accordance with various embodiments, the coils can be comprised of two or more orthogonal figure-8 shapes arranged on the surface of the magnetic surface. These coils can then be tuned to the same or to different RF resonant frequencies. These coils are designed to generate a uniform or varying magnetic RF field within the region of interest that is off-of the face of the magnet.

[0115] In accordance with various embodiments, the coil 1320 includes the ring 1322 and the ring 1324 that are positioned co-axially along the same axis but at a distance away from each other, as shown in FIG. 13. In accordance with various embodiments, the ring 1322 and the ring 1324 are separated by a distance ranging from about 0.1 m to about 10 m. In accordance with various embodiments, the ring 1322 and the ring 1324 are separated by a distance ranging from about 0.2 m to about 5 m, about 0.3 m to about 2 m, about 0.2 m to about 1 m, about 0.1 m to about 0.8 m, or about 0.1 m to about 1 m, inclusive of any separation distance therebetween. In accordance with various embodiments, the coil 1320 includes the ring 1322 and the ring 1324 that are positioned non-co-axially but along the same direction and separated at a distance ranging from about 0.2 m to about Sm. In accordance with various embodiments, the ring 1322 and the ring 1324 can also be tilted with respect to each other. In accordance with various embodiments, the tilt angle can be from 1 degree to 90 degrees, from 1 degree to 5 degrees, from 5 degrees to 10 degrees, from 10 degrees to 25 degrees, from 25 degrees to 45 degrees, and from 45 degrees to 90 degrees.

[0116] In accordance with various embodiments, the ring 1322 and the ring 1324 have the same diameter. In accordance with various embodiments, the ring 1322 and the ring 1324 have different diameters and the ring 1322 has a larger diameter than the ring 1324, as shown in FIG. 13. In accordance with various embodiments, the ring 1322 and the ring 1324 have differentAtty Dkt No.: 49880-722601 diameters and the ring 1322 has a smaller diameter than the ring 1324. In accordance with various embodiments, the ring 1322 and the ring 1324 of the coil 320 are configured to create the imaging region in the field of view 1340 containing a uniform RF power profile within the field of view 1340, a field of view that is not centered within the RF-TX coil and is instead projected outwards in space from the coil itself.

[0117] In accordance with various embodiments, the ring 1322 has a diameter between about 10 pm and about 10 m. In accordance with various embodiments, the ring 1322 has a diameter between about 0.001 m and about 9 m, between about 0.01 m and about 8 m, between about 0.03 m and about 6 m, between about 0.05 m and about 5 m, between about 0.1 m and about 3 m, between about 0.2 m and about 2 m, between about 0.3 m and about 1.5 m, between about 0.5 m and about 1 m, or between about 0.01 m and about 3 m, inclusive of any diameter therebetween.

[0118] In accordance with various embodiments, the ring 1324 has a diameter between about 10 pm and about 10 m. In accordance with various embodiments, the ring 1324 has a diameter between about 0.001 m and about 9 m, between about 0.01 m and about 8 m, between about 0.03 m and about 6 m, between about 0.05 m and about 5 m, between about 0.1 m and about 3 m, between about 0.2 m and about 2 m, between about 0.3 m and about 1.5 m, between about 0.5 m and about 1 m, or between about 0.01 m and about 3 m, inclusive of any diameter therebetween.

[0119] In accordance with various embodiments, the ring 1322 and the ring 1324 are connected by one or more rungs 1326, as shown in FIG. 13. In accordance with various embodiments, the one or more rungs 1326 are connected to the ring 1322 and 1324 so as to form a single electrical circuit loop (or single current loop). As shown in FIG. 13, for example, one end of the one or more rungs 1326 is connected to the electrical contact 1352 of the power source 1350 and another end of the one or more rungs 1326 be connected to the electrical contact 1354 so that the coil 1320 completes an electrical circuit.

[0120] In accordance with various embodiments, the ring 1322 is a discontinuous ring and the electrical contact 1352 and the electrical contact 1354 can be electrically connected to two opposite ends of the ring 1322 to form an electrical circuit powered by the power source 1350. Similarly, in accordance with various embodiments, the ring 1324 is a discontinuous ring and the electrical contact 1352 and the electrical contact 1354 can be electrically connected to two opposite ends of the ring 1324 to form an electrical circuit powered by the power source 1350.

[0121] In accordance with various embodiments, the rings 1322 and 1324 are not circular and can instead have a cross section that is elliptical, square, rectangular, or trapezoidal, or any shape or form having a closed loop. In accordance with various embodiments, the rings 1322 and 1324 may have cross sections that vary in two different axial planes with the primary axis being aAtty Dkt No.: 49880-722601 circle and the secondary axis having a sinusoidal shape or some other geometric shape. In accordance with various embodiments, the coil 1320 may include more than two rings 1322 and 1324, each connected by rungs that span and connect all the rings. In accordance with various embodiments, the coil 1320 may include more than two rings 1322 and 1324, each connected by rungs that alternate connection points between rings. In accordance with various embodiments, the ring 1322 may contain a physical aperture for access. In accordance with various embodiments, the ring 1322 may be a solid sheet without a physical aperture.

[0122] In accordance with various embodiments, the coil 1320 generates an electromagnetic field (also referred to herein as "magnetic field") strength between about 1 pT and about 10 mT. In accordance with various embodiments, the coil 1320 can generate a magnetic field strength between about 10 pT and about 5 mT, about 50 pT and about 1 mT, or about 100 pT and about 1 mT, inclusive of any magnetic field strength therebetween.

[0123] In accordance with various embodiments, the coil 1320 generates an electromagnetic field that is pulsed at a radio frequency between about 1 kHz and about 2 GHz. In accordance with various embodiments, the coil 1320 generates a magnetic field that is pulsed at a radio frequency between about 1 kHz and about 1 GHz, about 10 kHz and about 800 MHz, about 50 kHz and about 300 MHz, about 100 kHz and about 100 MHz, about 10 kHz and about 10 MHz, about 10 kHz and about 5 MHz, about 1 kHz and about 2 MHz, about 50 kHz and about 150 kHz, about 80 kHz and about 120 kHz, about 800 kHz and about 1.2 MHz, about 100 kHz and about 10 MHz, or about 1 MHz and about 5 MHz, inclusive of any frequencies therebetween.

[0124] In accordance with various embodiments, the coil 1320 is oriented to partially surround the region of interest. In accordance with various embodiments, the ring 1322, the ring 1324, and the one or more rungs 1326 are non-planar to each other. Said another way, the ring 1322, the ring 1324, and the one or more rungs 1326 form a three-dimensional structure that surrounds the region of interest where a patient resides. In accordance with various embodiments, the ring 1322 is closer to the region of interest than the ring 1324, as shown in FIG. 13. In accordance with various embodiments, the region of interest has a size of about 0.1 m to about 1 m. In accordance with various embodiments, the region of interest is smaller than the diameter of the ring 1322. In accordance with various embodiments, the region of interest is smaller than both the diameter of the ring 1324 and the diameter of the ring 1322, as shown in FIG. 13. In accordance with various embodiments, the region of interest has a size that is smaller than the diameter of the ring 1322 and larger than the diameter of the ring 1324.

[0125] In accordance with various embodiments, the ring 1322, the ring 1324, or the rungs 1326 include the same material. In accordance with various embodiments, the ring 1322, the ringAtty Dkt No.: 49880-7226011324, or the rungs 1326 include different materials. In accordance with various embodiments, the ring 1322, the ring 1324, or the rungs 1326 include hollow tubes or solid tubes. In accordance with various embodiments, the hollow tubes or solid tubes can be configured for air or fluid cooling. In accordance with various embodiments, each of the ring 1322 or the ring 1324 or the rungs 1326 includes one or more electrically conductive windings. In accordance with various embodiments, the windings include litz wires or any electrical conducting wires. These additional windings can be used to improve performance by lowering the resistance of the windings at the desired frequency. In accordance with various embodiments, the ring 1322, the ring 1324, or the rungs 1326 include copper, aluminum, silver, silver paste, or any high electrical conducting material, including metal, alloys or superconducting metal, alloys or non-metal. In accordance with various embodiments, the ring 1322, the ring 1324, or the rungs 1326 may include metamaterials.

[0126] In accordance with various embodiments, the ring 1322, the ring 1324, or the rungs 1326 may contain separate electrically non-conductive thermal control channels designed to maintain the temperature of the structure to a specified setting. In accordance with various embodiments, the thermal control channels can be made from electrically conductive materials and integrated as to carry the electrical current.

[0127] In accordance with various embodiments, the coil 1320 includes one or more electronic components for tuning the magnetic field. The one or more electronic components can include a varactor, a PIN diode, a capacitor, or a switch, including a micro-electro-mechanical system (MEMS) switch, a solid-state relay, or a mechanical relay. In accordance with various embodiments, the coil can be configured to include any of the one or more electronic components along the electrical circuit. In accordance with various embodiments, the one or more components can include mu metals, dielectrics, magnetic, or metallic components not actively conducting electricity and can tune the coil. In accordance with various embodiments, the one or more electronic components used for tuning includes at least one of dielectrics, conductive metals, metamaterials, or magnetic metals. In accordance with various embodiments, tuning the electromagnetic field includes changing the current or by changing physical locations of the one or more electronic components. In accordance with various embodiments, the coil is cryogenically cooled to reduce resistance and improve efficiency. In accordance with various embodiments, the first ring and the second ring comprise a plurality of windings or litz wires.

[0128] In accordance with various embodiments, the coil 1320 is configured for a magnetic resonance imaging system that has a magnetic field gradient across the field of view. The field gradient allows for imaging slices of the field of view without using an additionalAtty Dkt No.: 49880-722601 electromagnetic gradient. As disclosed herein, the coil can be configured to generate a large bandwidth by combining multiple center frequencies, each with their own bandwidth. By superimposing these multiple center frequencies with their respective bandwidths, the coil 1320 can effectively generate a large bandwidth over a desired frequency range between about 1 kHz and about 2 GHz. In accordance with various embodiments, the coil 1320 generates a magnetic field that is pulsed at a radio frequency between about 10 kHz and about 800 MHz, about 50 kHz and about 300 MHz, about 100 kHz and about 100 MHz, about 10 kHz and about 10 MHz, about 10 kHz and about 5 MHz, about 1 kHz and about 2 MHz, about 50 kHz and about 150 kHz, about 80 kHz and about 120 kHz, about 800 kHz and about 1.2 MHz, about 100 kHz and about 10 MHz, or about 1 MHz and about 5 MHz, inclusive of any frequencies therebetween.Gradient Coil Set

[0129] As discussed herein, and in accordance with various embodiments, the various systems, and various combinations of features that make up the various system embodiments, can also include a gradient coil set.

[0130] FIG. 14 is a schematic view of an implementation of a magnetic imaging apparatus 1400, according to various embodiments. As shown in FIG. 14, the apparatus 1400 includes a gradient coil set 1420 (also referred to herein as single-sided gradient coil set 1420) that is configured to project a gradient magnetic field outwards away from the coil set 1420 and within a field of view 1430. In accordance with various embodiments, the field of view 1430 is a region of interest for magnetic resonance imaging (i.e., imaging region) where a patient resides. Since the patient resides in the field of view 1430 away from the coil set 1420, the apparatus 1400 is suitable for use in a single-sided MRI system.

[0131] As shown in the figure, the coil set 1420 includes variously sized spiral coils in various sets of spiral coils 1440a, 1440b, 1440c, and 1440d (collectively referred to as "spiral coils 1440"). Each set of the spiral coils 1440 include at least one spiral coil and FIG. 14 is shown to include 3 spiral coils. In accordance with various embodiments, each spiral coil in the spiral coils 1440 has an electrical contact at its center and an electrical contact output on the outer edge of the spiral coil so as to form a single running loop of electrically conducting material spiraling out from the center to the outer edge, or vice versa. In accordance with various embodiments, each spiral coil in the spiral coils 1440 has a first electrical contact at a first position of the spiral coil and a second electrical contact at a second position the spiral coil so as to form a single running loop of electrically conducting material from the first position to the second position, or vice versa.Atty Dkt No.: 49880-722601

[0132] As shown in FIG. 14, the coil set 1420 also includes an aperture 1425 at its center where the spiral coils 1440 are disposed around the aperture 1425. The aperture 1425 itself does not contain any coil material within it for generating magnetic material. The coil set 1420 also includes an opening 1427 on the outer edge of the coil set 1420 to which the spiral coils 1440 can be disposed. Said another way, the aperture 1425 and the opening 1427 define the boundaries of the coil set 1420 within which the spiral coils 1440 can be disposed. In accordance with various embodiments, the coil set 1420 forms a bowl shape with a hole in the center.

[0133] In accordance with various embodiments, the spiral coils 1440 form across the aperture 1425. For example, the spiral coils 1440a are disposed across from the spiral coils 1440c with respect to the aperture 1425. Similarly, the spiral coils 1440b are disposed across from the spiral coils 1440d with respect to the aperture 1425. In accordance with various embodiments, the spiral coils 1440 in the coil set 1420 shown in FIG. 14 are configured to create spatial encoding in the magnetic gradient field within the field of view 1430.

[0134] As shown in FIG. 14, the coil set 1420 is also connected to a power source 450 via electrical contacts 1452 and 1454 by attaching the electrical contacts 1452 and 1454 to one or more of the spiral coils 1440. In accordance with various embodiments, the electrical contact 1452 is connected to one of the spiral coils 1440, which is then connected to other spiral coils 1440 in series and / or in parallel, and one other spiral coil 1440 is then connected to the electrical contact 1454 so as to form an electrical current loop. In accordance with various embodiments, the spiral coils 1440 are all electrically connected in series. In accordance with various embodiments, the spiral coils 1440 are all electrically connected in parallel. In accordance with various embodiments, some of the spiral coils 1440 are electrically connected in series while other spiral coils 1440 are electrically connected in parallel. In accordance with various embodiments, the spiral coils 1440a are electrically connected in series while the spiral coils 1440b are electrically connected in parallel. In accordance with various embodiments, the spiral coils 1440c are electrically connected in series while the spiral coils 1440d are electrically connected in parallel. The electrical connections between each spiral coil in the spiral coils 1440 or each set of spiral coils 1440 can be configured as needed to generate the magnetic field in the field of view 1430.

[0135] In accordance with various embodiments, the coil set 1420 includes the spiral coils 1440 spread out as shown in FIG. 14. In accordance with various embodiments, each of the sets of spiral coils 1440a, 1440b, 1440c, and 1440d are configured in a line from the aperture 1425 to the opening 1427 so that each set of spiral coils is set apart from another by an angle of 90°. In accordance with various embodiments, 1440a and 1440b are set at 45° from one another, andAtty Dkt No.: 49880-7226011440c and 1440d are set at 45° from one another, while 1440c is set 135° on the other side of 1440b and 1440d is set 135° on the other side of 1440a. In essence, any of the sets of spiral coils 1440 can be configured in any arrangement for any number "n" of sets of spiral coils 1440.

[0136] In accordance with various embodiments, the spiral coils 1440 have the same diameter. In accordance with various embodiments, each of the sets of spiral coils 1440a, 1440b, 1440c, and 1440d have the same diameter. In accordance with various embodiments, the spiral coils 1440 have different diameters. In accordance with various embodiments, each of the sets of spiral coils 1440a, 1440b, 1440c, and 1440d have different diameters. In accordance with various embodiments, the spiral coils in each of the sets of spiral coils 1440a, 1440b, 1440c, and 1440d have different diameters. In accordance with various embodiments, 1440a and 1440b have the same first diameter and 1440c and 1440d have the same second diameter, but the first diameter and the second diameter are not the same.

[0137] In accordance with various embodiments, each spiral coil in the spiral coils 1440 has a diameter between about 10 pm and about 10 m. In accordance with various embodiments, each spiral coil in the spiral coils 1440 has a diameter between about 0.001 m and about 9 m, between about 0.005 m and about 8 m, between about 0.01 m and about 6 m, between about 0.05 m and about 5 m, between about 0.1 m and about 3 m, between about 0.2 m and about 2 m, between about 0.3 m and about 1.5 m, between about 0.5 m and about 1 m, or between about 0.01 m and about 3 m, inclusive of any diameter therebetween.

[0138] In accordance with various embodiments, the spiral coils 1440 are connected to form a single electrical circuit loop (or single current loop). As shown in FIG. 14, for example, one spiral coil in the spiral coils 1440 is connected to the electrical contact 1452 of the power source 450 and another spiral coil is connected to the electrical contact 1454 so that the spiral coils 1440 completes an electrical circuit.

[0139] In accordance with various embodiments, the coil set 1420 generates an electromagnetic field strength (also referred to herein as "electromagnetic field gradient" or "gradient magnetic field") between about 1 pT and about 10 T. In accordance with various embodiments, the coil set 1420 can generate an electromagnetic field strength between about 100 pT and about 1 T, about 1 mT and about 500 mT, or about 10 mT and about 100 mT, inclusive of any magnetic field strength therebetween. In accordance with various embodiments, the coil set 1420 can generate an electromagnetic field strength greater than about 1 pT, about 10 pT, about 100 pT, about 1 mT, about 5 mT, about 10 mT, about 20 mT, about 50 mT, about 100 mT, or about 500 mT.

[0140] In accordance with various embodiments, the coil set 1420 generates an electromagnetic field that is pulsed at a rate with a rise-time less than about 100 ps. In accordance with variousAtty Dkt No.: 49880-722601 embodiments, the coil set 1420 generates an electromagnetic field that is pulsed at a rate with a rise-time less than about 1 ps, about 5 ps, about 10 ps, about 20 ps, about 30 ps, about 40 ps, about 50 ps, about 100 ps, about 200 ps, about 500 ps, about 1 ms, about 2 ms, about 5 ms, or about 10 ms.

[0141] In accordance with various embodiments, the coil set 1420 is oriented to partially surround the region of interest in the field of view 1430. In accordance with various embodiments, the spiral coils 1440 are non-planar to each other. In accordance with various embodiments, the sets of spiral coils 1440a, 1440b, 1440c, and 1440d are non-planar to each other. Said another way, the spiral coils 1440 and each of the sets of spiral coils 1440a, 1440b, 1440c, and 1440d form a three-dimensional structure that surrounds the region of interest in the field of view 1430 where a patient resides.

[0142] In accordance with various embodiments, the spiral coils 1440 include the same material. In accordance with various embodiments, the spiral coils 1440 include different materials. In accordance with various embodiments, the spiral coils in set 1440a include the same first material, the spiral coils in set 1440b include the same second material, the spiral coils in set 1440c include the same third material, the spiral coils in set 1440d include the same fourth material, but the first, second, third and fourth materials are different materials. In accordance with various embodiments, the first and second materials are the same material, but that same material is different from the third and fourth materials, which are the same. In essence, any of the spiral coils 1440 can be of the same material or different materials depending on the configuration of the coil set 1420.

