Relative electron density mapping from magnetic resonance imaging

Abstract

Systems, computer software, and methods for generating relative electron density maps (REDs) from magnetic resonance imaging (MRI) scans are disclosed. This may include obtaining a portion of an MRI scan of a patient and segmenting a first region and a second region in the MRI scan. The RED map may then be generated from the MRI scan by assigning the first RED to the first region, assigning the second RED to the second region, and assigning REDs to unsegmented regions in the MRI scan based on the intensity in the MRI scan.

Description

[0001] Related Applications

[0002] This application claims priority and the benefit of U.S. Provisional Application No. 63 / 417,978, filed on October 20, 2022, entitled "Relative Electron Density Mapping From Magnetic Resonance Imaging", the content of which is incorporated herein by reference. Background Art

[0003] Magnetic resonance imaging (MRI), or nuclear magnetic resonance imaging, is a non-invasive imaging technique that uses the interaction between radiofrequency pulses, a strong magnetic field (modified by applying weak gradient fields thereon to localize, encode, or decode phase and frequency), and body tissues to obtain projection, spectral signals, and planar or volumetric images from within a patient. Magnetic resonance imaging is particularly useful for soft tissue imaging and can be used for disease diagnosis and can be combined with interventional procedures (such as radiotherapy or image-guided surgery). Summary of the Invention

[0004] Systems, computer software, and methods are disclosed for generating a relative electron density map (RED) from a magnetic resonance imaging (MRI) scan. This can include obtaining an MRI scan of a portion of a patient and segmenting a first region and a second region in the MRI scan. Then, a RED map can be generated from the MRI scan by assigning a first RED to the first region, a second RED to the second region, and assigning REDs to the unsegmented regions in the MRI scan based on intensities in the MRI scan.

[0005] In some variations, the first region is cortical bone, the second region is gas, and the first region and the second region have substantially similar intensities in the MRI scan but have substantially different relative electron densities.

[0006] In some variations, assigning a first RED to the first region and a second RED to the second region can include assigning known average values corresponding to the composition of the first region and the second region, or can include assigning measured values corresponding to the composition of the first region and the second region.

[0007] In some variations, assigning REDs to the unsegmented regions can include identifying intensity ranges in the MRI scan and assigning REDs based on those intensity ranges.

[0008] In some variations, the assignment of REDs can include associating compositions with the identified intensity ranges and assigning known average values of REDs corresponding to the compositions.

[0009] In some variations, the assignment of REDs can include using REDs for components expected to be seen in an MRI scan.

[0010] In some variations, the operation can include: determining a first sub-region within a first region having intensities within a first range; determining a second sub-region within the first region having intensities within a second range; assigning a first RED corresponding to the components of the first sub-region; and assigning a third RED corresponding to the components of the second sub-region.

[0011] In some variations, the first RED and the third RED can be based on known average values of the components, the correlation between CT / MR intensities, or measurements from a CT scan.

[0012] In some variations, the determination of the first and second sub-regions can utilize thresholding techniques.

[0013] In some variations, the MRI scan can be obtained from a patient within an MRI-guided radiotherapy system, and the operation can further include: while the patient remains within the MRI-guided radiotherapy system, determining a radiotherapy treatment plan using a relative electron density map, and controlling the MRI-guided radiotherapy system to deliver therapy to the patient while the patient remains within the MRI-guided radiotherapy system.

[0014] In some variations, the relative electron density map can be generated without a CT scan, or can be generated from a single MRI scan.

[0015] In some variations, the MRI scan can be a balanced fast imaging MRI scan with steady-state free precession, or can be a T2-weighted scan.

[0016] Embodiments of the present subject matter may include, but are not limited to, methods consistent with the description provided herein and articles including tangible, machine-readable media operable to cause one or more machines (e.g., computers, etc.) to perform operations implementing one or more of the features. Similarly, computer systems are also contemplated, which may include one or more processors and one or more memories coupled to the one or more processors. The memory may include computer-readable storage media that may contain, encode, store, or otherwise process one or more programs that cause the one or more processors to perform one or more of the operations described herein. Computer-implemented methods consistent with one or more embodiments of the present subject matter may be implemented by one or more data processors residing in a single computing system or across multiple computing systems. Such multiple computing systems may be connected and may exchange data and / or commands or other instructions, etc., including but not limited to connections via a network (e.g., the Internet, wireless wide area network, local area network, wide area network, wired network, etc.), direct connections between one or more of the multiple computing systems, etc.

