Systems and methods for evaluating fluid and air flows - Patents.com

Abstract

Systems and methods are disclosed for determining the cross-sectional area of ​​a fluid or air passageway in an anatomical structure. In some examples, the method may include generating a model of the structure based on multiple images of the structure, the structure including at least one fluid or air flow path. In some examples, the method may also include identifying occlusion elements in the model of the structure, the occlusion elements affecting at least one fluid or air flow path in the model. In some examples, the method may also include determining an area of ​​the at least one fluid or air flow path for flow analysis.

Description

Detailed Description of the Invention

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This application claims priority to U.S. Provisional Patent Application No. 62 / 905,814, filed September 25, 2019, the contents of which are incorporated herein by reference in their entirety.

[0002] 〔background〕 [Technical field] This application relates to the assessment of fluid and / or air flow through anatomical structures in a patient's anatomy. In some embodiments, this application specifically relates to determining the degree of obstruction in fluid or air passages in anatomical structures, such as valves, arteries, veins, tubes, airways, etc.

[0003] Description of Related Art For many cardiac, cardiovascular, and / or respiratory conditions, the incorporation of prosthetic devices into the patient's anatomy has become a common treatment option. However, the presence of such devices in parts of the heart, blood vessels, or airways may impede or partially or completely prevent the natural flow of blood or air. For example, in procedures such as transcatheter mitral valve replacement (TMVR), mitral valve-in-valve (ViV), mitral valve-in-ring (ViR), and valve-in-MAC (ViMAC) procedures, obstruction of the left ventricular outflow tract (LVOT) is a potentially fatal complication.

[0004] For example, TMVR, ViV, ViR, and calcified mitral valve procedures can result in elongation of the LVOT. This elongation is limited by a curved anterior mitral leaflet, curved biological leaflets, and / or transcatheter heart valve struts. That is, the incorporation of the prosthesis may cause the anterior mitral leaflet to curve and hold it open, thereby at least partially obstructing the natural flow of blood from the LVOT.

[0005] A pre-treatment evaluation of the patient may be performed to estimate whether and to what extent the prosthesis will impede the natural flow of blood or air in the patient. For example, a pre-treatment evaluation of possible blockage of blood flow from the LVOT may be performed using two-dimensional (2D) cardiac computed tomography (CT) images. Using the CT images, measurements can be made at the cross-section of the LVOT to determine the minimum cross-section of the LVOT region.

[0006] However, this procedure has several drawbacks. For example, 2D CT images are limited to a cross-section of any anatomical region of interest. For example, the LVOT region may contain irregularities of shape and size that cannot be seen in 2D CT images. Thus, the irregular shape of the LVOT that is not shown in the 2D CT images reduces the quality of the pre-procedure assessment. Furthermore, this procedure is performed manually, leaving room for inter- and intra-user variability and error. For example, due to the complex three-dimensional shape of the heart, manually determining the LVOT and the degree of possible obstruction of the LVOT is not a simple task.

[0007] Summary of the Invention Certain aspects relate to a method for evaluating fluid flow. The method includes generating a model of a structure based on a plurality of images of the structure, the structure including at least one fluid flow path. The method may also include identifying occlusion elements in the model of the structure, the occlusion elements affecting the at least one fluid flow path in the model. The method may also include determining an area of ​​the at least one fluid flow path for flow analysis. The flow analysis includes defining a guide curve along at least a portion of the at least one fluid flow path. The fluid analysis also includes defining a plurality of planes along the guide curve, each of the plurality of planes being orthogonal to the guide curve and intersecting the region to define at least a portion of a plurality of cross-sections of the region. The fluid analysis also includes determining which one of the plurality of cross-sections has a minimum surface area. The fluid analysis also includes displaying a magnitude of the minimum surface area.