[0143] In accordance with various embodiments, the spiral coils 1440 include hollow tubes or solid tubes. In accordance with various embodiments, the spiral coils 1440 include one or more windings. In accordance with various embodiments, the windings include litz wires or any electrical conducting wires. In accordance with various embodiments, the spiral coils 1440 include copper, aluminum, silver, silver paste, or any high electrical conducting material, including metal, alloys or superconducting metal, alloys or non-metal. In accordance with various embodiments, the spiral coils 1440 include metamaterials.

[0144] In accordance with various embodiments, the coil set 1420 includes one or more electronic components for tuning the magnetic field. The one or more electronic components can include a PIN diode, a mechanical relay, a solid-state relay, or a switch, including a micro electro-mechanical system (MEMS) switch. In accordance with various embodiments, the coil can be configured to include any of the one or more electronic components along the electrical circuit. In accordance with various embodiments, the one or more components can include muAtty Dkt No.: 49880-722601 metals, dielectrics, magnetic, or metallic components not actively conducting electricity and can tune the coil. In accordance with various embodiments, the one or more electronic components used for tuning includes at least one of conductive metals, metamaterials, or magnetic metals. In accordance with various embodiments, tuning the electromagnetic field includes changing the current or by changing physical locations of the one or more electronic components. In some implementations, the coil is cryogenically cooled to reduce resistance and improve efficiency.Electromagnet

[0145] As discussed herein, and in accordance with various embodiments, the various systems, and various combinations of features that make up the various system embodiments, can also include an electromagnet.

[0146] FIG. 15 is a schematic front view of a magnetic resonance imaging system 1500, according to various embodiments. In accordance with various embodiments, the system 1500 can be any magnetic resonance imaging system, including for example, a single-sided magnetic resonance imaging system that comprises a magnetic resonance imaging scanner or a magnetic resonance imaging spectrometer, as disclosed herein.

[0147] As shown in FIG. 15, the system 1500 includes a housing 1520 that can house various components, including, for example but not limited to, magnets, electromagnets, coils for producing radio frequency fields, various electronic components, for example but not limited to, for controlling, powering, and / or monitoring of the system 1500. In accordance with various embodiments, the housing 1520 can house, for example, the permanent magnet 1230, the radio frequency transmit coil 1240, and / or the gradient coil set 1250 within the housing 1520. In accordance with various embodiments, the system 1500 also includes a bore 1535 in its center. As shown in FIG. 15, the housing 1520 also includes a front surface 1525 of the system 1500. In accordance with various embodiments, the front surface 1525 can be curved, flat, concave, convex, or otherwise have a straight or curvilinear surface. In accordance with various embodiments, the magnetic resonance imaging system 1500 can be configured to provide a region of interest in field of view 1530.

[0148] As shown in FIG. 15, the system 1500 includes an electromagnet 1560 disposed proximate to the front surface 1525 of the system 1500. In accordance with various embodiments, the electromagnet 1560 is disposed proximate to the center of the front surface 1525 on the front side of the system 1500. In accordance with various embodiments, the electromagnet 1560 can be a solenoid coil configured to create a field that either adds or subtracts from the magnetic field, for example, of the permanent magnet 1230. In accordanceAtty Dkt No.: 49880-722601 with various embodiments, this field can create a prepolarizing field for enhancing the signal or contrast from the nuclear magnetic resonance.

[0149] As shown in FIG. 15, the given field of view 1530 resides at the center of the front surface 1525 of the system 1500. In accordance with various embodiments, the electromagnet 1560 is disposed within the given field of view 1530. In accordance with various embodiments, the electromagnet 1560 is disposed concentrically with the given field of view 1530. In accordance with various embodiments, the electromagnet 1560 can be inserted in the bore 1535. In accordance with various embodiments, the electromagnet 1560 can be placed proximate to the bore 1535. For example, the electromagnet 1560 can be placed in front, back or middle of the bore 1535. In accordance with various embodiments, the electromagnet 1560 can be placed proximate to, or at the entrance of the bore 1535.Radio Frequency Receive Coil

[0150] As discussed herein, and in accordance with various embodiments, the various systems, and various combinations of features that make up the various system embodiments, can also include a radio frequency receive coil.

[0151] Some MR systems can create a uniform field within the imaging region. This uniform field can then generate a narrow band of magnetic resonance frequencies that can then be captured by a receive coil, amplified, and digitized by a spectrometer. Since frequencies are within a narrow well-defined bandwidth, hardware architecture can be focused on creating a statically tuned RF-RX coil with an optimal coil quality factor. Many variations in coil architectures have been created that explore large single volume coils, coil arrays, parallelized coil arrays, or body specific coil arrays. However, these structures may be limited to imaging a specific frequency close to the region of interest at high field strengths and with a limited sized region of interest within a magnetic bore.

[0152] In accordance with various embodiments, an MRI system is provided that can include an imaging region that can be offset from a face of a magnet. The MRI system can provide relatively unobstructed imaging. The MRI system can have a built-in magnetic field gradient that creates a range of field values over the region of interest. The MRI system can operate at a lower magnetic field strength as compared to other MRI systems allowing for a relaxation on the RX coil design constraints and allowing for additional mechanisms like robotics to be used with the MRI.

[0153] The architecture of the main magnetic field of the MRI system, in accordance with various embodiments, can create a different set of optimization constraints. Because the imagingAtty Dkt No.: 49880-722601 volume can extend over a broader range of magnetic resonance frequencies, the hardware can be configured to be sensitive to and capture the specific frequencies that are generated across the field of view. This frequency spread can be much larger than a single receive coil tuned to a single frequency and can provide increased sensitivity. In addition, because the field strength can be much lower than other MRI systems, and because signal intensity can be proportional to the field strength, it can allow for a maximization of a signal to noise ratio of the receive coil network. Methods are therefore provided, in accordance with various embodiments, to acquire the full range of frequencies that are generated within the field of view without loss of sensitivity.

[0154] In accordance with various embodiments, several methods are provided that can allow for imaging within the MRI system. These methods can include combining: (i) a variable tuned RF- RX coil; (ii) a RF-RX coil array with elements tuned to frequencies that are dependent upon the spatial inhomogeneity of the magnetic field; (iii) an ultralow-noise pre-amplifier design; and (iv) an RF-RX array with multiple receive coils designed to optimize the signal from a defined and limited field of view for a specific body part. These methods can be combined in any combination as needed.

[0155] In accordance with various embodiments, a variable tuned RF-RX coil can comprise one or more electronic components for tuning the electromagnetic receive field. In accordance with various embodiments, the one or more electronic components can include at least one of a varactor, a PIN diode, a capacitor, an inductor, a MEMS switch, a solid-state relay, or a mechanical relay. In accordance with various embodiments, the one or more electronic components used for tuning can include at least one of dielectrics, capacitors, inductors, conductive metals, metamaterials, or magnetic metals. In accordance with various embodiments, tuning the electromagnetic receive field includes changing the current or by changing physical locations of the one or more electronic components. In accordance with various embodiments, the coil is cryogenically cooled to reduce resistance and improve efficiency.

[0156] In accordance with various embodiments, the RF-RX array can be comprised of individual coil elements that are each tuned to a variety of frequencies. The appropriate frequency can be chosen, for example, to match the frequency of the magnetic field located at the specific spatial location where the specific coil is located. Because the magnetic field can vary as a function of space, as shown in FIG. 16A, the field and frequency of the coil can be adjusted to approximately match the spatial location. Here the coils can be designed to image the field locations Bl, B2, and B3, which are physically separated along a single axis.Atty Dkt No.: 49880-722601

[0157] For this low field system, in accordance with various embodiments, a low-noise preamplifier can be designed and configured to leverage the low signal environment of the MRI system. This low noise amplifier can be configured to utilize components that do not generate significant electronic and voltage noise at the desired frequencies (for example, < 3 MHz and >2 MHz). Typical junction field effect transistor designs (J-FET) may not have the appropriate noise characteristics at this frequency and can create high frequency instabilities at the GHz range that can bleed into, although several decades of dB lower, into the measured frequency range. Since the gain of the system can preferably be, for example, > 80 dB overall, any small instabilities or intrinsic electrical noise can be amplified and degrade signal integrity.

[0158] Referring to FIG. 16B, RF-RX coils can be designed to image specific limited field of views based upon the target anatomy. The vagina, for example, extends to about 100 millimeters deep within the human body (see FIG. 16D). Thus, a RX coil for POP imaging can be able to image at least about 100 mm deep inside human body. According to the Biot Savart law, the magnetic field of a loop coil can be calculated by the following equation,where pO = 4'7i * 10-7H / m is the vacuum permeability, R is the radius of the loop coil, z is distance along the center line of the coil from its center, and I is the current on the coil (see FIG. 16B). Assuming 1 = 1 Ampere, with the goal of locating a figure of magnetic field (Bz) at z = 100 mm, the maximum position is when R is 140 mm, as shown in FIG. 16C. In some cases, the RF RX coil network is configured for imaging external to the surface by a distance ranging from about 80 mm to about 120 mm to account for anatomical differences across patients.

[0159] Based upon the geometrical constraints of the body, the loop coil can be set up at the space between the human legs upon the torso. These anatomical constraints provide a difficulty for fitting a 280-mm diameter coil at this location. According to FIG. 16C, the Bz field value is proportional to the radius of the loop when R is less than 140mm. As such, it is advantageous that the coil approach a diameter as large as can be accommodated. For example, the largest loop coil that can be placed between a person’s legs can be about 10 cm large.

[0160] As the size of the coil is limited by the space between legs, the magnetic field of a 10-cm diameter coil may not be capable of reaching the depth of the vagina. Therefore, a single coil may not be enough for POP imaging. Thus, multiple coils can prove beneficial in receiving signal from different directions. In various embodiments of the MRI system, the magnetic field is provided in the z-direction and RF coils are sensitive to x- and y-direction. In this example case, a loop coil in x-y plane may not collect RF signal from a human since it is sensitive to z-Atty Dkt No.: 49880-722601 direction, while a butterfly coil may be useful. Based on the location and orientation of an RF coil, the RF coil can be a loop coil or a butterfly coil. In addition, an RF coil can be placed under the body of a subject without limiting the size of the RF coil.

[0161] In some embodiments, the MRI system comprises a plurality of RX coils. In some embodiments, one or more RX coils of the plurality of RX coils can be decoupled. Decoupling the one or more RX couples can comprise: geometry decoupling, capacitive or inductive decoupling, or low or high impedance pre-amplifier coupling.

[0162] The MRI system, in accordance with various embodiments, can have a variant magnetic field from the magnet, and its strength can vary linearly along the z direction. The RX coils can be located in different positions in z-direction, and each coil can be tuned to different frequencies, which can depend on the location of the coils in the system.

[0163] In some embodiments, the RX coils can be constructed from conductive traces that can be pre-tuned to a desired frequency and printed, for example, on a disposable substrate. In some embodiments, a clinician can place the RX coil (or a plurality of RX coils configured in an array) upon the body at the region of interest for a given procedure and dispose of the coil afterwards. For example, and in accordance with various embodiments, the RX coils can be surface coils, which can be affixed to, e.g., worn or taped to, a patient's body. For other body parts, e.g., an ankle or a wrist, the surface coil might be a single-loop configuration, figure-8 configuration, or butterfly coil configuration wrapped around the region of interest. For regions that require significant penetration depth, e.g., the torso or knee, the coil might consist of a Helmholtz coil pair. The main restriction to the receive coil is similar to other MRI systems: the coil can be sensitive to a plane that is orthogonal to the main magnetic field, BO, axis. FIG. 22 is a schematic view of figure-8 coils 2202 disposed within the housing of an MRI system proximate to the surface 2204. In some embodiments, the figure-8 coils 2202 cover the entirety of an underside of the surface 2204. In some embodiments, the coils can be disposed on an underside of a commode. In some embodiments, the MRI system described herein can comprise the commode.

[0164] In accordance with various embodiments, the coils might be inductively coupled to another loop that is electrically connected to the receive preamplifier. This design can allow for easier and unobstructed access of the receive coils.

[0165] In accordance with various embodiments, the size of coils can be limited by the structure of the human body. For example, the coils' size can be positioned and configured to fit in the space between human legs when imaging the vagina.Atty Dkt No.: 49880-722601

[0166] In accordance with various embodiments, the number of turns and loops of the RX coil can be adapted to cover the entire space between the legs so that the entire imaging volume can be covered. Because POP imaging requires functionality testing and does not require interventional access, the entire surface of the RX network can surround the biology. See Figure ##.Programmable Logic Controller

[0167] As discussed herein, and in accordance with various embodiments, the various systems, and various combinations of features that make up the various system embodiments, can also include a programmable logic controller (PLC). PLCs are industrial digital computers which can be designed to operate reliably in harsh usage environments and conditions. PLCs can be designed to handle these types of conditions and environments, not just in the external housing, but in the internal components and cooling arrangements as well. As such, PLCs can be adapted for the control of manufacturing processes, such as assembly lines, or robotic devices, or any activity that requires high reliability control and ease of programming and process fault diagnosis.

[0168] In accordance with various embodiments, the system can contain a PLC that can control the system in pseudo real-time. This controller can manage the power cycling and enabling of the gradient amplifier system, the radio frequency transmission system, the frequency tuning system, and sends a keep alive signal (e.g., a message sent by one device to another to check that the link between the two is operating, or to prevent the link from being broken) to the system watchdog. The system watchdog can continually look for a strobe signal supplied by the computer system. If the computer threads stall, a strobe is missed that can trigger the watchdog to enter a fault condition. If the watchdog enters a fault condition, the watchdog can be operated to depower the system.

[0169] The PLC can handle low level logic functions on incoming and outgoing signals into system. This system can monitor the subsystem health and control when subsystems needed to be powered or enabled. The PLC can be designed in different ways. One design example includes a PLC with one main motherboard with four expansion boards. Due to the speed of the microcontroller on the PLC, subsystems can be managed in pseudo real-time, while real-time applications can be handled by the computer or spectrometer on the system.

[0170] The PLC can serve many functional responsibilities including, for example, powering on / off the gradient amplifiers (discussed in greater detail herein) and the RF amplifier (discussedAtty Dkt No.: 49880-722601 in greater detail herein), enabling / disabling the gradient amplifiers and the RF amplifier, setting the digital and analog voltages for the RF coil tuning, and strobing the system watchdog.Robot

[0171] As discussed herein, and in accordance with various embodiments, the various systems, and various combinations of features that make up the various system embodiments, can also include a robot.

[0172] In some medical procedures, such as a prostate biopsy, it is typical for the patient to endure a lengthy procedure in an uncomfortable prone position, which often includes remaining motionless in one specific body position during the entire procedure. In such long procedures, if a metallic ferromagnetic needle is used for the biopsy with guidance from an MRI system, the needle may experience attraction force from the strong magnets of the MRI system, and thus may cause it to deviate from its path during the length of the procedure. Even in the case of using a non-magnetic needle, the local field distortions can cause distortions in the magnetic resonance images, and therefore, the image quality surrounding the needle may result in a poor quality. To avoid such distortions, pneumatic robots with complex compressed air mechanism have been designed to work in conjunction with conventional MRI systems. Even then, access to target anatomy remains challenging due to the form factor of currently available MRI systems.

[0173] The various embodiments presented herein include improved MRI systems that are configured to use for guiding in medical procedures, including, for example, robot-assisted, invasive medical procedures. The technologies, methods and apparatuses disclosed herein relate to a guided robotic system using magnetic resonance imaging as a guidance to automatically guide a robot (referred to herein as "a robotic system") in medical procedures. In accordance with various embodiments, the disclosed technologies combine a robotic system with magnetic resonance imaging as guidance. In accordance with various embodiments, the robotic system disclosed herein is combined with other suitable imaging techniques, for example, ultrasound, x- ray, laser, or any other suitable diagnostic or imaging methodologies.Spectrometer

[0174] As discussed herein, and in accordance with various embodiments, the various systems, and various combinations of features that make up the various system embodiments, can also include a spectrometer.

[0175] A spectrometer can operate to control all real-time signaling used to generate images. It creates the RF transmission (RF-TX) waveform, gradient waveforms, frequency tuning triggerAtty Dkt No.: 49880-722601 waveform, and blanking bit waveforms. These waveforms are then synchronized with the RF receiver (RF-RX) signals. This system can generate frequency swept RF-TX pulses and phase cycled RF-TX pulses. The swept RF-TX pulses allow for an inhomogeneous B1+ field (RF-TX field) to excite a sample volume more effectively and efficiently. It can also digitize multiple RF RX channels with the current configuration set to four receiver channels. However, this system architecture allows for an easy system scale-up to increase the number of transmit and receive channels to a maximum of 32 transmit channels and 16 receive channels without having to change the underlying hardware or software architecture.

[0176] The spectrometer can serve many functional responsibilities including, for example, generating and synchronizing the RF-TX (discussed in greater detail herein) waveforms, X gradient waveforms, Y-gradient waveforms, blanking bit waveforms, frequency tuning trigger waveform and RF-RX windows, and digitizing and signal processing the RF-RX data using, for example, quadrature demodulation followed by a finite impulse response filter decimation such as, for example, a cascade integrating comb (CIC) filter decimation.

[0177] The spectrometer can be designed in different ways. One design example includes a spectrometer with three main components: 1) a first software design radio (SDR 1) operating with Basic RF-TX daughter cards and Basic RF-RX daughter cards; 2) a second software design radio (SDR 2) operating with LFRF TX daughter cards and Basic RF-RX daughter cards; and 3) a clock distribution module (octoclock) that can synchronize the two devices.

[0178] SDRs are the real-time communication device between the transmitted signals and received MRI signals. They can communicate over 10-Gbit optical fiber to the computer using a Small Form-factor Pluggable Plus transceiver (SFP+) communication protocol. This communication speed can allow the waveforms to be generated with high fidelity and high reliability.

[0179] Each SDR can include a motherboard with an integrated field-programmable gate array (FPGA), digital to analog converters, analog to digital converters, and four module slots for integrating different daughtercards. Each of these daughtercards can function to change the frequency response of the associated TX or RX channel. In accordance with various embodiments, the system can utilize many variations daughtercards including, for example, a Basic RF version, and a low frequency (LP) RF version. The Basic RF daughtercards can be used for generating and measuring RF signals. The LP RF version can be used for generating gradient, trigger and blanking bit signals.

[0180] The octoclock can be used to synchronize a multi-channel SDR system to a common timing source while providing high-accuracy time and frequency reference distribution. It can doAtty Dkt No.: 49880-722601 so, for example, with 8-way time and frequency distribution (1 PPS and 10MHz). An example of an octoclock is the Ettus Octoclock CD A, which can distribute a common clock to up to eight SDRs to ensure phase coherency between the two or more SDR sources.RE Amplifier / Gradient Amplifier

[0181] As discussed herein, and in accordance with various embodiments, the various systems, and various combinations of features that make up the various system embodiments, can also include a radio frequency amplifier (RF amplifier) and a gradient amplifier.

[0182] A RF amplifier is a type of electronic amplifier that can converts a low-power radiofrequency signal into a higher power signal. In operation, the RF amplifier can accept signals at low amplitudes and provide, for example, up to 60 dB of gain with a flat frequency response. This amplifier can accept three phase AC input voltage and can have a 10% max duty cycle. The amplifier can be gated by a 5 V digital signal so that unwanted noise is not generated when the MRI is receiving signal.