[0017] Details of one or more variations of the subject matter described herein are set forth in the accompanying drawings and the following description. Other features and advantages of the subject matter described herein will be apparent from the specification, the drawings, and the claims. Although certain features of the presently disclosed subject matter are shown only for particular embodiments, it should be understood that these features are not intended to limit the invention. The appended claims of the present disclosure are intended to define the scope of the protected subject matter. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The drawings are incorporated into and form a part of this specification, showing certain aspects of the subject matter disclosed herein, and together with the description, serve to explain some of the principles associated with the disclosed embodiments. In the drawings,

[0019] Figure 1 exemplary embodiments of a magnetic resonance-guided radiotherapy system (MRgRT system) that combines a magnetic resonance imaging (MRI) system and a radiotherapy source in accordance with certain aspects of the present disclosure are shown,

[0020] Figure 2A is a schematic diagram showing an MRI image indicating various anatomical regions in accordance with certain aspects of the present disclosure,

[0021] Figure 2B is a table in accordance with certain aspects of the present disclosure containing exemplary components, relative electron densities, and their display manner in MRI,

[0022] Figure 3 is a flowchart showing an exemplary process for generating a relative electron density map in accordance with certain aspects of the present disclosure,

[0023] Figure 4A is a schematic diagram showing the segmentation of regions in an MRI scan according to certain aspects of the present disclosure,

[0024] Figure 4B is a schematic diagram showing an exemplary partial RED map according to certain aspects of the present disclosure,

[0025] Figure 5A is a schematic diagram showing an exemplary process of allocating RED according to certain aspects of the present disclosure,

[0026] Figure 5B is a schematic diagram showing an exemplary process of allocating RED based at least in part on intensities within a specific range in an MRI scan, and

[0027] Figure 6 is a process flow diagram showing an exemplary process of adaptive radiotherapy using RED allocation according to certain aspects of the present disclosure. DETAILED DESCRIPTION

[0028] The present disclosure provides systems, methods, and software for creating relative electron density maps based on MRI imaging. One particular application of such mapping is the planning and delivery of MRI-guided radiotherapy. Figure 1 An embodiment of a magnetic resonance-guided radiotherapy system (MRgRT system) 100 consistent with certain aspects of the present disclosure is shown, which combines a magnetic resonance imaging system 101 and a radiotherapy source 150. In Figure 1 this, the MRI 101 includes a main electromagnet 102, a gradient coil assembly 104, and an RF coil system 106. A patient bed 108 is within the MRI 101, and a patient 110 can lie on the patient bed. Figure 1 The exemplary main electromagnet 102 shown is a solenoid electromagnet with a gap, separated by a buttress 114 to form a gap 116. Other MRI configurations can also be used, such as gapless magnets, dipole magnets, etc.

[0029] Figure 1Also depicted is a simplified exemplary radiotherapy device 150 for delivering radiotherapy. Examples of radiotherapy devices can include, for example, a linear accelerator (linac) for delivering high-energy photons (X-rays, gamma rays, etc.), a particle beam source (e.g., protons, heavy ions, neutrons, electrons, etc.), and the like. The radiotherapy device 150 can be configured to move to different positions around a patient so as to deliver radiation at various angles. For example, the radiotherapy device can be mounted on a rotatable gantry disposed between two halves of an MRI magnet such that the gantry can rotate around the patient, thereby allowing MRI imaging while delivering radiation at different gantry angles. In other embodiments, the radiotherapy device 150 can be mounted on a robotic arm or can be located at a fixed position.

[0030] The phrase “MRgRT system” as used herein refers to the hardware and / or software associated with the operation of a magnetic resonance imaging system and an associated radiotherapy device. In contrast, the more general phrase “system” as used in this disclosure encompasses any hardware and / or software required to implement the disclosed concepts related to the system. The use of the term “a / the system” encompasses a processor and / or a computer program (and, as needed, an MRgRT system) for implementing the disclosed concepts. This disclosure contemplates that its relative electron density mapping technique can be used in conjunction with an MRgRT system or can be used independently.