[0008] Certain aspects relate to an apparatus for evaluating fluid flow. The apparatus includes a memory and a processor communicatively coupled to the memory. The processor and memory are configured to generate a model of a structure based on a plurality of images of the structure, the structure including at least one fluid flow path. The processor and memory are configured to identify occlusion elements in the model of the structure, the occlusion elements affecting the at least one fluid flow path in the model. The processor and memory are configured to determine a region of the at least one fluid flow path for flow analysis. The flow analysis includes defining a guide curve along at least a portion of the at least one fluid flow path. The flow analysis includes defining a plurality of planes along the guide curve, each of the plurality of planes being orthogonal to the guide curve and intersecting the region to define at least some of a plurality of cross-sections of the region. The flow analysis includes determining which one of the plurality of cross-sections has a minimum surface area. The flow analysis includes displaying a size of the minimum surface area.

[0009] Certain aspects relate to a non-transitory computer-readable medium storing instructions that, when executed by a processor of an apparatus, cause the apparatus to perform a method for evaluating fluid flow. The method includes generating a model of a structure based on a plurality of images of the structure, the structure including at least one fluid flow path. The method includes identifying occlusion elements in the model of the structure, the occlusion elements affecting at least one fluid flow path in the model. The method includes determining a region of the at least one fluid flow path for flow analysis. The flow analysis includes defining a guide curve along at least a portion of the at least one fluid flow path. The flow analysis includes defining a plurality of planes along the guide curve, each of the plurality of planes being orthogonal to the guide curve and intersecting the region to define at least some of a plurality of cross-sections of the region. The flow analysis includes determining which one of the plurality of cross-sections has a minimum surface area. The flow analysis includes displaying a size of the minimum surface area.

[0010] BRIEF DESCRIPTION OF THE DRAWINGS 1 and 2 are diagrams showing cross-sections of the heart.

[0011] FIG. 3 is an example of a suitable computing environment for implementing certain embodiments described herein.

[0012] FIG. 4 is an example of a computing device suitable for implementing various embodiments.

[0013] FIG. 5 is an example of a two-dimensional (2D) computed tomography (CT) image of a patient's heart.

[0014] FIG. 6 is an example of a combination of multiple orthogonal 2D images used to generate a three-dimensional (3D) model of a patient's heart.

[0015] FIG. 7 is a cross-sectional view of a structure of interest from the 3D model of FIG.

[0016] FIG. 8 is a cross-sectional view of a structure of interest from the 3D model of FIG.

[0017] FIG. 9 is a cross-sectional view of a structure of interest from the 3D model of FIG.

[0018] FIG. 10 is a cross-sectional view of a 2D CT image of one embodiment of a patient's heart.

[0019] FIG. 11 is a cross-sectional view of a structure of interest from the 3D model of FIG.

[0020] FIG. 12 is a diagram illustrating a conceptual guide curve having a number of planes defined perpendicular to the guide curve.

[0021] FIG. 13 is a diagram illustrating a conceptual guide curve having a first plane among a plurality of planes.

[0022] FIG. 14 is a diagram showing a conceptual guide curve obtained by rotating a first plane among a plurality of planes.

[0023] 15 and 16 are example graphs showing cross-sectional areas along centerlines or guide curves of fluid or air passages.

[0024] FIG. 17 is a flow diagram illustrating a process for creating multiple cross sections, in accordance with certain embodiments.

[0025] DETAILED DESCRIPTION OF EMBODIMENTS OF THE PRESENTINVENTION As mentioned above, the incorporation of a prosthesis into the patient's anatomy may cause blockage of blood and / or air passages. In one example, a prosthetic mitral valve may cause blockage of the left ventricular outflow tract (LVOT), thereby reducing blood flow from the heart toward the aorta. Here, a prosthetic mitral valve, such as a transcatheter mitral valve replacement (TMVR), may change the size and shape of the original LVOT into a modified LVOT. For example, the LVOT may be stretched into the left ventricle (this stretching is referred to herein as "neo-LVOT"). The neo-LVOT may have a reduced cross-sectional area compared to the original LVOT due to the protrusion of the prosthetic mitral valve into the LVOT.

[0026] The amount of fluid (e.g., blood) or air flow through a volume (e.g., valve, vein, artery, LVOT, neo-LVOT, airway, etc.) can be directly related to the minimum cross-sectional area in the volume through which the fluid or air can flow. This is because the minimum cross-sectional area can act as an obstacle to flow through the volume. Therefore, the blood flow through the modified LVOT can be directly related to the minimum cross-sectional area of ​​the neo-LVOT.