[0183] In operation, a gradient amplifier can increase the energy of the signal before it reaches the gradient coils such that the field strength can be intense enough to produce the variations in the main magnetic field for localization of the later received signal. The gradient amplifier can have two active amplification channels that can be controlled independently. Each channel can send out current to either the X or Y channel respectively. The third axis of spatial encoding can be handled by a permanent gradient in the main magnetic field (BO). With varying combinations of pulse sequences, the signal can be localized in three dimensions and reconstructed to create an object.Display / GUI

[0184] As discussed herein, and in accordance with various embodiments, the various systems, and various combinations of features that make up the various system embodiments, can also include a display in the form of, for example, a graphical user interface (GUI). In accordance with various embodiments, the GUI can take any contemplated form necessary to convey the information necessary to run magnetic resonance imaging procedures.

[0185] Further, it can be appreciated that the display may be embodied in any of a number of other forms, such as, for example, a rack-mounted computer, mainframe, supercomputer, server, client, a desktop computer, a laptop computer, a tablet computer, hand-held computing device (e.g., PDA, cell phone, smart phone, palmtop, etc.), cluster grid, netbook, embedded systems, orAtty Dkt No.: 49880-722601 any other type of special or general purpose display device as may be desirable or appropriate for a given application or environment.

[0186] The GUI is a system of interactive visual components for computer software. A GUI can display objects that convey information and represent actions that can be taken by the user. The objects change color, size, or visibility when the user interacts with them. GUI objects include, for example, icons, cursors, and buttons. These graphical elements are sometimes enhanced with sounds, or visual effects like transparency and drop shadows.

[0187] A user can interact with a GUI using an input device, which can include, for example, alphanumeric and other keys, mouse, a trackball or cursor direction keys for communicating direction information and command selections to a processor and for controlling cursor movement on the display. An input device may also be the display configured with touchscreen input capabilities. This input device can have two degrees of freedom in two axes, a first axis (i.e., x) and a second axis (i.e., y), that allows the device to specify positions in a plane.However, it can be understood that input devices allowing for 3 -dimensional (x, y and z) cursor movement are also contemplated herein.

[0188] In accordance with various embodiments, the touchscreen, or touchscreen monitor, can serves as the primary human interface device that allows a user to interact with the MRI. The screen can have a projected capacitive touch sensitive display with an interactive virtual keyboard. The touchscreen can have several functions including, for example, displaying the graphical user interface (GUI) to the user, relaying user input to the system's computer, and starting or stopping a scan.

[0189] In accordance with various embodiments, GUI views can be screens displayed (Qt widgets) to the user with appropriate buttons, edit fields, labels, images, etc. These screens can be constructed using a designer tool such as, for example, the Qt designer tool, to control placement of widgets, their alignment, fonts, colors, etc. A user interface (UI) sub controller can possess modules configured to control the behavior (display and responses) of the respective view modules.

[0190] Several application utilities (App Util) modules can perform specific functions. For example, S3 modules can handle data communication between the system and, for example, Amazon Web Services (AWS). Event Filters can be present to ensure valid characters are displayed on screen when user inputs are required. Dialog messages can be used to show various status, progress messages or require user prompts. Moreover, a system controller module can be utilized to handle coordination between the sub controller modules, and key data processingAtty Dkt No.: 49880-722601 blocks in the system, the pulse sequence generator, pulse interpreter, spectrometer and reconstruction.Processing Module

[0191] As discussed herein, and in accordance with various embodiments, the various workflows or methods, and various combinations of steps that make up the various workflow or method embodiments, can also include a processing module.

[0192] In accordance with various embodiments, a processing module serves many functions. For example, a processing module can operate to receive signal data acquired during the scan, process the data, and reconstruct those signals to produce an image that can be viewed (for example, via a touchscreen monitor that displays a GUI to the user), analyzed and annotated by system users. To create an image, an NMR signal can be localized in three-dimensional space. Magnetic gradient coils localize the signal and are operated before or during the RF acquisition. By prescribing a RF and gradient coil application sequence, called a pulse sequence, the signals acquired correspond to a specific magnetic field and RF field arrangement. Using mathematical operators and image reconstruction techniques, arrays of these acquired signals can be reconstructed into an image. These images can be generated from simple linear combinations of magnetic field gradients. In accordance with various embodiments, the system can operate to reconstruct the acquired signals from a-priori knowledge of, for example, the gradient fields, RF fields, and pulse sequences.

[0193] In accordance with various embodiments, the processing module can also operate to compensate for patient motion during a scan procedure. Motion (e.g., beating heart, breathing lungs, bulk patient movement) is one of the most common sources of artifacts in MRI, with such artifacts affecting image quality by leading to misinterpretations in the images and a subsequent loss in diagnostic quality. Therefore, motion compensation protocols can help address these issues at minimal cost in time, spatial resolution, temporal resolution, and signal-to-noise ratio.

[0194] In accordance with various embodiments, the processing module might include artificial intelligence machine learning modules designed to denoise the signal and improve the image signal-to-noise ratio.

[0195] In accordance with various embodiments, the processing module can also operate to assist clinicians in planning a path for subsequent patient intervention procedures, such as biopsy. In accordance with various embodiments, a robot can be provided as part of the system to perform the intervention procedure. The processing module can communicate instructions toAtty Dkt No.: 49880-722601 the robot, based on image analysis, to properly access, for example, the appropriate region of the body requiring a biopsy.

[0196] FIG. 17 is a flowchart for a method SI 00 of performing magnetic resonance imaging, according to various embodiments. In accordance with various embodiments, the method S1O0 includes inputting patient parameters into a magnetic resonance imaging system at step SI 10. In accordance with various embodiments, the system includes a housing having a front surface, a permanent magnet for providing a static magnetic field, a radio frequency transmit coil, and a single-sided gradient coil set. In accordance with various embodiments, the radio frequency transmit coil and the single-sided gradient coil set are positioned proximate to the front surface. In accordance with various embodiments, the system includes an electromagnet, a radio frequency receive coil, and a power source. In accordance with various embodiments, the power source is configured to flow current through at least one of the radio frequency transmit coil, the single-sided gradient coil set, or the electromagnet to generate an electromagnetic field in a region of interest. In accordance with various embodiments, the region of interest resides outside the front surface.

[0197] As shown in FIG. 17, the method S100 also includes executing a patient positioning protocol comprising running at least one first scan at step S120, running at least one second scan at step S130, reviewing the at least one second scan at step S140, and determining at least one path for conducting a biopsy based on review of the at least one second scan at step S150.

[0198] In accordance with various embodiments, the radio frequency transmit coil and the single-sided gradient coil set are located on the front surface. In accordance with various embodiments, the front surface is a concave surface. In accordance with various embodiments, the permanent magnet has an aperture through center of the permanent magnet. In accordance with various embodiments, the static magnetic field of the permanent magnet ranges from 1 mT to 1 T. In accordance with various embodiments, the static magnetic field of the permanent magnet ranges from 10 mT to 195 mT.

[0199] In accordance with various embodiments, the radio frequency transmit coil includes a first ring and a second ring that are connected via one or more capacitors and / or one or more rungs. In accordance with various embodiments, the radio frequency transmit coil is non-planar and oriented to partially surround the region of interest. In accordance with various embodiments, the single-sided gradient coil set is non-planar and oriented to partially surround the region of interest. In accordance with various embodiments, the single-sided gradient coil set is configured to project a magnetic field gradient to the region of interest. In accordance with various embodiments, the single-sided gradient coil set includes one or more first spiral coils at aAtty Dkt No.: 49880-722601 first position and one or more second spiral coils at a second position, the first position and the second position being located opposite each other about a center region of the single-sided gradient coil set. In accordance with various embodiments, the single-sided gradient coil set has a rise time less than 10 ps.

[0200] In accordance with various embodiments, the electromagnet is configured to alter the static magnetic field of the permanent magnet within the region of interest. In accordance with various embodiments, the electromagnet has a magnetic field strength from 10 mT to 1 T. In accordance with various embodiments, the radio frequency receive coil is a flexible coil configured to be affixed to an anatomical portion of a patient for imaging within the region of interest. In accordance with various embodiments, the radio frequency receive coil is in one of a single-loop coil configuration, figure-8 coil configuration, or butterfly coil configuration, wherein the coil is smaller than the region of interest. In accordance with various embodiments, the radio frequency transmit coil and the single-sided gradient coil set are concentric about the region of interest. In accordance with various embodiments, the magnetic resonance imaging system is a single-sided magnetic resonance imaging system that comprises a bore having an opening positioned about a center region of the front surface.

[0201] FIG. 18 is a flowchart for a method S200 of performing magnetic resonance imaging, according to various embodiments. In accordance with various embodiments, the method S200 includes inputting patient parameters into a magnetic resonance imaging system at step S210. In accordance with various embodiments, the system includes a housing having a concave front surface, a permanent magnet for providing a static magnetic field, a radio frequency transmit coil, and at least one gradient coil set. In accordance with various embodiments, the radio frequency transmit coil and the at least one gradient coil set are positioned proximate to the concave front surface. In accordance with various embodiments, the radio frequency transmit coil and the at least one gradient coil set are configured to generate an electromagnetic field in a region of interest. In accordance with various embodiments, the region of interest resides outside the concave front surface. In accordance with various embodiments, the system includes a radio frequency receive coil for detecting signal in the region of interest.

[0202] As shown in FIG. 18, the method S200 includes executing a patient positioning protocol comprising running at least one first scan at step S220, running at least one second scan at step S230, reviewing the at least one second scan at step S240, and determining at least one path for conducting a biopsy based on review of the at least one second scan at step S250.Atty Dkt No.: 49880-722601

[0203] In accordance with various embodiments, the radio frequency transmit coil and the single-sided gradient coil set are located on the concave front surface. In accordance with various embodiments, the static magnetic field of the permanent magnet ranges from 1 mT to 1

[0204] T. In accordance with various embodiments, the static magnetic field of the permanent magnet ranges from 10 mT to 195 mT. In accordance with various embodiments, the radio frequency transmit coil comprises a first ring and a second ring that are connected via one or more capacitors and / or one or more rungs. In accordance with various embodiments, the radio frequency transmit coil is non-planar and oriented to partially surround the region of interest. In accordance with various embodiments, the at least one gradient coil set is non-planar, single sided, and oriented to partially surround the region of interest. In accordance with various embodiments, the at least one gradient coil set is configured to project magnetic field gradient in the region of interest.

[0205] In accordance with various embodiments, the at least one gradient coil set comprises one or more first spiral coils at a first position and one or more second spiral coils at a second position, the first position and the second position being located opposite each other about a center region of the at least one gradient coil set. In accordance with various embodiments, the at least one gradient coil set has a rise time less than 10 ps. In accordance with various embodiments, the permanent magnet has an aperture through center of the permanent magnet. In accordance with various embodiments, the system further includes an electromagnet configured to alter the static magnetic field of the permanent magnet within the region of interest. In accordance with various embodiments, the electromagnet has a magnetic field strength from 10 mT to 1 T. In accordance with various embodiments, the radio frequency receive coil is a flexible coil configured to be affixed to an anatomical portion of a patient for imaging within the region of interest. In accordance with various embodiments, the radio frequency receive coil is in one of a single-loop coil configuration, figure-8 coil configuration, or butterfly coil configuration, where the coil is smaller than the region of interest.

[0206] In accordance with various embodiments, the radio frequency transmit coil and the at least one gradient coil set are concentric about the region of interest. In accordance with various embodiments, the magnetic resonance imaging system is a single-sided magnetic resonance imaging system that comprises a magnetic resonance imaging scanner or a magnetic resonance imaging spectrometer.

[0207] FIG. 19 is a flowchart for a method S300 of performing a scan on a magnetic resonance imaging system, according to various embodiments. In accordance with various embodiments, the method S300 includes at step S310 providing a housing having a front surface, a permanentAtty Dkt No.: 49880-722601 magnet for providing a static magnetic field, a radio frequency transmit coil, and a single-sided gradient coil set. In accordance with various embodiments, the radio frequency transmit coil and the single-sided gradient coil set are positioned proximate to the front surface. In accordance with various embodiments, the method S300 includes providing an electromagnet at step S320. In accordance with various embodiments, the method S300 includes at step S330 activating at least one of the radio frequency transmit coil, the single-sided gradient coil set, or the electromagnet to generate an electromagnetic field in a region of interest. In accordance with various embodiments, the region of interest resides outside the front surface.

[0208] In accordance with various embodiments, the method S300 includes activating a radio frequency receive coil to obtain imaging data at step S340, reconstructing obtained imaging data to produce an output image for analysis at step S350 and displaying the output image for user review and annotation at step S360.

[0209] In accordance with various embodiments, the radio frequency transmit coil and the single-sided gradient coil set are located on the front surface. In accordance with various embodiments, the front surface is a concave surface. In accordance with various embodiments, the permanent magnet has an aperture through center of the permanent magnet. In accordance with various embodiments, the static magnetic field of the permanent magnet ranges from 1 mT to 1 T. In accordance with various embodiments, the static magnetic field of the permanent magnet ranges from 10 mT to 195 mT.

[0210] In accordance with various embodiments, the radio frequency transmit coil includes a first ring and a second ring that are connected via one or more capacitors and / or one or more rungs. In accordance with various embodiments, the radio frequency transmit coil is non-planar and oriented to partially surround the region of interest. In accordance with various embodiments, the single-sided gradient coil set is non-planar and oriented to partially surround the region of interest. In accordance with various embodiments, the single-sided gradient coil set is configured to project a magnetic field gradient to the region of interest. In accordance with various embodiments, the single-sided gradient coil set includes one or more first spiral coils at a first position and one or more second spiral coils at a second position, the first position and the second position being located opposite each other about a center region of the single-sided gradient coil set. In accordance with various embodiments, the single-sided gradient coil set has a rise time less than 10 ps.

[0211] In accordance with various embodiments, the electromagnet is configured to alter the static magnetic field of the permanent magnet within the region of interest. In accordance with various embodiments, the electromagnet has a magnetic field strength from 10 mT to 1 T. InAtty Dkt No.: 49880-722601 accordance with various embodiments, the radio frequency receive coil is a flexible coil configured to be affixed to an anatomical portion of a patient for imaging within the region of interest. In accordance with various embodiments, the radio frequency receive coil is in one of a single-loop coil configuration, figure-8 coil configuration, or butterfly coil configuration, wherein the coil is smaller than the region of interest. In accordance with various embodiments, the radio frequency transmit coil and the single-sided gradient coil set are concentric about the region of interest. In accordance with various embodiments, the magnetic resonance imaging system is a single-sided magnetic resonance imaging system that comprises a bore having an opening positioned about a center region of the front surface.

[0212] FIG. 20 is a flowchart for a method S400 of performing a scan on a magnetic resonance imaging system, according to various embodiments. In accordance with various embodiments, the method S400 includes at step S410 providing a housing having a concave front surface, a permanent magnet for providing a static magnetic field, a radio frequency transmit coil, and a single-sided gradient coil set. In accordance with various embodiments, the radio frequency transmit coil and the single-sided gradient coil set are positioned proximate to the front surface.

[0213] In accordance with various embodiments, the method S400 includes at step S420 activating at least one of the radio frequency transmit coil and the at least one gradient coil set to generate an electromagnetic field in a region of interest. In accordance with various embodiments, the region of interest resides outside the concave front surface.

[0214] In accordance with various embodiments, the method S400 includes activating a radio frequency receive coil to obtain imaging data at step S430, reconstructing obtained imaging data to produce an output image for analysis at step S440 and displaying the output image for user review and annotation at step S450.

[0215] In accordance with various embodiments, the radio frequency transmit coil and the single-sided gradient coil set are located on the concave front surface. In accordance with various embodiments, the static magnetic field of the permanent magnet ranges from 1 mT to IT. In accordance with various embodiments, the static magnetic field of the permanent magnet ranges from 10 mT to 195 mT. In accordance with various embodiments, the radio frequency transmit coil comprises a first ring and a second ring that are connected via one or more capacitors and / or one or more rungs. In accordance with various embodiments, the radio frequency transmit coil is non-planar and oriented to partially surround the region of interest. In accordance with various embodiments, the at least one gradient coil set is non-planar, single sided, and oriented to partially surround the region of interest. In accordance with various embodiments, the at least one gradient coil set is configured to project magnetic field gradient in the region of interest.Atty Dkt No.: 49880-722601

[0216] In accordance with various embodiments, the at least one gradient coil set comprises one or more first spiral coils at a first position and one or more second spiral coils at a second position, the first position and the second position being located opposite each other about a center region of the at least one gradient coil set. In accordance with various embodiments, the at least one gradient coil set has a rise time less than 10 ps. In accordance with various embodiments, the permanent magnet has an aperture through center of the permanent magnet. In accordance with various embodiments, the system further includes an electromagnet configured to alter the static magnetic field of the permanent magnet within the region of interest. In accordance with various embodiments, the electromagnet has a magnetic field strength from 10 mT to 1 T. In accordance with various embodiments, the radio frequency receive coil is a flexible coil configured to be affixed to an anatomical portion of a patient for imaging within the region of interest. In accordance with various embodiments, the radio frequency receive coil is in one of a single-loop coil configuration, figure-8 coil configuration, or butterfly coil configuration, where the coil is smaller than the region of interest.

[0217] In accordance with various embodiments, the radio frequency transmit coil and the at least one gradient coil set are concentric about the region of interest. In accordance with various embodiments, the magnetic resonance imaging system is a single-sided magnetic resonance imaging system that comprises a magnetic resonance imaging scanner or a magnetic resonance imaging spectrometer.Pre-Polarizer

[0218] As discussed herein, and in accordance with various embodiments, the various workflows or methods, and various combinations of steps that make up the various workflow or method embodiments, can also include a pre-polarization step.

[0219] In some embodiments, the prepolarizer can be charged by a system power supply. The powering of this polarizer can temporarily change the magnetic field within the field of view either by increasing or decreasing the main magnetic field strength. This change in the magnetic field then creates a change in the total number of nuclear spins that are aligned within the field of view and it changes the time constants by which the nuclear spins relax. An increase in the field allows for more nuclear spins to be aligned with the field, thus temporarily increasing the signal from a given voxel. A decrease in the field changes the relaxation properties of the objects and can allow for increased contrast within the field of view.

[0220] In accordance with various embodiments, the prepolarizer might be first charged to increase the field strength and therefore the signal strength. Then after waiting an appropriateAtty Dkt No.: 49880-722601 amount of time for the nuclear spins to align (as dictated by the T1 time of the desired spins), the prepolarizer can be removed. As this prepolarizer is depowered, the spins that are aligned will begin to relax and lose energy but can still be imaged by the magnetic resonance system at an increased signal level than when the system did not apply a prepolarizing pulse.Patient Intake

[0221] As discussed herein, and in accordance with various embodiments, the various workflows or methods, and various combinations of steps that make up the various workflow or method embodiments, can also include a patient intake step.