[0031] Figure 2A is a schematic diagram showing an exemplary MRI image marked with various anatomical regions. Magnetic resonance imaging uses the magnetization of atoms in a patient's body to generate detailed anatomical images. A magnetic field is used to align the protons of the hydrogen nuclei within the region of interest. Then, a radiofrequency (RF) energy pulse is used to excite the protons to different spin positions. When the protons relax to their initial orientation, they emit radiofrequency energy that can be detected and measured. The measured radiofrequency energy can be analyzed and used to generate an image of the anatomical region. Figure 2A An example MRI image 200 (showing the pelvic region of a patient) is shown. Certain anatomical regions in the exemplary image 200 have been marked, such as cortical bone of the femur (black), cartilage (light gray), urine (light gray), muscle (dark gray), adipose tissue (white), and gas (black).

[0032] The appearance of the components shown in an MRI image can depend on the actual components themselves and the imaging technique used. Depending on the components of the object being imaged, different tissues, air, liquids, etc. may have different relaxation times - T1 and T2. T1 (longitudinal relaxation time) is the time constant that determines the rate at which excited protons return to their initial aligned position under the influence of a magnetic field. T2 (transverse relaxation time) is the time constant that determines the rate at which excited protons reach equilibrium or become out of phase with each other. Based on the sequencing of radiofrequency pulses, different types of images can be generated. For various imaging techniques, key parameters can include the repetition time (TR), which is the amount of time between successive pulse sequences applied to the same slice. Another parameter is the echo time (TE), which is the time between the delivery of a radiofrequency pulse and the reception of the echo signal.

[0033] Given the above, MRI sequences can be T1-weighted or T2-weighted. T1-weighted images are generated using short TE and TR times. The contrast and brightness of the image are mainly determined by T1 characteristics. T2-weighted images are generated using longer TE and TR times, where the contrast and brightness are mainly determined by T2 characteristics.

[0034] Figure 2B is a table that contains exemplary anatomical regions of a patient, how they appear in MRI, and a list of approximate relative electron densities (which are crucial for exemplary applications of radiotherapy). During radiotherapy, high-energy photons are scattered by electrons in the patient's body and deposit energy along their path. The degree of photon scattering depends on the patient components (e.g., water, bone, adipose tissue, etc.) that the photons encounter, which may have different electron densities. Since scattered photons deliver radiation dose, radiotherapy planning must accurately account for this scattering. Thus, dose deposition can be determined in part based on the relative electron density (RED) of the components encountered. As described herein, RED can be mapped or assigned to regions within the patient's body to form a RED map that can be used in radiotherapy planning and / or treatment software.

[0035] When the present disclosure refers to a RED map, the term is intended to encompass additional maps of patient density metrics, such as density (g / cm 3 ), Hounsfield number maps, etc., which provide a very close approximation of the RED commonly used in radiotherapy dose calculations (e.g., the RED of urine is 1.03, where the actual mass density can also be used for planning calculations, typically 1.005 to 1.03 g / cm 3 ). Additionally, when the present disclosure uses the term "map", it refers to any data structure that details the RED over one or more regions of a patient.

[0036] As Figure 2BAs shown, regions with different compositions (e.g., air vs. bone) may have very different REDs (e.g., 0.0 vs. 1.6) - while appearing with similar intensities (i.e., both black) in the MRI image. Thus, a RED map cannot be created based solely on the correlation with MRI image intensity.

[0037] Figure 3 FIG. is a flowchart showing an exemplary process for generating a relative electron density map in accordance with certain aspects of the present disclosure. The exemplary process can utilize segmentation (or contouring) of a patient region, assignment of REDs to the segmented regions based on identification of the composition of these segmented regions, and for non-segmented regions, assignment of REDs based on MRI intensity.

[0038] As Figure 3 shown in process 300 of FIG., at 310, some embodiments may include obtaining a magnetic resonance imaging (MRI) scan of a portion of a patient, e.g., as Figure 2A shown. At 320, a first region in the MRI scan can be segmented. The first region can be a portion of the patient, composed of cortical bone, spinal cord tissue, bladder, muscle, brain tissue, etc. At 330, a second region in the MRI scan can be segmented. The second region can be an additional region, such as adipose tissue, eye fluid, cerebrospinal fluid, air bubbles, etc. (although some embodiments herein are described as segmenting multiple regions, the present disclosure contemplates that only a single region (e.g., only the first region) can be segmented).