[0027] Sufficient blood flow through the modified LVOT is important to ensure the survival rate of the patient after the insertion of a prosthetic mitral valve. Without sufficient blood flow, the patient may experience complications, which may even lead to death. Thus, a reliable pre-procedure evaluation of the neo-LVOT region helps to reduce the chance of complications in mitral valve replacement by helping to demonstrate blood flow through the neo-LVOT before mitral valve replacement. Many of the examples discussed herein relate to pre-procedure evaluations for replacing a patient's mitral valve with a prosthesis. However, it should be noted that the techniques described herein are also applicable to pre-procedure evaluations performed before any other suitable procedures, such as other cardiac procedures, cardiovascular procedures, or pulmonary procedures, in which the flow of fluids (e.g., blood), air, or another gas or liquid may be partially or completely obstructed. Furthermore, the disclosed techniques may be applied with equal force to the evaluation of the effects of non-medically introduced phenomena on fluid and air flow, such as stenosis, blood clots, tumors, etc.

[0028] FIG. 1 illustrates a cross-sectional view of an embodiment of a cardiac structure 100. Specifically, the aorta 103, left ventricle 101, and left atrium 102 of the heart 100 are shown. The cardiac structure further includes an aortic valve 105, a left ventricular outflow tract (LVOT) 106a, an intervalvular fibrosa 108, a mitral valve 104a, an anterior mitral valve leaflet (AML) 109, and an interventricular septum (IVS) 110. FIG. 2 illustrates a cross-sectional view of another embodiment of a cardiac structure 150. In this example, the cardiac structure 150 includes a prosthetic mitral valve 104b. When the mitral valve 104b is placed in the heart 150, the AML 109 curves. The curved AML 109, together with the anatomy of the IVS 110, defines the neo-LVOT 106b. Optionally, if the user determines that additional measurements are needed, another neo-LVOT region 106c can be added.

[0029] In some methods, the neo-LVOT area is visually estimated by the user by first placing a schematic of the prosthetic valve 104b in one or more 2D images and drawing a 2D curve along an estimate of the centerline of the modified LVOT (i.e., a combination of the original LVOT 106a, the neo-LVOT 106b, and optionally another neo-LVOT area 106c) on one or more 2D images. The sidewall of the prosthetic valve 104b is often assumed to represent the shape of the curved AML 109. Drawing this pseudo-centerline may be done manually by the user and is prone to errors due to inaccurate visual estimation. The user can then draw a plane perpendicular to the pseudo-centerline. The user can manually select the location of the plane that visually appears to be a small cross-section. The distance along this plane from the intervalvular fibers 108, the curved AML 109, or the sidewall of the prosthetic valve 104b to the wall of the IVS 110 is then calculated and used as an estimate of the minimum neo-LVOT area. Thus, such an assessment of the neo-LVOT 106b may be crude and may not result in an accurate determination of the minimum neo-LVOT area. For example, depending on the user making the estimation and the selection of the 2D image on which the estimation is based, multiple visual estimates of the minimum neo-LVOT area for the same heart 100 with the same prosthetic mitral valve 104b placed in the same position may vary significantly. Inaccurate estimations may lead to improper selection and placement of the prosthetic mitral valve 104b in the patient's heart, which may result in complications or even death.

[0030] Unlike such methods, certain embodiments of the systems and methods described herein provide a robust and accurate determination of the degree of obstruction in a fluid or air passageway of a patient's anatomical structure. That is, certain embodiments of the systems and methods described herein improve the art of medicine and medical technology by efficiently and accurately calculating the minimum cross-sectional area of ​​an anatomical region so that an appropriate prosthesis may be selected and placed in the patient's anatomy such that the prosthesis does not obstruct or reduce proper blood and / or air flow through the anatomical region.