[0222] As part of this step, and any relevant information can be part of the patient intake step, including the intake of all data relevant to the performance of the magnetic resonance system, in accordance with various embodiments herein.

[0223] In accordance with various embodiments, the patient intake step can include, not only data inputted by user, but also data downloaded from any memory source, whether it be, for example, data from a remote data storage component (e.g., the cloud), an on-board data storage component, or portable data storage component (e.g., external flash / solid state drives and external hard drives).

[0224] In accordance with various embodiments, and further related to memory sources, an onboard data storage component (e.g., on-board a computing system within an MRI system) can be a random access memory (RAM) or other dynamic memory, or a read only memory (ROM) or other static storage device.

[0225] In accordance with various embodiments, and further related to memory sources, a remote or portable data storage component can include, for example, a magnetic disk, optical disk, solid state drive (SSD), and a media drive and a removable storage interface. A media drive may include a drive or other mechanism to support fixed or removable storage media, such as a hard disk drive, a floppy disk drive, a magnetic tape drive, an optical disk drive, a CD or DVD drive (R or RW), flash drive, or other removable or fixed media drive. As these examples illustrate, the storage media may include a computer-readable storage medium having stored therein particular computer software, instructions, or data.

[0226] In accordance with various embodiments, a storage device may include other similar instrumentalities for allowing computer programs or other instructions or data to be loaded into computing system. Such instrumentalities may include, for example, a removable storage unit and an interface, such as a program cartridge and cartridge interface, a removable memory (for example, a flash memory or other removable memory module) and memory slot, and otherAtty Dkt No.: 49880-722601 removable storage units and interfaces that allow software and data to be transferred from the storage device to computing system.

[0227] In accordance with various embodiments, the data types that can be user inputted, uploaded, downloaded, etc., can include, for example, patient name, patient sex, patient weight, patient height, patient contact information, patient birthdate, patient's referring physician, and patient race. In addition, a clinical baseline can be user inputted that includes information such as the patient's Gleason score for any past biopsies, the frequency of sexual intercourse, the last time the patient had food, and the patient's PSA level.Patient Positioning

[0228] As discussed herein, and in accordance with various embodiments, the various workflows or methods, and various combinations of steps that make up the various workflow or methods, can also include a patient positioning step. The patient positions described below comprise exemplary patient positions and may or may not be used when screening for POP specifically. In some cases, a patient may have multiple scans scheduled, such that the patient may be positioned in one manner for one scan (e.g., such as shown in FIGS. 21A-21X) and in another way (e.g., supine or seated) for a POP scan.

[0229] As a precursor to the positioning, a patient can undergo a patient preparation and screening process, whereby the patient is screened for foreign bodies and devices such as pacemakers that may represent a contraindication to imaging. The patient's important health conditions, including allergies, as well as patient data received as part of the patient intake process, can also be reviewed.

[0230] For positioning in a full-body MRI, a patient can be placed on a table, such as in a supine position. Receiver imaging coils can be arranged around the body part of interest (e.g., pelvis, head, chest, knee, etc.) If EKG or respiratory gating is required, then these devices are attached at this time. A key anatomic structure such as the bridge of the nose or umbilicus is identified as a landmark using laser guidance, and this is correlated with table position by pressing a button on the gantry.

[0231] In accordance with various embodiments, using the example system illustrated in FIGS. 21A-21X as a basis herein, a patient is positioned in any number of different positions depending on the type of anatomical scan.

[0232] As illustrated in FIG. 21A, when the abdomen is the region scanned, the patient can be laid on a surface at a lateral position. As illustrated, for the abdominal scan, a patient can be positioned to lay sideways facing the bore, with the arm closest to the table stretched out and theAtty Dkt No.: 49880-722601 other at the side of the body. The abdomen region can be positioned such that it is directly in front of the bore.

[0233] As illustrated in FIG. 21B, when an appendage (e.g., arm or hand) is the region scanned, the patient can be laid on a surface at a supine position. As illustrated, for the appendage scan, a patient can be positioned to be laid down with the arm or hand to be scanned situated directly in front of the bore.

[0234] As illustrated in FIG. 21C, when an appendage (e.g., arm or hand) is the region scanned, the patient can also be placed at a seated position. As illustrated, for the appendage scan, a patient can be positioned to be seated with arm to be scanned raised up against the system such that it is situated directly in front of the bore.

[0235]

[0185] As illustrated in FIG. 21D, when an appendage (e.g., elbow) is the region scanned, the patient can also be placed at a seated position. As illustrated, for the appendage scan, a patient can be positioned to be seated with elbow to be scanned raised up against the system such that it is situated directly in front of the bore and the other arm resting comfortably.

[0236]

[0186] As illustrated in FIG. 21E, when an appendage (e.g., knee) is the region scanned, the patient can also be situated to stand with the one leg lifted that is to be scanned. As illustrated, for the appendage scan, a patient can be positioned to be standing and facing the bore such that he leg of interest is lifted with the knee resting directly in front of the bore and the other leg placed firmly on the ground for stability.

[0237] As illustrated in FIG. 21F, when an appendage (e.g., knee) is the region scanned, the patient can also be situated in a lateral position. As illustrated, for the appendage scan, a patient can be positioned to lay sideways facing the bore, with the leg of interest bent and the other leg resting on the table and extended out. The patient's knee can be placed such that it is directly in front of the bore.

[0238] As illustrated in FIG. 21G, when an appendage (e.g., foot) is the region scanned, the patient can also be situated in a lateral position. As illustrated, for the appendage scan, a patient can be positioned to lay sideways facing away from the bore, with the leg of interest bent and resting on the table and the other leg extended out. The patient's foot can be placed such that it is directly in front of the bore.

[0239] As illustrated in FIG. 21H, when an appendage (e.g., foot) is the region scanned, the patient can also be situated in a seated position. As illustrated, for the appendage scan, a patient can be positioned to be seated facing the bore, with the leg of interest extended out toward the bore and the other leg resting comfortably. The patient's foot can be placed such that it is directly in front of the bore.Atty Dkt No.: 49880-722601

[0240]

[0190] As illustrated in FIG. 211, when an appendage (e.g., wrist) is the region scanned, the patient can be situated in a seated position. As illustrated, for the appendage scan, a patient can be positioned to be seated parallel to the system, such that the wrist of interest is directly in front of the bore with and the other arm is resting comfortably to the side.

[0241] As illustrated in FIG. 21 J, when the breast is the region scanned, the patient can be laid on a surface in a lateral position. As illustrated, for the breast scan, a patient can be positioned to lay sideways facing the bore, with one arm extended out above the head and the other hand resting to the side of the body. The breast region can be positioned to be directly in front of the bore.

[0242] As illustrated in FIG. 21K, when the breast is the region scanned, the patient can also be placed at a seated position. As illustrated, for the breast scan, a patient can be positioned to be seated and facing the bore such that arms are extended out and resting on the top of the system. The breast region can be positioned to be directly in front of the bore.

[0243] As illustrated in FIG. 21L, when the breast is the region scanned, the patient can also be placed at a kneeling position. As illustrated, for the breast scan, a patient can be positioned to be kneeling and facing the bore such that arms are extended out and resting on the top of the system. The breast region can be positioned to be directly in front of the bore.

[0244] As illustrated in FIG. 21M, when the head is the region scanned, the patient can be laid on a surface at a lateral position. As illustrated, for the head scan, a patient can be positioned to lay sideways facing away from the bore, with the head placed directly in front of the bore.

[0245] As illustrated in FIG. 21N, when the head is the region scanned, the patient can also be laid on a surface at a supine position. As illustrated, for the head scan, a patient can be positioned to lay down face up, with the top of the head against the system, such that it is situated directly in front of the bore.

[0246] As illustrated in FIG. 210, when the heart is the region scanned, the patient can be placed at a seated or standing position. As illustrated, for the heart scan, a patient can be positioned to be seated facing the bore such that the heart region is situated directly in front of the bore.

[0247] As illustrated in FIG. 21P, when the kidney is the region scanned, the patient can be laid on a surface at a lateral position. As illustrated, for the kidney scan, a patient can be positioned to lay sideways facing the bore, with the arm closest to the table stretched out and the other at the side of the body. The kidney region can be positioned such that it is directly in front of the bore.

[0248] As illustrated in FIG. 21Q, when the liver is the region scanned, the patient can be laid on a surface at a lateral position. As illustrated, for the liver scan, a patient can be positioned toAtty Dkt No.: 49880-722601 lay sideways facing the bore, with the arm closest to the table stretched out or bent to rest the head, and the other at the side of the body. The liver region can be positioned such that it is directly in front of the bore.

[0249] As illustrated in FIG. 21R, when the lung is the region scanned, the patient can be placed at a seated position. As illustrated, for the lung scan, a patient can be positioned to be seated facing away from the bore such that the lung region is situated directly in front of the bore.

[0250] As illustrated in FIG. 21S, when the neck is the region scanned, the patient can be laid on a surface at a lateral position. As illustrated, for the neck scan, a patient can be positioned to lay sideways and face away from the bore. The neck region can be positioned to be directly in front of the bore.

[0251] As illustrated in FIG. 21T, when the pelvis is the region scanned, the patient can be laid on a surface at a lithotomy position. As illustrated, for the pelvic scan, a patient can be positioned to have their back resting on the table and legs raised up to be resting against the top of the system. The pelvic region can be positioned to be directly in front of the bore.

[0252] As illustrated in FIG. 21U, when the pelvis is the region scanned, the patient can also be laid on a surface at a lateral position. As illustrated, for the pelvic scan, a patient can be positioned to lay sideways and face away from the bore. The pelvic region of the body can be positioned to be directly in front of the bore.

[0253] As illustrated in FIG. 21V, when the pelvis is the region scanned, the patient can also be placed at a prone position. As illustrated, for the pelvic scan, a patient can be positioned to rest with the chest against a surface, facing away from the bore. The pelvic region can be positioned such that it is directly in front of the bore.

[0254] As illustrated in FIG. 21W, when the shoulder is the region scanned, the patient can be placed at a seated position. As illustrated, for the shoulder scan, a patient can be positioned to be seated next to the system with the shoulder to be scanned situated directly in front of the bore.

[0255] As illustrated in FIG. 21X, when the spine is the region scanned, the patient can be placed at a seated position. As illustrated, for the spine scan, a patient can be positioned to be seated with back facing away from the bore and spine situated directly in view of the bore.Biopsy Guidance

[0256] As discussed herein, and in accordance with various embodiments, the various workflows or methods, and various combinations of steps that make up the various workflow or method embodiments, can also include biopsy guidance using the disclosed MRI system.Atty Dkt No.: 49880-722601

[0257] In accordance with various embodiments, the procedure for biopsy guidance using the disclosed MRI system may include one from the list of medical procedures consisting of transperineal biopsy, transperineal LDR brachytherapy, transperineal HDR brachytherapy, transperineal laser ablation, transperineal cryoablation, transrectal HIFU, breast biopsies, deep brain stimulation (DBS), brain biopsy, liver biopsy, kidney biopsy, lung biopsy, coronary stent insertion, brain stent insertion, and intensity modulated radiation treatment guidance.Calibration

[0258] As discussed herein, and in accordance with various embodiments, the various workflows or methods, and various combinations of steps that make up the various workflow or method embodiments, can also include a calibration step.

[0259] Calibration can take many forms of processes. In some cases, calibration involves running a full scan, similar to the scan run on a patient, in order to ensure image quality. In accordance with various embodiments, after a predetermined period, a user can be prompted to initiate a calibration routine such as, for example, a RF calibration routine. As part of initiating a calibration, a calibration phantom is positioned to allow calibration to advance. A calibration phantom can take many forms. In some cases, a calibration phantom can be an object (such as an artificial object) of known size and composition that is imaged to test, adjust or monitor an MRI systems homogeneity, imaging performance and orientation aspects. A phantom can be a fluid filled container or bottle often filled with a plastic structure of various sizes and shapes.

[0260] RF Calibration routine, in particular, optimizes RF pulse parameters such as, for example, signal power, signal duration and signal bandwidth to ensure image quality. The calibration routine acquires signal data from a calibration phantom using a predetermined set of parameters and sequence. Calibration data can be processed to determine the parameter set that can be used during imaging scans.Computing Systems

[0261] FIG. 23 shows the computer system 2301 comprising a central processing unit (CPU, also “processor” and “computer processor” herein) 2305, which can be a single core or multi core processor, or a plurality of processors for parallel processing. The computer system 2301 also includes memory or memory location (e.g., random-access memory, read-only memory, flash memory), electronic storage unit 2315 (e.g., hard disk), communication interface 2320 (e.g., network adapter) for communicating with one or more other systems, and peripheral devices 2325, such as cache, other memory, data storage and / or electronic display adapters. TheAtty Dkt No.: 49880-722601 memory, storage unit 2315, interface 2320 and peripheral devices 2325 are in communication with the CPU 2305 through a communication bus (solid lines), such as a motherboard. The storage unit 2315 can be a data storage unit (or data repository) for storing data. The computer system 2301 can be operatively coupled to a computer network (“network”) 2330 with the aid of the communication interface 2320. The network 2330 can be the Internet, an internet and / or extranet, or an intranet and / or extranet that is in communication with the Internet. The network 2330 in some cases is a telecommunication and / or data network. The network 2330 can include one or more computer servers, which can enable distributed computing, such as cloud computing. The network 2330, in some cases with the aid of the computer system 2301, can implement a peer-to-peer network, which may enable devices coupled to the computer system 2301 to behave as a client or a server.

[0262] The CPU 2305 can execute a sequence of machine-readable instructions, which can be embodied in a program or software. The instructions may be stored in a memory location, such as the memory. The instructions can be directed to the CPU 2305, which can subsequently program or otherwise configure the CPU 2305 to implement methods of the present disclosure. Examples of operations performed by the CPU 2305 can include fetch, decode, execute, and writeback.

[0263] The CPU 2305 can be part of a circuit, such as an integrated circuit. One or more other components of the system 2301 can be included in the circuit. In some cases, the circuit is an application specific integrated circuit (ASIC).

[0264] The storage unit 2315 can store files, such as drivers, libraries and saved programs. The storage unit 2315 can store user data, e.g., user preferences and user programs. The computer system 2301 in some cases can include one or more additional data storage units that are external to the computer system 2301, such as located on a remote server that is in communication with the computer system 2301 through an intranet or the Internet.

[0265] The computer system 2301 can communicate with one or more remote computer systems through the network 2330. For instance, the computer system 2301 can communicate with a remote computer system of a user. Examples of remote computer systems include personal computers (e.g., portable PC), slate or tablet PC’s (e.g., Apple® iPad, Samsung® Galaxy Tab), telephones, Smart phones (e.g., Apple® iPhone, Android-enabled device, Blackberry®), or personal digital assistants. The user can access the computer system 2301 via the network 2330.

[0266] Methods as described herein can be implemented by way of machine (e.g., computer processor) executable code stored on an electronic storage location of the computer system 2301, such as, for example, on the memory 2310 or electronic storage unit 2315. The machineAtty Dkt No.: 49880-722601 executable or machine-readable code can be provided in the form of software. During use, the code can be executed by the processor 2305. In some cases, the code can be retrieved from the storage unit 2315 and stored on the memory 2310 for ready access by the processor 2305. In some situations, the electronic storage unit 2315 can be precluded, and machine-executable instructions are stored on memory 2310.

[0267] The code can be pre-compiled and configured for use with a machine having a processer adapted to execute the code or can be compiled during runtime. The code can be supplied in a programming language that can be selected to enable the code to execute in a pre-compiled or as-compiled fashion.

[0268] Aspects of the systems and methods provided herein, such as the computer system 2301, can be embodied in programming. Various aspects of the technology may be thought of as “products” or “articles of manufacture” typically in the form of machine (or processor) executable code and / or associated data that is carried on or embodied in a type of machine readable medium. Machine-executable code can be stored on an electronic storage unit, such as memory (e.g., read-only memory, random-access memory, flash memory) or a hard disk. “Storage” type media can include any or all of the tangible memory of the computers, processors or the like, or associated modules thereof, such as various semiconductor memories, tape drives, disk drives and the like, which may provide non-transitory storage at any time for the software programming. All or portions of the software may at times be communicated through the Internet or various other telecommunication networks. Such communications, for example, may enable loading of the software from one computer or processor into another, for example, from a management server or host computer into the computer platform of an application server. Thus, another type of media that may bear the software elements includes optical, electrical and electromagnetic waves, such as used across physical interfaces between local devices, through wired and optical landline networks and over various air-links. The physical elements that carry such waves, such as wired or wireless links, optical links or the like, also may be considered as media bearing the software. As used herein, unless restricted to non-transitory, tangible “storage” media, terms such as computer or machine “readable medium” refer to any medium that participates in providing instructions to a processor for execution.

[0269] Hence, a machine readable medium, such as computer-executable code, may take many forms, including but not limited to, a tangible storage medium, a carrier wave medium or physical transmission medium. Non-volatile storage media include, for example, optical or magnetic disks, such as any of the storage devices in any computer(s) or the like, such as may be used to implement the databases, etc. shown in the drawings. Volatile storage media includeAtty Dkt No.: 49880-722601 dynamic memory, such as main memory of such a computer platform. Tangible transmission media include coaxial cables; copper wire and fiber optics, including the wires that comprise a bus within a computer system. Carrier-wave transmission media may take the form of electric or electromagnetic signals, or acoustic or light waves such as those generated during radio frequency (RF) and infrared (IR) data communications. Common forms of computer-readable media therefore include for example: a floppy disk, a flexible disk, hard disk, magnetic tape, any other magnetic medium, a CD-ROM, DVD or DVD-ROM, any other optical medium, punch cards paper tape, any other physical storage medium with patterns of holes, a RAM, a ROM, a PROM and EPROM, a FLASH-EPROM, any other memory chip or cartridge, a carrier wave transporting data or instructions, cables or links transporting such a carrier wave, or any other medium from which a computer may read programming code and / or data. Many of these forms of computer readable media may be involved in carrying one or more sequences of one or more instructions to a processor for execution.

[0270] The computer system 2301 can include or be in communication with an electronic display 2335 that comprises a user interface (UI) 2340 for providing, for example, a UI on a display of the user device. Examples of UI’s include, without limitation, a graphical user interface (GUI) and web-based user interface. In some embodiments, the electronic display may comprise a touch screen.

[0271] Methods and systems of the present disclosure can be implemented by way of one or more algorithms. An algorithm can be implemented by way of software upon execution by the central processing unit 2305. The algorithm can, for example, analyze data obtained by the user identification device or the monitoring module (or the medication monitoring module).Examples of Machine Learning Methodologies

[0272] As used in this specification and the appended claims, the terms “artificial intelligence,” “artificial intelligence techniques,” “artificial intelligence operation,” and “artificial intelligence algorithm” generally refer to any system or computational procedure that may take one or more actions that simulate human intelligence processes for enhancing or maximizing a chance of achieving a goal. The term “artificial intelligence” may include “generative modeling,” “machine learning” (ML), or “reinforcement learning” (RL).