[0039] In the case where one or more specific patient regions are segmented, at Figure 3 340 of FIG., a RED map can be generated based on the MRI scan. In some embodiments, generating the RED map can include assigning a first RED to the first region at 350, and assigning a second RED to the second region at 360. In some embodiments, the assignment of the first RED and / or the second RED can be performed by software automatically determining the composition of the region and assigning the RED to the region. In other embodiments, the assignment can be performed by software receiving a manual input of the RED from a user and assigning the RED to the region. In the case where the first region and / or the second region has been assigned a RED, some embodiments for creating the RED map may further include: at 370, based on the intensity in the MRI scan, assigning a RED to the non-segmented regions in the MRI scan. In the embodiments described in more detail herein, the assignment of REDs to the non-segmented regions can be automatically performed by computer software based on the intensity of the MRI scan in these non-segmented regions.

[0040] As used herein, "segmentation" can include manual segmentation, e.g., where software receives a manual contouring command (e.g., a command provided by a user drawing a contour using a computer interface). Segmentation can also include automatic contouring, e.g., where software automatically determines a contour, such as using edge detection or other such methods. Segmentation can also include software determining a region without explicitly forming a contour, e.g., by identifying a region based on the intensity of pixel values near a known location or region, thereby effectively determining its boundary.

[0041] Figure 4A is a schematic diagram showing segmentation of regions in an MRI scan according to certain aspects of the present disclosure. In Figure 4A exemplary MRI scan 400, the first region can be (hard) cortical bone and the second region can be gas. Although the first and second regions can have substantially similar intensities (e.g., black) in the MRI scan, they can also have substantially different relative electron densities (e.g., 1.6 and 0.0, respectively). Such regions can be referred to herein as "confounding structures" because their similar intensities in the MRI scan can confound the assignment of RED (if assigned based solely on MRI scan intensity). Although Figure 4A example depicts the segmentation of cortical bone and gas, other MRI scans may contain other "confounding structures". In another example, if the imaged region is a patient's head, the first region can be intraocular fluid and the second region can be fat - again, the first and second regions have substantially similar intensities (e.g., white) in the MRI scan, but substantially different relative electron densities (e.g., 1.03 and 0.9, respectively). Thus, in various embodiments, the first and second regions can correspond to, for example, intraocular fluid, urine, cerebrospinal fluid, adipose tissue, hard cortical bone, air bubbles, etc. The present disclosure also contemplates embodiments where more than the first and second regions are segmented. For example, Figure 4A another femur in and any other present air bubbles or other confounding structures can be contoured as a third region.

[0042] Figure 4B is a schematic diagram showing an exemplary partial RED map according to certain aspects of the present disclosure. The segmented regions can be added to the RED map 450 and appropriate RED values can be assigned to them. The present disclosure contemplates various ways of assigning RED to regions, e.g., assigning a first RED to the first region and a second RED to the second region can include assigning known averages corresponding to the components of the first and second regions. Such known averages can be obtained from a database, look-up table, etc., and can be provided by manual input or software determination. In Figure 4BIn an example, 1.6 of RED can be assigned to bone, and 0.0 of RED can be assigned to the gas region. In other embodiments, assigning a first RED to a first region and a second RED to a second region can include assigning measured values corresponding to the components of the first and second regions. Such measured values can be obtained, for example, from a CT scan of a patient and determined manually or automatically by software for assignment.

[0043] After assigning RED to each segmented region as described above (e.g., with respect to a heterogeneous structure), the RED can be further determined and assigned to the unsegmented region. This can include identifying an intensity range in an MRI scan and assigning RED based on that intensity range. For example, the intensity range of an MRI scan 400 can be from 0 (black) to 255 (white), and an intensity in the range of 20 - 40 (dark gray) can be identified as muscle and assigned a RED of 1.03. In this way, the component type can be associated with the intensity range, and then the RED value can be obtained and assigned (e.g., using a look-up table or other such data storage) to the region corresponding to that intensity range.

[0044] In some embodiments, the assignment of RED can also include using the RED of components expected to be seen at a particular MRI scan location (within the patient). For example, if the scanned region is the pelvic region, this information can be used to assign RED suitable for the components expected to be seen in the pelvic region. Conversely, if the MRI scan location is the brain, a region of dark gray brain tissue will be assigned a RED of 1.05 (instead of the RED of 1.03 for muscle for the same dark gray intensity seen in a scan of the pelvic region).