[0273] As used in this specification and the appended claims, the terms “machine learning,” “machine learning techniques,” “machine learning operation,” and “machine learning model” generally refer to any system or analytical or statistical procedure that may progressively improve computer performance of a task. In some cases, ML may generally involve identifyingAtty Dkt No.: 49880-722601 and recognizing patterns in existing data in order to facilitate making predictions for subsequent data. ML may include a ML model (which may include, for example, a ML algorithm).Machine learning, whether analytical or statistical in nature, may provide deductive or abductive inference based on real or simulated data. The ML model may be a trained model. ML techniques may comprise one or more supervised, semi-supervised, self-supervised, or unsupervised ML techniques. For example, an ML model may be a trained model that is trained through supervised learning (e.g., various parameters are determined as weights or scaling factors). ML may comprise one or more of regression analysis, regularization, classification, dimensionality reduction, ensemble learning, meta learning, association rule learning, cluster analysis, anomaly detection, deep learning, or ultra-deep learning. ML may comprise, but is not limited to: k-means, k-means clustering, k-nearest neighbors, learning vector quantization, linear regression, non-linear regression, least squares regression, partial least squares regression, logistic regression, stepwise regression, multivariate adaptive regression splines, ridge regression, principal component regression, least absolute shrinkage and selection operation (LASSO), least angle regression, canonical correlation analysis, factor analysis, independent component analysis, linear discriminant analysis, multidimensional scaling, non-negative matrix factorization, principal components analysis, principal coordinates analysis, projection pursuit, Sammon mapping, t-distributed stochastic neighbor embedding, AdaBoosting, boosting, gradient boosting, bootstrap aggregation, ensemble averaging, decision trees, conditional decision trees, boosted decision trees, gradient boosted decision trees, random forests, stacked generalization, Bayesian networks, Bayesian belief networks, naive Bayes, Gaussian naive Bayes, multinomial naive Bayes, hidden Markov models, hierarchical hidden Markov models, support vector machines, encoders, decoders, auto-encoders, stacked auto-encoders, perceptrons, multi-layer perceptrons, artificial neural networks, feedforward neural networks, convolutional neural networks, recurrent neural networks, long short-term memory, deep belief networks, deep Boltzmann machines, deep convolutional neural networks, deep recurrent neural networks, or generative adversarial networks.

[0274] Methods and / or systems of the disclosure can process, analyze, and / or classify MRI images to automatically screen, diagnose, or grade POP, as described elsewhere herein. In some cases, the processing, analyzing, and / or classifying MRI images and / or one or more features of the MRI images may be conducted by way of one or more machine learning algorithms and / or one or more predictive models with instructions provided with one or more processors as disclosed herein. For example, one or more machine learning algorithms and / or predictiveAtty Dkt No.: 49880-722601 models may process one or more, or two or more features of the MRI images, described elsewhere herein.

[0275] In some cases, the subject's and / or plurality of subjects’ phenotypes may be determined and / or predicted with one or more machine learning algorithms and / or one or more predictive models with a sensitivity of at least about 70%, at least about 75%, at least about 80%, at least about 85% or at least about 90%.

[0276] In some cases, the automatically screening, diagnosing, or grading POP may be determined and / or predicted with one or more machine learning algorithms and / or one or more predictive models with a sensitivity of up to about 70%, up to about 75%, up to about 80%, up to about 85% or up to about 90%.

[0277] In some cases, the automatically screening, diagnosing, or grading POP may be determined and / or predicted with one or more machine learning algorithms and / or one or more predictive models with a specificity of at least about 70%, at least about 75%, at least about 80%, at least about 85% or at least about 90%.

[0278] In some cases, the automatically screening, diagnosing, or grading POP may be determined and / or predicted with one or more machine learning algorithms and / or one or more predictive models with a specificity of up to about 70%, up to about 75%, up to about 80%, up to about 85% or up to about 90%.

[0279] In some cases, the automatically screening, diagnosing, or grading POP may be determined and / or predicted with one or more machine learning algorithms and / or one or more predictive models with a positive predictive value of at least about 70%, at least about 75%, at least about 80%, at least about 85% or at least about 90%.

[0280] In some cases, the automatically screening, diagnosing, or grading POP may be determined and / or predicted with one or more machine learning algorithms and / or one or more predictive models with a positive predictive value of up to about 70%, up to about 75%, up to about 80%, up to about 85% or up to about 90%.

[0281] In some cases, the automatically screening, diagnosing, or grading POP may be determined and / or predicted with one or more machine learning algorithms and / or one or more predictive models with a negative predictive value of at least about 70%, at least about 75%, at least about 80%, at least about 85% or at least about 90%.

[0282] In some cases, the automatically screening, diagnosing, or grading POP may be determined and / or predicted with one or more machine learning algorithms and / or one or more predictive models with a negative predictive value of up to about 70%, up to about 75%, up to about 80%, up to about 85% or up to about 90%.Atty Dkt No.: 49880-722601

[0283] In some cases, the automatically screening, diagnosing, or grading POP may be determined and / or predicted with one or more machine learning algorithms and / or one or more predictive models with an Area Under the Receiver Operating Characteristic Curve (AUROC) of at least about 0.65, at least about 0.70, at least about 0.75, at least about 0.80, at least about 0.82, at least about 0.84, at least about 0.86, at least about 0.88, or at least about 0.90.

[0284] In some cases, the automatically screening, diagnosing, or grading POP may be determined and / or predicted with one or more machine learning algorithms and / or one or more predictive models with an Area Under the Receiver Operating Characteristic (AUROC) of up to about 0.65, up to about 0.70, up to about 0.75 up to about 0.80, up to about 0.82, up to about 0.84, up to about 0.86 up to about 0.88, or up to about 0.90.

[0285] An algorithm and / or predictive model can be implemented by way of software upon execution by the central processing unit 2305. In some cases, the predictive model may comprise a machine learning predictive model. In some cases, the machine learning predictive model may comprise one or more statistical, machine learning, or artificial intelligence algorithms.Examples of utilized algorithms, machine learning algorithms, and / or predictive models may include a support vector machine (SVM), a naive Bayes classification, a random forest, a neural network (such as a deep neural network (DNN)), a recurrent neural network (RNN), a deep RNN, a long short-term memory (LSTM) recurrent neural network (RNN), decision tree algorithm, unsupervised clustering algorithm, a supervised clustering algorithm, unsupervised clustering algorithm, a regression algorithm, a gradient-boosting algorithm (e.g., a gradientboosting implementation of a machine learning algorithm and / or predictive model such as a gradient-boosted decision trees), a gated recurrent unit (GRU), supervised learning algorithm, unsupervised learning algorithm, statistical, deep-learning algorithm for classification and regression, or any combination thereof. In some cases, the recurrent neural network may comprise units which can be LSTM units or GRU. In some cases, the predictive model and / or the machine learning algorithm may comprise an ensemble of one or more predictive models and / or machine learning algorithms

[0286] The machine learning predictive model may likewise involve the estimation of ensemble models, comprised of multiple predictive models, and utilize techniques such as gradient boosting, for example in the construction of gradient-boosting decision trees. The machine learning predictive model may be trained using one or more training datasets corresponding to an MRI image. In some embodiments, the one or more training datasets may comprise MRI images and corresponding classification of the MRI images as being indicative of POP.Atty Dkt No.: 49880-722601

[0287] Training records may be constructed from sequences of observations. Such sequences may comprise a fixed length for ease of data processing. For example, sequences may be zero- padded or selected as independent subsets of a single subject’s records.

[0288] The one or more predictive models and / or one or more machine learning algorithms may process one or more input features to generate one or more output values comprising automatically screening, diagnosing, or grading POP. For example, such automatically screening, diagnosing, or grading POP may comprise a binary classification of a healthy / normal health state (e.g., absence of a disease or disorder) or an adverse health state (e.g., presence of a disease or disorder), a classification between a group of categorical labels (e.g., ‘no disease or disorder’, ‘apparent disease or disorder’, and ‘likely disease or disorder’), a likelihood (e.g., relative likelihood or probability) of developing a particular disease or disorder, a score indicative of a presence of disease or disorder, a score indicative of a level of systemic inflammation experienced by the patient, a ‘risk factor’ for the likelihood of mortality of the patient, a prediction of the time at which the patient is expected to have developed the disease or disorder, a confidence interval for any numeric predictions, or any combination thereof. Various predictive model and / or machine learning algorithms may be cascaded such that the output of one or more predictive models and / or one or more machine learning algorithms may be used as one or more input features to subsequent layers or subsections of the one or more predictive model and / or one or more machine learning algorithms.

[0289] In order to train the one or more predictive models and / or the one or more machine learning algorithms e.g., by determining weights and correlations of the predictive model and / or the machine learning algorithm) to generate real-time classifications or predictions, the model can be trained using datasets (e.g., training datasets), described elsewhere herein. Such datasets may be sufficiently large to generate statistically significant classifications or predictions. For example, datasets may comprise databases of de-identified data including one or more molecular signatures, other measurements from a hospital or other clinical setting, or any combination thereof.

[0290] Datasets, as described elsewhere herein, may be split into subsets (e.g., discrete or overlapping), such as a training dataset, a development dataset, and a test dataset. For example, a dataset may be split into a training dataset comprising 80% of the dataset, a development dataset comprising 10% of the dataset, and a test dataset comprising 10% of the dataset. The training dataset may comprise about 10%, about 20%, about 30%, about 40%, about 50%, about 60%, about 70%, about 80%, or about 90% of the dataset. The development dataset may comprise about 10%, about 20%, about 30%, about 40%, about 50%, about 60%, about 70%, about 80%,Atty Dkt No.: 49880-722601 or about 90% of the dataset. The test dataset may comprise about 10%, about 20%, about 30%, about 40%, about 50%, about 60%, about 70%, about 80%, or about 90% of the dataset. Training sets (e.g., training datasets) may be selected by random sampling of a set of data corresponding to one or more subject cohorts to ensure independence of sampling. In some cases, training sets (e.g., training datasets) may be selected by proportionate sampling of a set of data corresponding to one or more subject cohorts to ensure independence of sampling.

[0291] To improve the accuracy of predictive model and / or machine learning algorithm predictions and reduce overfitting of the predictive model and / or machine learning algorithm, the datasets may be augmented to increase the number of samples within the training set. For example, data augmentation may comprise rearranging the order of observations in a training record. To accommodate datasets having missing observations, methods to impute missing data may be used, such as forward-filling, back-filling, linear interpolation, and multi-task Gaussian processes. Datasets may be filtered to remove confounding factors. For example, within a database, a subset of subjects may be excluded.

[0292] Neural network techniques, such as dropout or regularization, may be used during training the one or more predictive models and / or one or more machine learning algorithms to prevent overfitting. The neural network may comprise a plurality of sub-networks, each of which is configured to generate a classification or prediction of a different type of output information (e.g., which may be combined to form an overall output of the neural network). The one or more predictive models and / or the one or more machine learning algorithms may alternatively utilize statistical or related algorithms including random forest, classification and regression trees, support vector machines, discriminant analyses, regression techniques, ensemble and gradient- boosted variations thereof, or any combination thereof.

[0293] When the one or more predictive models and / or the one or more machine learning algorithms generate a classification or a prediction of or grading POP, a notification (e.g., alert or alarm) may be generated and transmitted to a health care provider, such as a physician, nurse, health care personnel managing, or any combination thereof, treating a subject e.g., a subject within a hospital. Notifications may be transmitted via an automated phone call, a short message service (SMS), multimedia message service (MMS) message, an e-mail, an alert within a dashboard, or any combination thereof. The notification may comprise output information such as a prediction of or grading POP.

[0294] To validate the performance of the one or more predictive models and / or one more machine learning algorithms, different performance metrics may be generated. For example, an area under the receiver-operating curve (AUROC) may be used to determine the diagnosticAtty Dkt No.: 49880-722601 and / or classification capability of the one or more predictive models and / or one or more machine learning algorithms. For example, the one or more predictive models and / or one or more machine learning algorithms may use classification thresholds which are adjustable, such that specificity and sensitivity are tunable, and the receiver-operating characteristic curve (ROC) can be used to identify the different operating points corresponding to different values of specificity and sensitivity of the one or more predictive models and / or one or more machine learning algorithms.

[0295] In some cases, such as when datasets are not sufficiently large, cross-validation may be performed to assess the robustness of one or more predictive models and / or one or more machine learning algorithms across different training and testing datasets.

[0296] To calculate performance metrics such as sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), AUPRC, AUROC, any combination thereof, or similar, the following definitions may be used. A “false positive” may refer to an outcome in which a positive outcome or result has been incorrectly or prematurely generated. A “true positive” may refer to an outcome in which positive outcome or result has been correctly generated. A “false negative” may refer to an outcome in which a negative outcome or result has been generated. A “true negative” may refer to an outcome in which a negative outcome or result has been generated.

[0297] The one or more predictive models and / or one or more machine learning algorithms may be trained until certain pre-determined conditions for accuracy or performance are satisfied, such as having minimum desired values corresponding to classification and / or diagnostic accuracy measures. For example, the diagnostic accuracy measure may correspond to prediction of a likelihood of occurrence of POP. Examples of diagnostic accuracy measures may include sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, area under the precision-recall curve (AUPRC), and area under the curve (AUC) of a Receiver Operating Characteristic (ROC) curve (AUROC) corresponding to the diagnostic accuracy of detecting or predicting a phenotype.

[0298] For example, such a pre-determined condition may be that the sensitivity of predicting or grading POP comprises a value of, for example, at least about 50%, at least about 55%, at least about 60%, at least about 65%, at least about 70%, at least about 75%, at least about 80%, at least about 85%, at least about 90%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, or at least about 99%.

[0299] As another example, such a pre-determined condition may be that the specificity of predicting or grading POP comprises a value of, for example, at least about 50%, at least aboutAtty Dkt No.: 49880-72260155%, at least about 60%, at least about 65%, at least about 70%, at least about 75%, at least about 80%, at least about 85%, at least about 90%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, or at least about 99%.

[0300] As another example, such a pre-determined condition may be that the positive predictive value (PPV) of predicting or grading POP comprises a value of, for example, at least about 50%, at least about 55%, at least about 60%, at least about 65%, at least about 70%, at least about 75%, at least about 80%, at least about 85%, at least about 90%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, or at least about 99%.

[0301] As another example, such a pre-determined condition may be that the negative predictive value (NPV) of predicting or grading POP comprises a value of, for example, at least about 50%, at least about 55%, at least about 60%, at least about 65%, at least about 70%, at least about 75%, at least about 80%, at least about 85%, at least about 90%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, or at least about 99%.

[0302] As another example, such a pre-determined condition may be that the area under the curve (AUC) of a Receiver Operating Characteristic (ROC) curve (AUROC) of predicting or grading POP comprises a value of at least about 0.50, at least about 0.55, at least about 0.60, at least about 0.65, at least about 0.70, at least about 0.75, at least about 0.80, at least about 0.85, at least about 0.90, at least about 0.95, at least about 0.96, at least about 0.97, at least about 0.98, or at least about 0.99.

[0303] As another example, such a pre-determined condition may be that the area under the precision-recall curve (AUPRC) of predicting or grading POP comprises a value of at least about 0.10, at least about 0.15, at least about 0.20, at least about 0.25, at least about 0.30, at least about 0.35, at least about 0.40, at least about 0.45, at least about 0.50, at least about 0.55, at least about 0.60, at least about 0.65, at least about 0.70, at least about 0.75, at least about 0.80, at least about 0.85, at least about 0.90, at least about 0.95, at least about 0.96, at least about 0.97, at least about 0.98, or at least about 0.99.

[0304] In some embodiments, the trained model may be trained or configured to predict or grade POP with a sensitivity of at least about 50%, at least about 55%, at least about 60%, at least about 65%, at least about 70%, at least about 75%, at least about 80%, at least about 85%, at least about 90%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, or at least about 99%.

[0305] In some embodiments, the trained model may be trained or configured to predict or grade POP with a specificity of at least about 50%, at least about 55%, at least about 60%, at least about 65%, at least about 70%, at least about 75%, at least about 80%, at least about 85%,Atty Dkt No.: 49880-722601 at least about 90%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, or at least about 99%.

[0306] In some embodiments, the trained model may be trained or configured to predict or grade POP with a positive predictive value (PPV) of at least about 50%, at least about 55%, at least about 60%, at least about 65%, at least about 70%, at least about 75%, at least about 80%, at least about 85%, at least about 90%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, or at least about 99%.

[0307] In some embodiments, the trained model may be trained or configured to predict or grade POP with a negative predictive value (NPV) of at least about 50%, at least about 55%, at least about 60%, at least about 65%, at least about 70%, at least about 75%, at least about 80%, at least about 85%, at least about 90%, at least about 95%, at least about 96%, at least about 97%, at least about 98%, or at least about 99%.

[0308] In some embodiments, the trained model may be trained or configured to predict or grade POP with an area under the curve (AUC) of a Receiver Operating Characteristic (ROC) curve (AUROC) of at least about 0.50, at least about 0.55, at least about 0.60, at least about 0.65, at least about 0.70, at least about 0.75, at least about 0.80, at least about 0.85, at least about 0.90, at least about 0.95, at least about 0.96, at least about 0.97, at least about 0.98, or at least about 0.99.

[0309] In some embodiments, the trained model may be trained or configured to predict or grade POP with an area under the precision-recall curve (AUPRC) of at least about 0.10, at least about 0.15, at least about 0.20, at least about 0.25, at least about 0.30, at least about 0.35, at least about 0.40, at least about 0.45, at least about 0.50, at least about 0.55, at least about 0.60, at least about 0.65, at least about 0.70, at least about 0.75, at least about 0.80, at least about 0.85, at least about 0.90, at least about 0.95, at least about 0.96, at least about 0.97, at least about 0.98, or at least about 0.99.

[0310] The training data sets may be collected from training subjects (e.g., humans). Each training subject has a diagnostic status indicating that they have either been diagnosed and / or classified with POP or have not been diagnosed with POP. The training procedure, as described elsewhere herein may be performed for each training subject in a plurality of training subjects.

[0311] In some embodiments, the machine learning analysis is performed by a device executing one or more programs (e.g., one or more programs stored in the Non-Persistent Memory or in the Persistent Memory) including instructions to perform the data analysis. In some embodiments, the data analysis is performed by a system comprising at least one processorAtty Dkt No.: 49880-722601 e.g, the processing core) and memory (e.g., one or more programs stored in the Non-Persistent Memory or in the Persistent Memory) comprising instructions to perform the data analysis.

[0312] Training the ML model may include, in some cases, selecting one or more untrained data models to train using a training data set. The selected untrained data models may include any type of untrained ML models for supervised, semi-supervised, self-supervised, or unsupervised machine learning. The selected untrained data models may be specified based upon input (e.g., user input) specifying relevant parameters to use as predicted variables or other variables to use as potential explanatory variables. For example, the selected untrained data models may be specified to generate an output (e.g., a prediction) based upon the input. Conditions for training the ML model from the selected untrained data models may likewise be selected, such as limits on the ML model complexity or limits on the ML model refinement past a certain point. The ML model may be trained (e.g., via a computer system such as a server) using the training data set. In some cases, a first subset of the training data set may be selected to train the ML model. The selected untrained data models may then be trained on the first subset of training data set using appropriate ML techniques, based upon the type of ML model selected and any conditions specified for training the ML model. In some cases, due to the processing power requirements of training the ML model, the selected untrained data models may be trained using additional computing resources (e.g., cloud computing resources). Such training may continue, in some cases, until at least one aspect of the ML model is validated and meets selection criteria to be used as a predictive model.

[0313] In some cases, one or more aspects of the ML model may be validated using a second subset of the training data set (e.g., distinct from the first subset of the training data set) to determine accuracy and robustness of the ML model. Such validation may include applying the ML model to the second subset of the training data set to make predictions derived from the second subset of the training data. The ML model may then be evaluated to determine whether performance is sufficient based upon the derived predictions. The sufficiency criteria applied to the ML model may vary depending upon the size of the training data set available for training, the performance of previous iterations of trained models, or user-specified performance requirements. If the ML model does not achieve sufficient performance, additional training may be performed. Additional training may include refinement of the ML model or retraining on a different first subset of the training dataset, after which the new ML model may again be validated and assessed. When the ML model has achieved sufficient performance, in some cases, the ML may be stored for present or future use. The ML model may be stored as sets of parameter values or weights for analysis of further input (e.g., further relevant parameters to useAtty Dkt No.: 49880-722601 as further predicted variables, further explanatory variables, further user interaction data, etc.), which may also include analysis logic or indications of model validity in some instances. In some cases, a plurality of ML models may be stored for generating predictions under different sets of input data conditions. In some embodiments, the ML model may be stored in a database (e.g., associated with a server).Definitions

[0314] Unless defined otherwise, all terms of art, notations and other technical and scientific terms or terminology used herein are intended to have the same meaning as is commonly understood by one of ordinary skill in the art to which the claimed subject matter pertains. In some cases, terms with commonly understood meanings are defined herein for clarity and / or for ready reference, and the inclusion of such definitions herein should not necessarily be construed to represent a substantial difference over what is generally understood in the art.

[0315] Throughout this application, various embodiments may be presented in a range format. It should be understood that the description in range format is merely for convenience and brevity and should not be construed as an inflexible limitation on the scope of the disclosure. Accordingly, the description of a range should be considered to have specifically disclosed all the possible subranges as well as individual numerical values within that range. For example, description of a range such as from 1 to 6 should be considered to have specifically disclosed subranges such as from 1 to 3, from 1 to 4, from 1 to 5, from 2 to 4, from 2 to 6, from 3 to 6 etc., as well as individual numbers within that range, for example, 1, 2, 3, 4, 5, and 6. This applies regardless of the breadth of the range.

[0316] The ranges disclosed herein also encompass any and all overlap, sub-ranges, and combinations thereof. Language such as “up to,” “at least,” “greater than,” “less than,” “between,” and the like includes the number recited. Numbers preceded by a term such as “approximately”, “about”, and “substantially” as used herein include the recited numbers, and also represent an amount close to the stated amount that still performs a desired function or achieves a desired result. The term “about” or “approximately” may mean within an acceptable error range for the particular value, which will depend in part on how the value is measured or determined, e.g., the limitations of the measurement system. For example, the terms “approximately”, “about”, and “substantially” may refer to an amount that is within less than 10% of, within less than 5% of, within less than 1% of, within less than 0.1% of, and within less than 0.01% of the stated amount. For example, “about” may mean within 1 or more than 1 standard deviation, per the practice in the art. Alternatively, “about” may mean a range of up toAtty Dkt No.: 49880-72260120%, up to 10%, up to 5%, or up to 1% of a given value. As used herein, the term “about” a number refers to that number plus or minus 10% of that number. The term “about” a range refers to that range minus 10% of its lowest value and plus 10% of its greatest value. Where particular values are described in the application and claims, unless otherwise stated the term “about” meaning within an acceptable error range for the particular value may be assumed.

[0317] As used in the specification and claims, the singular forms “a”, “an” and “the” include plural references unless the context clearly dictates otherwise. For example, the term “a sample” includes a plurality of samples, including mixtures thereof.

[0318] The terms “determining,” “measuring,” “evaluating,” “assessing,” “assaying,” and “analyzing” are often used interchangeably herein to refer to forms of measurement. The terms include determining if an element is present or not (for example, detection). These terms can include quantitative, qualitative or quantitative and qualitative determinations. Assessing can be relative or absolute. “Detecting the presence of’ can include determining the amount of something present in addition to determining whether it is present or absent depending on the context.

[0319] The terms “subject,” “individual,” or “patient” are often used interchangeably herein. A “subject” can be a biological entity containing expressed genetic materials. The subject can be a mammal. The mammal can be a human. The subject may be diagnosed or suspected of being at high risk for a disease. In some cases, the subject is not necessarily diagnosed or suspected of being at high risk for the disease.

[0320] As used herein, the terms “treatment” or “treating” are used in reference to a pharmaceutical or other intervention regimen for obtaining beneficial or desired results in the recipient. Beneficial or desired results include but are not limited to a therapeutic benefit and / or a prophylactic benefit. A therapeutic benefit may refer to eradication or amelioration of symptoms or of an underlying disorder being treated. Also, a therapeutic benefit can be achieved with the eradication or amelioration of one or more of the physiological symptoms associated with the underlying disorder such that an improvement is observed in the subject, notwithstanding that the subject may still be afflicted with the underlying disorder. A prophylactic effect includes delaying, preventing, or eliminating the appearance of a disease or condition, delaying or eliminating the onset of symptoms of a disease or condition, slowing, halting, or reversing the progression of a disease or condition, or any combination thereof. For prophylactic benefit, a subject at risk of developing a particular disease, or to a subject reporting one or more of the physiological symptoms of a disease may undergo treatment, even though a diagnosis of this disease may not have been made.Atty Dkt No.: 49880-722601

[0321] The section headings used herein are for organizational purposes only and are not to be construed as limiting the subject matter described.Clauses

[0322] 1. A magnetic resonance imaging (MRI) system for the screening of pelvic organ prolapse (POP), the MRI system comprising: a housing comprising a surface for contact with a subject; and a radio frequency receive (RF RX) coil network; wherein the RF RX coil network is configured to enable imaging in a region of interest, wherein the region of interest is external to the surface of the housing by a distance ranging from about 80 mm to about 120 mm.

[0323] 2. The MRI system of clause 1, wherein the RF RX coil network is configured to fully cover the surface such that there is no access aperture on the surface nearest the region of interest.

[0324] 3. The MRI system of clause 1 or 2, wherein the RF RX coil network is configured for imaging external to the surface by a distance of about 100 mm.

[0325] 4. The MRI system of any one of clauses 1 to 3, wherein the RF RX coil network comprises a plurality of RF RX coils.

[0326] 5. The MRI system of any one of clauses 1 to 4, wherein the RF RX coil network comprises a plurality of interconnected RF RX coils.

[0327] 6. The MRI system of any one of clauses 1 to 5, wherein the RF RX coil network comprises a plurality of coupled RF RX coils.

[0328] 7. The MRI system of any one of clauses 1 to 6, wherein a number of turns and loops of the RF RX coil is configured to be adjustable to cover an entire space between legs of the subject such that the region of interest is entirely or partially covered.

[0329] 8. The MRI system of any one of clauses 1 to 7, wherein the housing further comprises a radio frequency transmit (RF TX) coil proximate to the surface of the housing, wherein the RF TX coil is configured to generate an electromagnetic field in the region of interest.

[0330] 9. The MRI system of clause 8, the RF TX coil comprises a plurality of figure-8 coils arranged proximal the surface.

[0331] 10. The MRI system of clause 8 or 9, wherein the plurality of figure-8 coils are configured to generate a varying magnetic RF field within the region of interest.

[0332] 11. The MRI system of any one of clauses 8 to 10, wherein the plurality of figure-8 coils are orthogonal to each other.Atty Dkt No.: 49880-722601

[0333] 12. The MRI system of any one of clauses 8 to 11, wherein the plurality of figure-8 coils are tunable to same radiofrequency (RF) resonant frequencies.

[0334] 13. The MRI system of any one of clauses 8 to 12, wherein the plurality of figure-8 coils are tunable to different RF resonant frequencies.

[0335] 14. The MRI system of any one of clauses 8 to 13, wherein the plurality of figure-8 coils are configured to generate a uniform magnetic RF field within the region of interest.

[0336] 15. The MRI system of any one of clauses 1 to 14, further comprising an electromagnet configured to generate an electromagnetic field in the region of interest.

[0337] 16. The MRI system of any one of clauses 1 to 15, wherein the housing further comprises a gradient coil set positioned proximate to the surface, wherein the gradient coil set is configured to generate an electromagnetic field in the region of interest.

[0338] 17. The MRI system of clause 16, wherein the gradient coil set comprises a singlesided gradient coil set.

[0339] 18. The MRI system of any one of clauses 1 to 17, wherein the MRI system is configured to be used for one or more of diagnosis, grading, treatment planning, or monitoring of POP.

[0340] 19. The MRI system of any one of clauses 1 to 18, wherein the MRI system comprises a magnetic field strength of less than about 0.5 T.

[0341] 20. The MRI system of any one of clauses 1 to 19, wherein the MRI system comprises one or more of an open or single-sided MRI.

[0342] 21. The MRI system of any one of clauses 1 to 20, wherein the housing comprises a through-bore access aperture.

[0343] 22. The MRI system of any one of clauses 1 to 20, wherein the housing does not comprise a through-bore access aperture.

[0344] 23. The MRI system of any one of clauses 1 to 22, wherein the MRI system is configured to be used in an office setting without shielding or floor reinforcements.

[0345] 24. The MRI system of any one of clauses 1 to 23, wherein the MRI system comprises at least one permanent magnet configured for use without superconducting material.

[0346] 25. The MRI system of any one of clauses 1 to 24, wherein the RF RX coil is configured to capture images of the subject when the subject is in a position in front of or on top of the MRI, wherein the position is a high lithotomy, an inclined lithotomy, or a seated position over the MRI.Atty Dkt No.: 49880-722601

[0347] 26. The MRI system of clause 25, wherein the RF RX coil is configured to capture images of the subject when the subject is in contact with the surface of the MRI in the high lithotomy, the inclined lithotomy, or the seated position.

[0348] 27. The MRI system of clause 25 or 26, wherein the housing is configured to be positioned such that a central axis thereof is perpendicular to a floor when capturing images of the subject in the high lithotomy or the inclined lithotomy.

[0349] 28. The MRI system of clause 25 or 26, wherein the housing is configured to be positioned such that a central axis thereof is parallel to a floor when capturing images of the subject in the seated position.

[0350] 29. The MRI system of any one of clauses 25 to 28, wherein the MRI system is configured to be usable in a first mode and a second mode, wherein the first mode comprises capturing images of the subject in the high lithotomy or the inclined lithotomy when the housing is positioned such that a central axis thereof is perpendicular to a floor, and wherein the second mode comprises capturing images of the subject in the seated position when the housing is positioned such that a central axis thereof is parallel to the floor.

[0351] 30. The MRI system of any one of clauses 1 to 29, wherein the MRI system is configured to record dynamic imaging of activities applying pressure to pelvic organs of the subject.

[0352] 31. The MRI system of any one of clauses 1 to 30, further comprising a processor configured to run a computer-implemented method, wherein the computer-implemented method comprises one or more of automatically screening, diagnosing, or grading POP.

[0353] 32. The MRI system of clause 31, wherein the computer-implemented method comprises employing a machine learning based system trained on at least one training dataset.

[0354] 33. The MRI system of clause 32, wherein the training dataset comprises at least one of a dataset comprising data from multiple subjects, a dataset comprising longitudinal data from one subject, or a combination thereof.

[0355] 34. The MRI system of clauses 33, wherein the computer-implemented method comprises analyzing images comprising the dataset comprising longitudinal data from one subject acquired over time to manually detect and quantify anatomical changes over time.

[0356] 35. The MRI system of clauses 33, wherein the computer-implemented method comprises analyzing images comprising the dataset comprising longitudinal data from one subject acquired over time to automatically detect and quantify anatomical changes over time.Atty Dkt No.: 49880-722601

[0357] 36. The MRI system of clause 35, wherein the computer-implemented method comprises detecting and quantifying anatomical changes over time automatically through coregistrations with prior images or predefined protocols.

[0358] 37. The MRI system of any one of clause 34 to 36, wherein the computer- implemented method comprises determining whether the anatomical changes are of a normal or an abnormal characteristic and grading the anatomical changes if a prolapse is detected.

[0359] 38. The MRI system of any one of clauses 31 to 37, wherein the computer- implemented method comprises employing one or more of an Al-based segmentation, classification, or regression model to assess POP via one or more of detection, grading, surveillance, or treatment recommendations.

[0360] 39. The MRI system of any one of clauses 31 to 38, wherein the computer- implemented method comprises providing treatment recommendations based on a POP determination and grade.

[0361] 40. The MRI system of any one of clauses 31 to 39, wherein the computer- implemented method comprises detecting early anatomical changes.

[0362] 41. The MRI system of clause 40, wherein the computer-implemented method comprises detecting the early anatomical changes automatically.

[0363] 42. The MRI system of any one of clauses 31 to 41, wherein the computer- implemented method comprises monitoring progress of the POP via images of the subject acquired during a treatment, after a treatment, or a combination thereof.

[0364] 43. The MRI system of clause 42, wherein the computer-implemented method comprises recommending at least one alternative treatment if a predetermined treatment progress threshold is not achieved, wherein a predetermined treatment progress is determined based on the monitored progress of the POP.

[0365] 44. The MRI system of any one of clauses 31 to 43, wherein the computer- implemented method comprises providing feedback to a user, wherein the user is different from the subject, wherein the feedback comprises a progress of a treatment, wherein the feedback is determined from analyzed changes in anatomy across multiple images.

[0366] 45. The MRI system of any one of clauses 31 to 44, wherein the computer- implemented method comprises recommending a treatment to aid a physician in decision making.

[0367] 46. The MRI system of any one of clauses 31 to 45, wherein the computer- implemented method comprises training a classifier model on one or more of MR images ofAtty Dkt No.: 49880-722601 normal anatomy, different types and grades of POP, or images of POP progressing over time from early onset to proper diagnosis.

[0368] 47. The MRI system of any one of clauses 31 to 46, wherein the computer- implemented method comprises using an Al model to perform segmentation and landmark identification on low field MRI comprising a static component or a dynamic component for grading of POP.

[0369] 48. The MRI system of any one of clauses 31 to 47, wherein the computer- implemented method comprises using a classification model for determination of POP based on continuous distance metrics from one or more of a static low field MRI exam, a dynamic low field MRI exam, or a physical examination.

[0370] 49. The MRI system of any one of clauses 31 to 48, wherein the computer- implemented method comprises using an Al model for visualization of longitudinal low field MRI data with a static component or a dynamic component.

[0371] 50. The MRI system of any one of clauses 31 to 49, wherein the computer- implemented method comprises using an Al model for identification of hotspots indicating progressing prolapse or resolving prolapse.

[0372] 51. The MRI system of any one of clauses 31 to 50, wherein the computer- implemented method comprises using a spatio-temporal model using longitudinal low field MRI data with a static component or a dynamic component for prediction of anatomical segmentation masks at a future time point.

[0373] 52. The MRI system of any one of clauses 31 to 51, wherein the computer- implemented method comprises using a spatio-temporal model using longitudinal low field MRI data with a static component or a dynamic component for prediction of low field MRI at a future time point.

[0374] 53. The MRI system of clause 52, wherein the computer-implemented method comprises using a classification model and the low field MRI prediction model to compare low field MRI at the future time point and predicted low field MRI at the future time point to evaluate whether a health condition deviated from an expected trajectory.

[0375] 54. The MRI system of clause 52 or 53, wherein the computer-implemented method comprises using a classification model and the low field MRI prediction model to compare low field MRI at the future time point and predicted low field MRI at the future time point to evaluate whether prolapse deviated from an expected trajectory.

[0376] 55. The MRI system of any one of clauses 31 to 54, wherein the computer- implemented method comprises using a spatio-temporal model for generating trajectory andAtty Dkt No.: 49880-722601 velocity metrics from longitudinal low field MRI with a static component or a dynamic component.

[0377] 56. The MRI system of any one of clauses 31 to 55, wherein the computer- implemented method comprises using a prognostic model for one or more of risk stratification or outcome prediction via one or more of a) trajectory and velocity metrics derived from low field MRI, b) physical examination-based metrics, c) clinical variables, or d) symptom and quality of life scores.

[0378] 57. The MRI system of any one of clauses 1 to 56, wherein the MRI system is configured to be rotatable 90 degrees such that the system has an imaging field of view on top of the MRI system.

[0379] 58. The MRI system of any one of clauses 1 to 57, wherein the MRI system is configured for static and dynamic magnetic resonance (MR) imaging.

[0380] 59. The MRI system of clause 58, wherein a shape and orientation of the housing are configured to use gravity and intra-abdominal natural pressures to increase MR imaging access to the region of interest during static MR imaging.

[0381] 60. The MRI system of clause 58 or 59, wherein the static MR imaging comprises a first imaging protocol.

[0382] 61. The MRI system of clause 60, wherein the first imaging protocol comprises a scout scan configured to determine a position of the subject within a field of view of the MRI system.

[0383] 62. The MRI system of clause 60 or 61, wherein the first imaging protocol comprises T2-weighted fast spin echo imaging of about 24 cm to about 30 cm in the axial or coronal plane and about 30 to about 40 cm in the sagittal plane.

[0384] 63. The MRI system of clause 62, wherein the T2-weighted fast spin echo imaging comprises from about a 3 mm to about a 5 mm static slice thickness with less than about a 1 mm gap-10385] 64. The MRI system of any one of clauses 60 to 63, wherein the first imaging protocol comprises T1 fast spin echo imaging.

[0386] 65. The MRI system of any one of clauses 60 to 64, wherein the first imaging protocol comprises fat saturated T1 imaging.

[0387] 66. The MRI system of any one of clauses 60 to 65, wherein the first imaging protocol comprises diffusion weighted imaging.Atty Dkt No.: 49880-722601

[0388] 67. The MRI system of any one of clauses 58 to 66, wherein the static MR imaging is configured to screen for early onset of POP and to detect one or more of cystocele tendencies, uterine / vault descent, perineal descent, or levator ballooning.

[0389] 68. The MRI system of any one of clauses 58 to 67, wherein the dynamic MR imaging is configured to provide a quantitative pelvic organ prolapse equivalent quantification (POP-Q) score.

[0390] 69. The MRI system of any one of clauses 58 to 68, wherein the dynamic MR imaging comprises a second imaging protocol.

[0391] 70. The MRI system of clause 69, wherein the second imaging protocol comprises T2 static fast spin echo imaging.