[0045] Thus, various embodiments can include a system accessing a particular table to obtain RED values for a particular MRI scan location, where the RED values are based on the components expected to be seen at such an MRI scan location.

[0046] Figure 5A and 5B are schematic diagrams showing an exemplary process for assigning RED to a bone structure.

[0047] Figure 5ASchematic diagram of an exemplary process using split allocation of RED according to certain aspects of the present disclosure. A simplified cross-section of a bone 510 is shown in the figure. Some embodiments may include splitting a first region of the bone 510 by splitting the cortical bone 520. Then, a first RED may be assigned to the first region based on known averages corresponding to the composition of the cortical bone. A second RED may be assigned to a second region, such as a bubble. And, in some embodiments, a third RED may be assigned to a region (i.e., region 530) within the split cortical bone based on known averages of the composition of cartilage. In this example, a RED of 1.6 may be assigned to the first region of the cortical bone, a RED of 0.0 may be assigned to the second region of the gas, and a RED of 1.1 may be assigned to the region within the cortical bone for cartilage. Then, the system may continue and assign REDs to the un-split regions based on the intensities of the un-split regions in the MRI scan.

[0048] Figure 5B Schematic diagram showing an exemplary process of assigning REDs based on intensities within a specific range in an MRI scan according to certain aspects of the present disclosure. In this example, splitting the first region includes splitting the outer boundary of the bone 510. Then, the system may determine a first sub-region 540 within the outer boundary of the bone 510 where the intensity is within a first range 542, and then may determine a second sub-region 550 within the bone 510 where the intensity is within a second range 552. A first RED corresponding to the cortical bone (e.g., 1.6) may be assigned to the first sub-region. A second RED may be assigned to a second region, such as a bubble. And, a third RED corresponding to cartilage (e.g., 1.1) may be assigned to the second sub-region. As mentioned above, REDs may be based on known averages of the composition, correlations between CT / MR intensities, measurements according to CT scans, etc. In some embodiments, determination of the first and second sub-regions may utilize threshold techniques.

[0049] As a general example of patient composition (different from the example of bone above), embodiments of the present disclosure may include the system determining a first sub-region within a first region where the intensity is within a first range. A second sub-region where the intensity is within a second range may be determined within the first region. A first RED may be assigned to the first sub-region, a second RED may be assigned to the second region, and a third RED may be assigned to the second sub-region. Similar to the example of bone structure above, threshold techniques may be utilized to determine the first and second sub-regions. Additionally, REDs may be based on known averages of the composition, correlations between CT / MR intensities, measurements according to CT scans, etc.

[0050] Figure 6is a process flow diagram showing an exemplary process for adaptive radiotherapy using RED map creation in accordance with certain aspects of the present disclosure. By generating a RED map while a patient is being treated in an MRIgRT system (e.g., without a separate CT scan), any of the embodiments herein can be used in conjunction with the implementation of adaptive radiotherapy. Such embodiments can include embodiments of obtaining an MRI scan of a patient within an MRI-guided radiotherapy system and operating (e.g., as referred to in Figure 3 and reproduced in Figure 6 ) also includes, at 610, determining a radiotherapy treatment plan using a relative electron density map while the patient remains within the MRI-guided radiotherapy system. Additionally, at 620, the system can control the MRI-guided radiotherapy system to deliver therapy to the patient while the patient remains within the MRI-guided radiotherapy system. Thus, in certain embodiments, a RED map can be generated without a CT scan and can be generated by a single MRI scan.

[0051] A variety of different types of MRI pulse sequences can be implemented, but in one embodiment, the MRI scan can be a T2-weighted scan. In other embodiments, the MRI scan can be a balanced fast imaging MRI scan with steady-state free precession, where the pulse sequence can be balanced such that the gradients can return the nuclei to the same phase they had before the gradients were applied. These embodiments can be used, for example, to clearly display fluids such as cerebrospinal fluid.

[0052] Next, further features, characteristics, and exemplary technical solutions of the present disclosure will be described in the form of items that can optionally be claimed in any combination:

[0053] Item 1: A system, comprising: at least one programmable processor; and a non-transitory machine-readable medium storing instructions that, when executed by the at least one programmable processor, cause the at least one programmable processor to perform operations, the operations including: obtaining a magnetic resonance imaging (MRI) scan of a portion of a patient; segmenting a first region in the MRI scan; segmenting a second region in the MRI scan; and generating a relative electron density (RED) map based on the MRI scan, the generating including: assigning a first RED to the first region; assigning a second RED to the second region; and assigning REDs to unsegmented regions in the MRI scan based on intensities in the MRI scan.

[0054] Item 2: The system of Item 1, wherein the first region is cortical bone, the second region is gas, and the first region and the second region have substantially similar intensities and substantially different relative electron densities in the MRI scan.

[0055] Item 3: The system according to any one of the foregoing, wherein the first region is the ocular fluid, the second region is adipose tissue, and the first region and the second region have substantially similar intensities and substantially different relative electron densities in the MRI scan.

[0056] Item 4: The system according to any one of the foregoing items, wherein the first region and the second region correspond to ocular fluid, urine, cerebrospinal fluid, adipose tissue, cortical bone, or air bubbles.

[0057] Item 5: The system according to any one of the foregoing items, wherein assigning the first RED to the first region and the second RED to the second region further includes assigning known averages corresponding to the components of the first region and the second region.

[0058] Item 6: The system according to any one of the foregoing items, wherein assigning the first RED to the first region and the second RED to the second region further includes assigning measured values corresponding to the components of the first region and the second region.

[0059] Item 7: The system according to any one of the foregoing items, wherein assigning the RED to the unsegmented region further includes: identifying an intensity range in the MRI scan; and assigning the RED based on the intensity range.

[0060] Item 8: The system according to any one of the foregoing items, wherein the assignment of the RED further includes: associating a component with the identified intensity range; and assigning a known average of the RED corresponding to the component.

[0061] Item 9: The system according to any one of the foregoing items, wherein the assignment of the RED further includes: using the RED of a component expected to be seen in the MRI scan.

[0062] Item 10: The system according to any one of the foregoing items, wherein segmenting the first region includes segmenting cortical bone, and assigning the first RED to the first region includes assigning the first RED based on a known average corresponding to the component of the cortical bone; and the operation further includes assigning a third RED to a region within the segmented cortical bone based on a known average of the component of cartilage.

[0063] Item 11: The system according to any one of the preceding items, wherein dividing the first region includes dividing the outer boundary of the bone; the operation further includes: determining a first sub-region within the outer boundary of the bone having an intensity within a first range; determining a second sub-region within the outer boundary of the bone having an intensity within a second range; assigning a first RED corresponding to cortical bone to the first sub-region; and assigning a third RED corresponding to cartilage to the second sub-region.

[0064] Item 12: The system according to any one of the preceding items, wherein the first RED and the third RED are based on known average values of the composition, the correlation between CT / MR intensities, or measurements from a CT scan.

[0065] Item 13: The system according to any one of the preceding items, wherein the determination of the first sub-region and the second sub-region utilizes threshold techniques.

[0066] Item 14: The system according to any one of the preceding items, the operation further includes: determining a first sub-region within the first region having an intensity within a first range; determining a second sub-region within the first region having an intensity within a second range; assigning a first RED corresponding to the composition of the first sub-region; and assigning a third RED corresponding to the composition of the second sub-region.

[0067] Item 15: The system according to any one of the preceding items, wherein the first RED and the third RED are based on known average values of the composition, the correlation between CT / MR intensities, or measurements from a CT scan.

[0068] Item 16: The system according to any one of the preceding items, wherein the determination of the first sub-region and the second sub-region utilizes threshold techniques.

[0069] Item 17: The system according to any one of the preceding items, wherein the MRI scan is obtained from a patient within an MRI-guided radiotherapy system, and the operation further includes: using the relative electron density map to determine a radiotherapy treatment plan while the patient remains within the MRI-guided radiotherapy system; and controlling the MRI-guided radiotherapy system to deliver therapy to the patient while the patient remains within the MRI-guided radiotherapy system.

[0070] Item 18: The system according to any one of the preceding items, wherein the relative electron density map is generated without performing a CT scan.

[0071] Item 19: The system according to any one of the preceding items, wherein the relative electron density map is generated from a single MRI scan.

[0072] Item 20: The system as described in any of the foregoing, wherein the MRI scan is a balanced fast imaging MRI scan with steady state free precession.

[0073] Item 21: The system as described in any of the foregoing, wherein the MRI scan is a T2 weighted scan.

[0074] The present disclosure anticipates that the computations disclosed in the embodiments herein can be performed in a variety of ways applying the same concepts taught herein, and such computations are equivalent to the disclosed embodiments.