[0392] 71. The MRI system of clause 69 or 70, wherein the second imaging protocol comprises T1 static fast spin echo imaging.

[0393] 72. A method of performing magnetic resonance (MR) imaging, the method comprising: (a) inputting patient parameters into a magnetic resonance imaging (MRI) system, the system comprising: a housing comprising a surface for contact with a subject; and a radio frequency receive (RF RX) coil network; (b) activating the RF RX coil network to obtain imaging data in the region of interest, wherein the region of interest is external to the surface of the housing by a distance ranging from about 80 mm to about 120 mm; (c) reconstructing obtained imaging data to produce an output image for analysis; and (d) displaying the output image for user review and annotation.

[0394] 73. The method of clause 72, wherein the RF RX coil network is configured to fully cover the surface such that there is no access aperture on the surface nearest the region of interest.

[0395] 74. The method of clause 72 or 73, wherein the region of interest is external to the surface of the housing by about 100 mm.

[0396] 75. The method of any one of clauses 72 to 74, wherein the RF RX coil network comprises a plurality of RF RX coils.

[0397] 76. The method of any one of clauses 72 to 75, wherein the RF RX coil network comprises a plurality of interconnected RF RX coils.

[0398] 77. The method of any one of clauses 72 to 76, wherein the RF RX coil network comprises a plurality of coupled RF RX coils.

[0399] 78. The method of any one of clauses 72 to 77, wherein a number of turns and loops of the RF RX coil is configured to cover an entire space between legs of the subject such that the region of interest is entirely or partially covered.Atty Dkt No.: 49880-722601

[0400] 79. The method of any one of clauses 72 to 78, wherein the housing further comprises a radio frequency transmit (RF TX) coil proximate to the surface of the housing, wherein the RF TX coil is configured to generate an electromagnetic field in the region of interest.

[0401] 80. The method of clause 79, the RF TX coil comprises a plurality of figure-8 coils arranged proximal the surface.

[0402] 81. The method of clause 79 or 80, wherein the plurality of figure-8 coils are configured to generate a varying magnetic RF field within the region of interest.

[0403] 82. The method of any one of clauses 79 to 81, wherein the plurality of figure-8 coils are orthogonal to each other.

[0404] 83. The method of any one of clauses 79 to 82, further comprising tuning the plurality of figure-8 coils to same radiofrequency (RF) resonant frequencies.

[0405] 84. The method of any one of clauses 79 to 83, further comprising tuning the plurality of figure-8 coils to different RF resonant frequencies.

[0406] 85. The method of any one of clauses 79 to 84, further comprising generating, via the plurality of figure-8 coils, a uniform magnetic RF field within the region of interest.

[0407] 86. The method of any one of clauses 72 to 85, further comprising generating an electromagnetic field in the region of interest via activating an electromagnet in the MRI system.

[0408] 87. The method of any one of clauses 72 to 86, further comprising generating an electromagnetic field in the region of interest via activating a gradient coil set disposed in the housing and positioned proximate to the surface.

[0409] 88. The method of clause 87, wherein the gradient coil set comprises a single-sided gradient coil set.

[0410] 89. The method of any one of clauses 72 to 88, further comprising using the MRI system for one or more of diagnosis, grading, treatment planning, or monitoring of POP.

[0411] 90. The method of any one of clauses 72 to 89, wherein the MRI system comprises a magnetic field strength of less than about 0.5 T.

[0412] 91. The method of any one of clauses 72 to 90, wherein the MRI system comprises one or more of an open or single-sided MRI.

[0413] 92. The method of any one of clauses 72 to 91, wherein the housing comprises a bore.

[0414] 93. The method of any one of clauses 72 to 91, wherein the housing does not comprise a bore.

[0415] 94. The method of any one of clauses 72 to 93, wherein the MRI system is configured to be used in an office setting without shielding or floor reinforcements.Atty Dkt No.: 49880-722601

[0416] 95. The method of any one of clauses 72 to 94, further comprising using at least one permanent magnet configured without superconducting material.

[0417] 96. The method of any one of clauses 72 to 95, further comprising capturing images of the subject, via the RF RX coil, when the subject is in a position in front of or on top of the MRI, wherein the position is a high lithotomy, an inclined lithotomy, or a seated position over the MRI.

[0418] 97. The method of clause 96, further comprising capturing images of the subject, via the RF RX coil, when the subject is in contact with the surface of the MRI in the high lithotomy, the inclined lithotomy, or the seated position.

[0419] 98. The method of clause 96 or 97, further comprising positioning the housing such that a central axis thereof is perpendicular to a floor when capturing images of the subject in the high lithotomy or the inclined lithotomy.

[0420] 99. The method of clause 96 or 97, further comprising positioning the housing such that a central axis thereof is parallel to a floor when capturing images of the subject in the seated position.

[0421] 100. The method of any one of clauses 96 to 99, further comprising using the MRI system in a first mode and a second mode, wherein the first mode comprises capturing images of the subject in the high lithotomy or the inclined lithotomy when the housing is positioned such that a central axis thereof is perpendicular to a floor, and wherein the second mode comprises capturing images of the subject in the seated position when the housing is positioned such that a central axis thereof is parallel to the floor.

[0422] 101. The method of any one of clauses 72 to 100, further comprising recording, via the MRI system, dynamic imaging of activities applying pressure to pelvic organs of the subject.

[0423] 102. The method of any one of clauses 72 to 101, further comprising one or more of automatically screening, diagnosing, or grading POP.

[0424] 103. The method of clause 102, further comprising employing a machine learning based system trained on at least one training dataset.

[0425] 104. The method of clause 103, wherein the training dataset comprises at least one of a dataset comprising data from multiple subjects, a dataset comprising longitudinal data from one subject, or a combination thereof.

[0426] 105. The method of clauses 104, further comprising analyzing images comprising the dataset comprising longitudinal data from one subject acquired over time to manually detect and quantify anatomical changes over time.Atty Dkt No.: 49880-722601

[0427] 106. The method of clauses 104, further comprising analyzing images comprising the dataset comprising longitudinal data from one subject acquired over time to automatically detect and quantify anatomical changes over time.

[0428] 107. The method of clause 106, further comprising detecting and quantifying anatomical changes over time automatically through co-regi strati ons with prior images or predefined protocols.

[0429] 108. The method of any one of clause 105 to 107, further comprising determining whether the anatomical changes are of a normal or an abnormal characteristic and grading the anatomical changes if a prolapse is detected.

[0430] 109. The method of any one of clauses 102 to 108, further comprising employing one or more of an Al-based segmentation, classification, or regression model to assess POP via one or more of detection, grading, surveillance, or treatment recommendations.

[0431] 110. The method of any one of clauses 102 to 109, further comprising providing treatment recommendations based on a POP determination and grade.

[0432] 111. The method of any one of clauses 102 to 110, further comprising detecting early anatomical changes.

[0433] 112. The method of clause 111, further comprising detecting the early anatomical changes automatically.

[0434] 113. The method of any one of clauses 102 to 112, further comprising monitoring progress of the POP via images of the subject acquired during a treatment, after a treatment, or a combination thereof.

[0435] 114. The method of clause 113, further comprising recommending at least one alternative treatment if a predetermined treatment progress threshold is not achieved, wherein a predetermined treatment progress is determined based on the monitored progress of the POP.

[0436] 115. The method of any one of clauses 102 to 114, further comprising providing feedback to a user, wherein the user is different from the subject, wherein the feedback comprises a progress of a treatment, wherein the feedback is determined from analyzed changes in anatomy across multiple images.

[0437] 116. The method of any one of clauses 102 to 115, further comprising recommending a treatment to aid a physician in decision making.

[0438] 117. The method of any one of clauses 102 to 116, further comprising training a classifier model on one or more of MR images of normal anatomy, different types and grades of POP, or images of POP progressing over time from early onset to proper diagnosis.Atty Dkt No.: 49880-722601

[0439] 118. The method of any one of clauses 102 to 117, further comprising using an Al model to perform segmentation and landmark identification on low field MRI comprising a static component or a dynamic component for grading of POP.

[0440] 119. The method of any one of clauses 102 to 118, further comprising using a classification model for determination of POP based on continuous distance metrics from one or more of a static low field MRI exam, a dynamic low field MRI exam, or a physical examination.

[0441] 120. The method of any one of clauses 102 to 119, further comprising using an Al model for visualization of longitudinal low field MRI data with a static component or a dynamic component.

[0442] 121. The method of any one of clauses 102 to 120, further comprising using an Al model for identification of hotspots indicating progressing prolapse or resolving prolapse.

[0443] 122. The method of any one of clauses 102 to 121, further comprising using a spatiotemporal model using longitudinal low field MRI data with a static component or a dynamic component for prediction of anatomical segmentation masks at a future time point.

[0444] 123. The method of any one of clauses 102 to 122, further comprising using a spatiotemporal model using longitudinal low field MRI data with a static component or a dynamic component for prediction of low field MRI at a future time point.

[0445] 124. The method of clause 123, further comprising using a classification model and the low field MRI prediction model to compare low field MRI at the future time point and predicted low field MRI at the future time point to evaluate whether a health condition deviated from an expected trajectory.

[0446] 125. The method of clause 123 or 124, further comprising using a classification model and the low field MRI prediction model to compare low field MRI at the future time point and predicted low field MRI at the future time point to evaluate whether prolapse deviated from an expected trajectory.

[0447] 126. The method of any one of clauses 102 to 125, further comprising using a spatiotemporal model for generating trajectory and velocity metrics from longitudinal low field MRI with a static component or a dynamic component.

[0448] 127. The method of any one of clauses 102 to 126, further comprising using a prognostic model for one or more of risk stratification or outcome prediction via one or more of a) trajectory and velocity metrics derived from low field MRI, b) physical examination-based metrics, c) clinical variables, or d) symptom and quality of life scores.Atty Dkt No.: 49880-722601

[0449] 128. The method of any one of clauses 72 to 127, wherein the MRI system is configured to be rotatable 90 degrees such that the system has an imaging field of view on top of the MRI system.

[0450] 129. The method of any one of clauses 72 to 128, further comprising executing, via the MRI system, static and dynamic magnetic resonance (MR) imaging.

[0451] 130. The method of clause 129, wherein a shape and orientation of the housing are configured to use gravity and intra-abdominal natural pressures to increase MR imaging access to the region of interest during static MR imaging.

[0452] 131. The method of clause 129 or 130, wherein the static MR imaging comprises a first imaging protocol.

[0453] 132. The method of clause 131, further comprising determining, via a scout scan, a position of the subject within a field of view of the MRI system.

[0454] 133. The method of clause 131 or 132, wherein the first imaging protocol comprises T2-weighted fast spin echo imaging of about 24 cm to about 30 cm in the axial or coronal plane and about 30 to about 40 cm in the sagittal plane.

[0455] 134. The method of clause 133, wherein the T2-weighted fast spin echo imaging comprises from about a 3 mm to about a 5 mm static slice thickness with less than about a 1 mm gap-10456] 135. The method of any one of clauses 129 to 134, wherein the first imaging protocol comprises T1 fast spin echo imaging.

[0457] 136. The method of any one of clauses 129 to 135, wherein the first imaging protocol comprises fat saturated T1 imaging.

[0458] 137. The method of any one of clauses 129 to 136, wherein the first imaging protocol comprises diffusion weighted imaging.

[0459] 138. The method of any one of clauses 127 to 137, further comprising screening for early onset of POP and detecting one or more of cystocele tendencies, uterine / vault descent, perineal descent, or levator ballooning via the static MR imaging.

[0460] 139. The method of any one of clauses 127 to 138, further comprising providing an equivalent quantitative pelvic organ prolapse quantification (POP-Q) score via the dynamic MR imaging.

[0461] 140. The method of any one of clauses 127 to 139, wherein the dynamic MR imaging comprises a second imaging protocol.

[0462] 141. The method of clause 140, wherein the second imaging protocol comprises T2 static fast spin echo imaging.Atty Dkt No.: 49880-722601

[0463] 142. The method of clause 140 or 141, wherein the second imaging protocol comprises T1 static fast spin echo imaging.

[0464] 143. The method of any one of clauses 72 to 142, further comprising executing a subject positioning protocol comprising running at least one scan.

[0465] 144. The method of any one of clauses 72 to 143, further comprising running at least one static scan.

[0466] 145. The method of any one of clauses 72 to 144, further comprising running at least one dynamic scan.

[0467] While preferred embodiments of the present disclosure have been shown and described herein, it will be obvious to those skilled in the art that such embodiments are provided by way of example only. Numerous variations, changes, and substitutions can occur to those skilled in the art without departing from the present disclosure. It should be understood that various alternatives to the embodiments of the present disclosure described herein may be employed in practicing the present disclosure. It is intended that the following claims define the scope of the invention and that methods and structures within the scope of these claims and their equivalents be covered thereby.EXAMPLESExample 1 - Static MRI for Screening and Diagnosis of Pelvic Organ Prolapse

[0468] Static MR imaging in a seated position has the advantage of gravity and intra-abdominal pressures being present in natural form, being a more comfortable patient position, and providing an open configuration. Performing low-field open MRI in a position where a patient can sit on the MRI device, as illustrated, for example, in FIG. 2, can be used for screening, diagnosis and post-treatment follow ups of a subject with or suspected of having pelvic organ prolapse (POP). A protocol, as shown in Table 1, is used for a comprehensive 15-20 minute MR exam:Table 1: Patient Preparation and Positioning:Atty Dkt No.: 49880-722601

[0469] The MRI protocol involves the following scans: (i) a scout scan to position the patient within the field of view; (ii) a T2 weighted fast-spin echo (FSE) image; (iii) a T1 weighted FSE image; (iv) optionally a fat saturated T1 weighted image; and (v) optionally a diffusion weighted image (DWI). The T2 weighted FCE image can comprise 24-30 cm (axial / coronal) x 30-40 cm (sagittal), 3-5 mm static slice thickness, with less than a 1 mm gap.

[0470] Table 2 provides specification and purpose information for the scans performed in the example MRI protocol described herein.Table 2: Specification and Purpose of the Scans Performed in an Example MRI Protocol:

[0471] The static test is designed to screen for an early onset of POP and can detect cystocele tendencies, uterine / vault descent, perineal descent, and levator ballooning. These measurements directly correlate to suspected stage I - stage III+ tendencies. Using clinical thresholds, the test can further be useful for surgical planning.

[0472] Dynamic MRI provides a POP-Q equivalent score and can be performed in a seated or a supine position. Table 3 provides clinical protocols for static and dynamic imaging using the MRI systems described herein. Patient preparation can include the preparation provided in Table 1 and further comprise optional rectal opacification for defecation phase, and optional vaginal gel if evaluating vault prolapse.Atty Dkt No.: 49880-722601Table 3: Clinical protocol details for static and dynamic low field MRI imaging.

Claims

1. Atty Dkt No.: 49880-722601CLAIMSWHAT IS CLAIMED IS:

1. A magnetic resonance imaging (MRI) system for the screening of pelvic organ prolapse (POP), the MRI system comprising:(a) a housing comprising a surface for contact with a subject; and(b) a radio frequency receive (RF RX) coil network; wherein the RF RX coil network is configured to enable imaging in a region of interest, wherein the region of interest is external to the surface of the housing by a distance ranging from about 80 mm to about 120 mm.

2. The MRI system of claim 1, wherein the RF RX coil network is configured to fully cover the surface such that there is no access aperture on the surface nearest the region of interest.

3. The MRI system of claim 1 or 2, wherein the RF RX coil network is configured for imaging external to the surface by a distance of about 100 mm.

4. The MRI system of any one of claims 1 to 3, wherein the RF RX coil network comprises a plurality of RF RX coils.

5. The MRI system of any one of claims 1 to 4, wherein the RF RX coil network comprises a plurality of interconnected RF RX coils.

6. The MRI system of any one of claims 1 to 5, wherein the RF RX coil network comprises a plurality of coupled RF RX coils.

7. The MRI system of any one of claims 1 to 6, wherein a number of turns and loops of the RF RX coil is configured to be adjustable to cover an entire space between legs of the subject such that the region of interest is entirely or partially covered.

8. The MRI system of any one of claims 1 to 7, wherein the housing further comprises a radio frequency transmit (RF TX) coil proximate to the surface of the housing, wherein the RF TX coil is configured to generate an electromagnetic field in the region of interest.

9. The MRI system of claim 8, the RF TX coil comprises a plurality of figure-8 coils arranged proximal the surface.

10. The MRI system of claim 8 or 9, wherein the plurality of figure-8 coils are configured to generate a varying magnetic RF field within the region of interest.

11. The MRI system of any one of claims 8 to 10, wherein the plurality of figure-8 coils are orthogonal to each other.

12. The MRI system of any one of claims 8 to 11, wherein the plurality of figure-8 coils are tunable to same radiofrequency (RF) resonant frequencies.Atty Dkt No.: 49880-72260113. The MRI system of any one of claims 8 to 12, wherein the plurality of figure-8 coils are tunable to different RF resonant frequencies.

14. The MRI system of any one of claims 8 to 13, wherein the plurality of figure-8 coils are configured to generate a uniform magnetic RF field within the region of interest.

15. The MRI system of any one of claims 1 to 14, further comprising an electromagnet configured to generate an electromagnetic field in the region of interest.

16. The MRI system of any one of claims 1 to 15, wherein the housing further comprises a gradient coil set positioned proximate to the surface, wherein the gradient coil set is configured to generate an electromagnetic field in the region of interest.

17. The MRI system of claim 16, wherein the gradient coil set comprises a singlesided gradient coil set.

18. The MRI system of any one of claims 1 to 17, wherein the MRI system is configured to be used for one or more of diagnosis, grading, treatment planning, or monitoring of POP.

19. The MRI system of any one of claims 1 to 18, wherein the MRI system comprises a magnetic field strength of less than about 0.5 T.

20. The MRI system of any one of claims 1 to 19, wherein the MRI system comprises one or more of an open or single-sided MRI.

21. The MRI system of any one of claims 1 to 20, wherein the housing comprises a through-bore access aperture.

22. The MRI system of any one of claims 1 to 20, wherein the housing does not comprise a through-bore access aperture.

23. The MRI system of any one of claims 1 to 22, wherein the MRI system is configured to be used in an office setting without shielding or floor reinforcements.

24. The MRI system of any one of claims 1 to 23, wherein the MRI system comprises at least one permanent magnet configured for use without superconducting material.

25. The MRI system of any one of claims 1 to 24, wherein the RF RX coil is configured to capture images of the subject when the subject is in a position in front of or on top of the MRI, wherein the position is a high lithotomy, an inclined lithotomy, or a seated position over the MRI.

26. The MRI system of claim 25, wherein the RF RX coil is configured to capture images of the subject when the subject is in contact with the surface of the MRI in the high lithotomy, the inclined lithotomy, or the seated position.Atty Dkt No.: 49880-72260127. The MRI system of claim 25 or 26, wherein the housing is configured to be positioned such that a central axis thereof is perpendicular to a floor when capturing images of the subject in the high lithotomy or the inclined lithotomy.