[0075] One or more aspects or features of the subject matter described herein can be implemented in digital electronic circuitry, integrated circuitry, specially designed application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), computer hardware, firmware, software, and / or combinations thereof. These different aspects or features can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, a storage system, at least one input device, and at least one output device, the programmable processor may be special or general purpose, coupled to receive data and instructions from, and to send data and instructions to, the programmable processor. The programmable system or computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. The relationship of client and server arises by virtue of computer programs running on respective computers and having a client-server relationship to each other.

[0076] These computer programs may also be referred to as programs, software, software applications, applications, components, or code, including machine instructions for a programmable processor, and can be implemented in a high-level procedural language, an object-oriented programming language, a functional programming language, a logical programming language, and / or assembly / machine language. As used herein, the term "machine-readable medium" (or "computer-readable medium") refers to any computer program product, apparatus, and / or device, such as a magnetic disk, optical disk, memory, and programmable logic device (PLD), for providing machine instructions and / or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" (or "computer-readable signal") refers to any signal for providing machine instructions and / or data to a programmable processor. The machine-readable medium can non-transitorily store such machine instructions, such as, for example, non-transitory solid state memory or a magnetic hard disk drive or any equivalent storage medium. The machine-readable medium can alternatively or additionally store such machine instructions in transient fashion, such as, for example, in a processor cache or other random access memory associated with one or more physical processor cores.

[0077] To provide for interaction with a user, one or more aspects or features of the subject matter described herein can be implemented on a computer having a display device such as, for example, a cathode ray tube (CRT), liquid crystal display (LCD), or light emitting diode (LED) monitor for displaying information to the user and a keyboard and a pointing device such as, for example, a mouse or a trackball by which the user can provide input to the computer. Other types of devices can also be used to provide for interaction with the user. For example, the feedback provided to the user can be any form of sensory feedback such as visual feedback, auditory feedback, or tactile feedback; and the input received from the user can be in any form including, but not limited to, acoustic, speech, or tactile input. Other possible input devices include, but are not limited to, touchscreens or other touch-sensitive devices such as single-point or multi-point resistive or capacitive touchpads, speech recognition hardware and software, optical scanners, optical pointers, digital image capture devices and associated interpretation software, and the like.

[0078] In the foregoing description and claims, phrases such as "at least one" or "one or more" can occur after a list of elements or features. The term "and / or" can also occur in a list of two or more elements or features. Such phrases are intended to mean any of the listed elements or features individually or any combination of any of the listed elements or features in combination with any other listed element or feature, unless contextually implied or explicitly contradicted by the context in which it is used. For example, the phrases "at least one of A and B;" "one or more of A and B;" "A and / or B" each mean "A alone, B alone, or A and B together." Similar interpretations apply to lists containing three or more items. For example, the phrases "at least one of A, B, and C;" "one or more of A, B, and C;" "A, B, and / or C" each mean "A alone, B alone, C alone, A and B together, A and C together, B and C together, or A and B and C together." The term "based on" as used above and in the claims is intended to mean "at least partially based on" such that features or elements not recited are also permissible.

[0079] Depending on the desired configuration, the subject matter described herein may be embodied in a system, apparatus, method, computer program, and / or article. Any method or logical flow depicted in the figures and / or described herein need not be in the particular order or sequential order shown to achieve the desired result. The embodiments set forth in the foregoing description do not represent all embodiments consistent with the subject matter described herein. Instead, they are only some examples consistent with aspects related to the described subject matter. Although some variations have been described in detail above, other modifications or additions are possible. In particular, additional features and / or variations may be provided in addition to the features and / or variations set forth herein. The foregoing embodiments may be directed to various combinations and sub-combinations of the disclosed features and / or combinations and sub-combinations of the other features described above. Moreover, the foregoing advantages are not intended to limit the application of any of the issued claims to processes and structures that achieve any or all of such advantages.

[0080] In addition, chapter headings should not limit or characterize the invention set forth in any claims that may be derived from the present disclosure. Further, the technical descriptions in the "Background" should not be construed as an admission that the technology is prior art to any invention in the present disclosure. The "Summary" should also not be regarded as a characterization of the invention set forth in the issued claims. Moreover, any general reference to the present disclosure or use of the singular term "invention" is not intended to imply any limitation on the scope of the claims presented below. Multiple inventions may be set forth by the limitations of multiple claims issued in accordance with the present disclosure, and these claims accordingly define the (one or more) inventions protected thereby and their equivalents.

Claims

1. A system, comprising: at least one programmable processor; and a non - transitory machine - readable medium storing instructions that, when executed by the at least one programmable processor, cause the at least one programmable processor to perform operations, the operations including: obtaining a magnetic resonance imaging (MRI) scan of a portion of a patient; segmenting a first region in the MRI scan; segmenting a second region in the MRI scan; and generating a relative electron density (RED) map based on the MRI scan, the generating including: assigning a first RED to the first region; assigning a second RED to the second region; and assigning REDs to the un - segmented regions in the MRI scan based on intensities in the MRI scan.

2. The system according to claim 1, wherein, the first region is cortical bone, the second region is gas, and the first region and the second region have substantially similar intensities and substantially different relative electron densities in the MRI scan.

3. The system according to claim 1, wherein, the first region is ocular fluid, the second region is adipose tissue, and the first region and the second region have substantially similar intensities and substantially different relative electron densities in the MRI scan.

4. The system according to claim 1, wherein, the first region and the second region correspond to ocular fluid, urine, cerebrospinal fluid, adipose tissue, hard cortical bone, or air bubbles.

5. In the system according to claim 1, assigning the first RED to the first region and assigning the second RED to the second region further includes assigning known averages corresponding to the compositions of the first region and the second region.

6. In the system according to claim 1, assigning the first RED to the first region and assigning the second RED to the second region further includes assigning measured values corresponding to the compositions of the first region and the second region.

7. The system according to claim 1, wherein, assigning REDs to the un - segmented regions further includes: identifying intensity ranges in the MRI scan; and assigning REDs based on the intensity ranges.

8. The system according to claim 7, wherein, the assignment of REDs further includes: associating a composition with the identified intensity range; and assigning a known average of the RED corresponding to the composition.

9. The system according to claim 7, wherein, the assignment of REDs further includes: utilizing the REDs of the components expected to be seen in the MRI scan.

10. The system according to claim 1, wherein, segmenting the first region includes segmenting cortical bone, and assigning the first RED to the first region includes assigning the first RED based on a known average corresponding to the composition of cortical bone; and the operations further include assigning a third RED to a region within the segmented cortical bone based on a known average of the composition of cartilage.

11. The system according to claim 1, wherein, segmenting the first region includes segmenting the outer boundary of bone; the operations further include: Determine a first sub-region within the outer boundary of the bone where the strength is within a first range; Determine a second sub-region within the outer boundary of the bone where the strength is within a second range; Assign a first RED corresponding to cortical bone to the first sub-region; and Assign a third RED corresponding to cartilage to the second sub-region.

12. The system according to claim 11, wherein, the first RED and the third RED are based on known average values of the composition, the correlation between CT / MR intensities, or measurements according to CT scans.

13. The system according to claim 11, wherein, the determination of the first sub-region and the second sub-region utilizes threshold techniques.

14. The system according to claim 1, the operation further comprises: Determine a first sub-region within the first region where the strength is within a first range; Determine a second sub-region within the first region where the strength is within a second range; Assign a first RED corresponding to the composition of the first sub-region; and Assign a third RED corresponding to the composition of the second sub-region.

15. The system according to claim 14, wherein, the first RED and the third RED are based on known average values of the composition, the correlation between CT / MR intensities, or measurements according to CT scans.

16. The system according to claim 14, wherein, the determination of the first sub-region and the second sub-region utilizes threshold techniques.

17. The system according to claim 1, wherein, the MRI scan is obtained from a patient within an MRI-guided radiotherapy system, and the operation further comprises: When the patient remains within the MRI-guided radiotherapy system, utilize the relative electron density map to determine a radiotherapy treatment plan; and Control the MRI-guided radiotherapy system to deliver therapy to the patient when the patient remains within the MRI-guided radiotherapy system.

18. The system according to claim 1, wherein, the relative electron density map is generated without performing a CT scan.

19. The system according to claim 1, wherein, the relative electron density map is generated from a single MRI scan.

20. The system according to claim 1, wherein, the MRI scan is a balanced fast imaging MRI scan with steady-state free precession.

21. The system according to claim 1, wherein, the MRI scan is a T2-weighted scan.

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