28. The MRI system of claim 25 or 26, wherein the housing is configured to be positioned such that a central axis thereof is parallel to a floor when capturing images of the subject in the seated position.

29. The MRI system of any one of claims 25 to 28, wherein the MRI system is configured to be usable in a first mode and a second mode, wherein the first mode comprises capturing images of the subject in the high lithotomy or the inclined lithotomy when the housing is positioned such that a central axis thereof is perpendicular to a floor, and wherein the second mode comprises capturing images of the subject in the seated position when the housing is positioned such that a central axis thereof is parallel to the floor.

30. The MRI system of any one of claims 1 to 29, wherein the MRI system is configured to record dynamic imaging of activities applying pressure to pelvic organs of the subject.

31. The MRI system of any one of claims 1 to 30, further comprising a processor configured to run a computer-implemented method, wherein the computer-implemented method comprises one or more of automatically screening, diagnosing, or grading POP.

32. The MRI system of claim 31, wherein the computer-implemented method comprises employing a machine learning based system trained on at least one training dataset.

33. The MRI system of claim 32, wherein the training dataset comprises at least one of a dataset comprising data from multiple subjects, a dataset comprising longitudinal data from one subject, or a combination thereof.

34. The MRI system of claims 33, wherein the computer-implemented method comprises analyzing images comprising the dataset comprising longitudinal data from one subject acquired over time to manually detect and quantify anatomical changes over time.

35. The MRI system of claims 33, wherein the computer-implemented method comprises analyzing images comprising the dataset comprising longitudinal data from one subject acquired over time to automatically detect and quantify anatomical changes over time.

36. The MRI system of claim 35, wherein the computer-implemented method comprises detecting and quantifying anatomical changes over time automatically through coregistrations with prior images or predefined protocols.Atty Dkt No.: 49880-72260137. The MRI system of any one of claim 34 to 36, wherein the computer- implemented method comprises determining whether the anatomical changes are of a normal or an abnormal characteristic and grading the anatomical changes if a prolapse is detected.

38. The MRI system of any one of claims 31 to 37, wherein the computer- implemented method comprises employing one or more of an Al-based segmentation, classification, or regression model to assess POP via one or more of detection, grading, surveillance, or treatment recommendations.

39. The MRI system of any one of claims 31 to 38, wherein the computer- implemented method comprises providing treatment recommendations based on a POP determination and grade.

40. The MRI system of any one of claims 31 to 39, wherein the computer- implemented method comprises detecting early anatomical changes.

41. The MRI system of claim 40, wherein the computer-implemented method comprises detecting the early anatomical changes automatically.

42. The MRI system of any one of claims 31 to 41, wherein the computer- implemented method comprises monitoring progress of the POP via images of the subject acquired during a treatment, after a treatment, or a combination thereof.

43. The MRI system of claim 42, wherein the computer-implemented method comprises recommending at least one alternative treatment if a predetermined treatment progress threshold is not achieved, wherein a predetermined treatment progress is determined based on the monitored progress of the POP.

44. The MRI system of any one of claims 31 to 43, wherein the computer- implemented method comprises providing feedback to a user, wherein the user is different from the subject, wherein the feedback comprises a progress of a treatment, wherein the feedback is determined from analyzed changes in anatomy across multiple images.

45. The MRI system of any one of claims 31 to 44, wherein the computer- implemented method comprises recommending a treatment to aid a physician in decision making.

46. The MRI system of any one of claims 31 to 45, wherein the computer- implemented method comprises training a classifier model on one or more of MR images of normal anatomy, different types and grades of POP, or images of POP progressing over time from early onset to proper diagnosis.

47. The MRI system of any one of claims 31 to 46, wherein the computer- implemented method comprises using an Al model to perform segmentation and landmarkAtty Dkt No.: 49880-722601 identification on low field MRI comprising a static component or a dynamic component for grading of POP.

48. The MRI system of any one of claims 31 to 47, wherein the computer- implemented method comprises using a classification model for determination of POP based on continuous distance metrics from one or more of a static low field MRI exam, a dynamic low field MRI exam, or a physical examination.

49. The MRI system of any one of claims 31 to 48, wherein the computer- implemented method comprises using an Al model for visualization of longitudinal low field MRI data with a static component or a dynamic component.

50. The MRI system of any one of claims 31 to 49, wherein the computer- implemented method comprises using an Al model for identification of hotspots indicating progressing prolapse or resolving prolapse.

51. The MRI system of any one of claims 31 to 50, wherein the computer- implemented method comprises using a spatio-temporal model using longitudinal low field MRI data with a static component or a dynamic component for prediction of anatomical segmentation masks at a future time point.

52. The MRI system of any one of claims 31 to 51, wherein the computer- implemented method comprises using a spatio-temporal model using longitudinal low field MRI data with a static component or a dynamic component for prediction of low field MRI at a future time point.

53. The MRI system of claim 52, wherein the computer-implemented method comprises using a classification model and the low field MRI prediction model to compare low field MRI at the future time point and predicted low field MRI at the future time point to evaluate whether a health condition deviated from an expected trajectory.

54. The MRI system of claim 52 or 53, wherein the computer-implemented method comprises using a classification model and the low field MRI prediction model to compare low field MRI at the future time point and predicted low field MRI at the future time point to evaluate whether prolapse deviated from an expected trajectory.

55. The MRI system of any one of claims 31 to 54, wherein the computer- implemented method comprises using a spatio-temporal model for generating trajectory and velocity metrics from longitudinal low field MRI with a static component or a dynamic component.

56. The MRI system of any one of claims 31 to 55, wherein the computer- implemented method comprises using a prognostic model for one or more of risk stratification orAtty Dkt No.: 49880-722601 outcome prediction via one or more of a) trajectory and velocity metrics derived from low field MRI, b) physical examination-based metrics, c) clinical variables, or d) symptom and quality of life scores.

57. The MRI system of any one of claims 1 to 56, wherein the MRI system is configured to be rotatable 90 degrees such that the system has an imaging field of view on top of the MRI system.

58. The MRI system of any one of claims 1 to 57, wherein the MRI system is configured for static and dynamic magnetic resonance (MR) imaging.

59. The MRI system of claim 58, wherein a shape and orientation of the housing are configured to use gravity and intra-abdominal natural pressures to increase MR imaging access to the region of interest during static MR imaging.

60. The MRI system of claim 58 or 59, wherein the static MR imaging comprises a first imaging protocol.

61. The MRI system of claim 60, wherein the first imaging protocol comprises a scout scan configured to determine a position of the subject within a field of view of the MRI system.

62. The MRI system of claim 60 or 61, wherein the first imaging protocol comprises T2-weighted fast spin echo imaging of about 24 cm to about 30 cm in the axial or coronal plane and about 30 to about 40 cm in the sagittal plane.

63. The MRI system of claim 62, wherein the T2-weighted fast spin echo imaging comprises from about a 3 mm to about a 5 mm static slice thickness with less than about a 1 mm gap-64. The MRI system of any one of claims 60 to 63, wherein the first imaging protocol comprises T1 fast spin echo imaging.

65. The MRI system of any one of claims 60 to 64, wherein the first imaging protocol comprises fat saturated T1 imaging.

66. The MRI system of any one of claims 60 to 65, wherein the first imaging protocol comprises diffusion weighted imaging.

67. The MRI system of any one of claims 58 to 66, wherein the static MR imaging is configured to screen for early onset of POP and to detect one or more of cystocele tendencies, uterine / vault descent, perineal descent, or levator ballooning.

68. The MRI system of any one of claims 58 to 67, wherein the dynamic MR imaging is configured to provide a quantitative pelvic organ prolapse equivalent quantification (POP-Q) score.Atty Dkt No.: 49880-72260169. The MRI system of any one of claims 58 to 68, wherein the dynamic MR imaging comprises a second imaging protocol.

70. The MRI system of claim 69, wherein the second imaging protocol comprises T2 static fast spin echo imaging.

71. The MRI system of claim 69 or 70, wherein the second imaging protocol comprises T1 static fast spin echo imaging.

72. A method of performing magnetic resonance (MR) imaging, the method comprising:(a) inputting patient parameters into a magnetic resonance imaging (MRI) system, the system comprising:(i) a housing comprising a surface for contact with a subject; and(ii) a radio frequency receive (RF RX) coil network;(b) activating the RF RX coil network to obtain imaging data in the region of interest, wherein the region of interest is external to the surface of the housing by a distance ranging from about 80 mm to about 120 mm;(c) reconstructing obtained imaging data to produce an output image for analysis; and(d) displaying the output image for user review and annotation.

73. The method of claim 72, wherein the RF RX coil network is configured to fully cover the surface such that there is no access aperture on the surface nearest the region of interest.

74. The method of claim 72 or 73, wherein the region of interest is external to the surface of the housing by about 100 mm.

75. The method of any one of claims 72 to 74, wherein the RF RX coil network comprises a plurality of RF RX coils.

76. The method of any one of claims 72 to 75, wherein the RF RX coil network comprises a plurality of interconnected RF RX coils.

77. The method of any one of claims 72 to 76, wherein the RF RX coil network comprises a plurality of coupled RF RX coils.

78. The method of any one of claims 72 to 77, wherein a number of turns and loops of the RF RX coil is configured to cover an entire space between legs of the subject such that the region of interest is entirely or partially covered.Atty Dkt No.: 49880-72260179. The method of any one of claims 72 to 78, wherein the housing further comprises a radio frequency transmit (RF TX) coil proximate to the surface of the housing, wherein the RF TX coil is configured to generate an electromagnetic field in the region of interest.

80. The method of claim 79, the RF TX coil comprises a plurality of figure-8 coils arranged proximal the surface.

81. The method of claim 79 or 80, wherein the plurality of figure-8 coils are configured to generate a varying magnetic RF field within the region of interest.

82. The method of any one of claims 79 to 81, wherein the plurality of figure-8 coils are orthogonal to each other.

83. The method of any one of claims 79 to 82, further comprising tuning the plurality of figure-8 coils to same radiofrequency (RF) resonant frequencies.

84. The method of any one of claims 79 to 83, further comprising tuning the plurality of figure-8 coils to different RF resonant frequencies.

85. The method of any one of claims 79 to 84, further comprising generating, via the plurality of figure-8 coils, a uniform magnetic RF field within the region of interest.

86. The method of any one of claims 72 to 85, further comprising generating an electromagnetic field in the region of interest via activating an electromagnet in the MRI system.

87. The method of any one of claims 72 to 86, further comprising generating an electromagnetic field in the region of interest via activating a gradient coil set disposed in the housing and positioned proximate to the surface.

88. The method of claim 87, wherein the gradient coil set comprises a single-sided gradient coil set.

89. The method of any one of claims 72 to 88, further comprising using the MRI system for one or more of diagnosis, grading, treatment planning, or monitoring of POP.

90. The method of any one of claims 72 to 89, wherein the MRI system comprises a magnetic field strength of less than about 0.5 T.

91. The method of any one of claims 72 to 90, wherein the MRI system comprises one or more of an open or single-sided MRI.

92. The method of any one of claims 72 to 91, wherein the housing comprises a bore.

93. The method of any one of claims 72 to 91, wherein the housing does not comprise a bore.

94. The method of any one of claims 72 to 93, wherein the MRI system is configured to be used in an office setting without shielding or floor reinforcements.Atty Dkt No.: 49880-72260195. The method of any one of claims 72 to 94, further comprising using at least one permanent magnet configured without superconducting material.

96. The method of any one of claims 72 to 95, further comprising capturing images of the subject, via the RF RX coil, when the subject is in a position in front of or on top of the MRI, wherein the position is a high lithotomy, an inclined lithotomy, or a seated position over the MRI.

97. The method of claim 96, further comprising capturing images of the subject, via the RF RX coil, when the subject is in contact with the surface of the MRI in the high lithotomy, the inclined lithotomy, or the seated position.

98. The method of claim 96 or 97, further comprising positioning the housing such that a central axis thereof is perpendicular to a floor when capturing images of the subject in the high lithotomy or the inclined lithotomy.

99. The method of claim 96 or 97, further comprising positioning the housing such that a central axis thereof is parallel to a floor when capturing images of the subject in the seated position.

100. The method of any one of claims 96 to 99, further comprising using the MRI system in a first mode and a second mode, wherein the first mode comprises capturing images of the subject in the high lithotomy or the inclined lithotomy when the housing is positioned such that a central axis thereof is perpendicular to a floor, and wherein the second mode comprises capturing images of the subject in the seated position when the housing is positioned such that a central axis thereof is parallel to the floor.

101. The method of any one of claims 72 to 100, further comprising recording, via the MRI system, dynamic imaging of activities applying pressure to pelvic organs of the subject.

102. The method of any one of claims 72 to 101, further comprising one or more of automatically screening, diagnosing, or grading POP.

103. The method of claim 102, further comprising employing a machine learning based system trained on at least one training dataset.

104. The method of claim 103, wherein the training dataset comprises at least one of a dataset comprising data from multiple subjects, a dataset comprising longitudinal data from one subject, or a combination thereof.

105. The method of claims 104, further comprising analyzing images comprising the dataset comprising longitudinal data from one subject acquired over time to manually detect and quantify anatomical changes over time.Atty Dkt No.: 49880-722601106. The method of claims 104, further comprising analyzing images comprising the dataset comprising longitudinal data from one subject acquired over time to automatically detect and quantify anatomical changes over time.

107. The method of claim 106, further comprising detecting and quantifying anatomical changes over time automatically through co-regi strati ons with prior images or predefined protocols.

108. The method of any one of claim 105 to 107, further comprising determining whether the anatomical changes are of a normal or an abnormal characteristic and grading the anatomical changes if a prolapse is detected.

109. The method of any one of claims 102 to 108, further comprising employing one or more of an Al-based segmentation, classification, or regression model to assess POP via one or more of detection, grading, surveillance, or treatment recommendations.

110. The method of any one of claims 102 to 109, further comprising providing treatment recommendations based on a POP determination and grade.

111. The method of any one of claims 102 to 110, further comprising detecting early anatomical changes.

112. The method of claim 111, further comprising detecting the early anatomical changes automatically.

113. The method of any one of claims 102 to 112, further comprising monitoring progress of the POP via images of the subject acquired during a treatment, after a treatment, or a combination thereof.

114. The method of claim 113, further comprising recommending at least one alternative treatment if a predetermined treatment progress threshold is not achieved, wherein a predetermined treatment progress is determined based on the monitored progress of the POP.

115. The method of any one of claims 102 to 114, further comprising providing feedback to a user, wherein the user is different from the subject, wherein the feedback comprises a progress of a treatment, wherein the feedback is determined from analyzed changes in anatomy across multiple images.

116. The method of any one of claims 102 to 115, further comprising recommending a treatment to aid a physician in decision making.

117. The method of any one of claims 102 to 116, further comprising training a classifier model on one or more of MR images of normal anatomy, different types and grades of POP, or images of POP progressing over time from early onset to proper diagnosis.Atty Dkt No.: 49880-722601118. The method of any one of claims 102 to 117, further comprising using an Al model to perform segmentation and landmark identification on low field MRI comprising a static component or a dynamic component for grading of POP.

119. The method of any one of claims 102 to 118, further comprising using a classification model for determination of POP based on continuous distance metrics from one or more of a static low field MRI exam, a dynamic low field MRI exam, or a physical examination.

120. The method of any one of claims 102 to 119, further comprising using an Al model for visualization of longitudinal low field MRI data with a static component or a dynamic component.

121. The method of any one of claims 102 to 120, further comprising using an Al model for identification of hotspots indicating progressing prolapse or resolving prolapse.

122. The method of any one of claims 102 to 121, further comprising using a spatiotemporal model using longitudinal low field MRI data with a static component or a dynamic component for prediction of anatomical segmentation masks at a future time point.

123. The method of any one of claims 102 to 122, further comprising using a spatiotemporal model using longitudinal low field MRI data with a static component or a dynamic component for prediction of low field MRI at a future time point.

124. The method of claim 123, further comprising using a classification model and the low field MRI prediction model to compare low field MRI at the future time point and predicted low field MRI at the future time point to evaluate whether a health condition deviated from an expected trajectory.

125. The method of claim 123 or 124, further comprising using a classification model and the low field MRI prediction model to compare low field MRI at the future time point and predicted low field MRI at the future time point to evaluate whether prolapse deviated from an expected trajectory.

126. The method of any one of claims 102 to 125, further comprising using a spatiotemporal model for generating trajectory and velocity metrics from longitudinal low field MRI with a static component or a dynamic component.

127. The method of any one of claims 102 to 126, further comprising using a prognostic model for one or more of risk stratification or outcome prediction via one or more of a) trajectory and velocity metrics derived from low field MRI, b) physical examination-based metrics, c) clinical variables, or d) symptom and quality of life scores.Atty Dkt No.: 49880-722601128. The method of any one of claims 72 to 127, wherein the MRI system is configured to be rotatable 90 degrees such that the system has an imaging field of view on top of the MRI system.

129. The method of any one of claims 72 to 128, further comprising executing, via the MRI system, static and dynamic magnetic resonance (MR) imaging.

130. The method of claim 129, wherein a shape and orientation of the housing are configured to use gravity and intra-abdominal natural pressures to increase MR imaging access to the region of interest during static MR imaging.

131. The method of claim 129 or 130, wherein the static MR imaging comprises a first imaging protocol.

132. The method of claim 131, further comprising determining, via a scout scan, a position of the subject within a field of view of the MRI system.

133. The method of claim 131 or 132, wherein the first imaging protocol comprises T2-weighted fast spin echo imaging of about 24 cm to about 30 cm in the axial or coronal plane and about 30 to about 40 cm in the sagittal plane.

134. The method of claim 133, wherein the T2-weighted fast spin echo imaging comprises from about a 3 mm to about a 5 mm static slice thickness with less than about a 1 mm gap-135. The method of any one of claims 129 to 134, wherein the first imaging protocol comprises T1 fast spin echo imaging.

136. The method of any one of claims 129 to 135, wherein the first imaging protocol comprises fat saturated T1 imaging.

137. The method of any one of claims 129 to 136, wherein the first imaging protocol comprises diffusion weighted imaging.

138. The method of any one of claims 127 to 137, further comprising screening for early onset of POP and detecting one or more of cystocele tendencies, uterine / vault descent, perineal descent, or levator ballooning via the static MR imaging.

139. The method of any one of claims 127 to 138, further comprising providing an equivalent quantitative pelvic organ prolapse quantification (POP-Q) score via the dynamic MR imaging.

140. The method of any one of claims 127 to 139, wherein the dynamic MR imaging comprises a second imaging protocol.

141. The method of claim 140, wherein the second imaging protocol comprises T2 static fast spin echo imaging.Atty Dkt No.: 49880-722601142. The method of claim 140 or 141, wherein the second imaging protocol comprises T1 static fast spin echo imaging.

143. The method of any one of claims 72 to 142, further comprising executing a subject positioning protocol comprising running at least one scan.

144. The method of any one of claims 72 to 143, further comprising running at least one static scan.

145. The method of any one of claims 72 to 144, further comprising running at least one dynamic scan.

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