[0031] In one example, calculating the minimum cross-sectional area of ​​the anatomical region may include calculating one or more of the LVOT 106a and the neo-LVOT 106b / 106c. Based on these calculations, a suitable prosthetic mitral valve 104b can be selected and placed in the patient's anatomy while maintaining adequate blood flow through the neo-LVOT 106b / 106c. Such techniques improve the art of medicine and medical technology by reducing the chance of patient complications due to improper neo-LVOT 106b / 106c calculations and placement and selection / design of the prosthetic mitral valve 104b. Such techniques further improve the capabilities of the computing device itself used to calculate the minimum neo-LVOT region 106b / 106c by providing an efficient and defined computing system that efficiently finds the minimum cross-sectional area in a volume.

[0032] The systems and methods described herein can be implemented in a computing environment that includes one or more computing devices configured to provide various functions. FIG. 3 is an example of a computing environment 300 suitable for implementing certain embodiments described herein. The computing environment 300 can include a network 302. The network 302 can take various forms. For example, the network 302 can be a local area network (LAN) located at the surgical site. In an embodiment, the network 302 can be a wide area network (WAN) such as the Internet. In other embodiments, the network 302 can be a combination of a LAN and a WAN. Typically, the network 302 allows secure communications and data to be shared between various computing devices. Among these computing devices are client devices 304. The client devices 304 can be typical personal computing devices running off-the-shelf operating systems such as Windows, Mac OS, Linux, Chrome OS, or any other operating system. The client devices 304 can have application software installed to allow them to interact with various other modules in the computing environment 300 and other software stored on the devices via the network 302. This application software may take the form of a web browser capable of accessing a remote application service. Alternatively, the application software may be a client application installed on the operating system of the client device 304. The client device 304 may also take the form of a special purpose computer specifically designed for medical imaging tasks (e.g., a special purpose computer integrated into a medical imaging instrument or a control system of a medical imaging instrument), or more specifically for the determination of the neo-LVOT region 106b / 106c.The client device 304 may further take the form of a mobile device or tablet computer configured to communicate over the network 302 and configured to execute one or more software modules for enabling a user to perform the various methods described herein.

[0033] The computing environment 300 may further include an image data storage 306. Typically, the image data storage 306 takes the form of a large database designed to store image files captured by a scanning device 322. These images may be part of a Digital Imaging and Communications in Medicine (DICOM) Management System and may include 2D images (e.g., CT images), 3D images (e.g., images constructed from multiple views of a 2D image), and / or 4D images. The image data storage 306 may be part of the scanning device 322 or may be part of the client computing device 304. The image data storage 306 may be in a stand-alone database or in a server-based system such as a Picture Archiving and Communication System (PACS) having dedicated storage optimized for medical image data. The computing environment 300 may also include a scanning device 322. The scanning device 322 may be a medical imaging device that typically scans a patient to generate images of the patient's anatomy. In the computing environment 300 shown in FIG. 3, the scanning device 322 may be a CT scanner or a magnetic resonance imaging (MRI) device. However, those skilled in the art will appreciate that other suitable scanning techniques may be implemented that provide imaging data that can be used to generate a three-dimensional anatomical model.

[0034] As described in more detail below, the scanning device 322 may be configured to generate cross-sectional images of a fluid or air passageway (e.g., an anatomical structure) such as a patient's heart or airways. These images may be stored in the image data storage 306 and utilized to create a three-dimensional model of the fluid or air passageway. To that end, the computing environment 300 may also include an image processing module 308. The image processing modules 308 may take the form of computer software, hardware, or a combination of both. They retrieve medical imaging data from the image data storage 306 and use stacks of 2D image data to generate three-dimensional models, such as 3D surface models (e.g., 3D triangle models). The image processing modules 308 may be commercially available image processing software for three-dimensional design and modeling, such as the Mimics application provided by Materialise NV. However, other image processing software may be used. In an embodiment, the image processing module 308 may be provided via a web-based network application. The web-based network application is accessed by a computer via a network (e.g., the client device 304, etc.). Alternatively, the image processing module 308 may be a software application that is installed directly on the client device 304 and accesses the image data storage 306 over the network 302. In general, the image processing module 308 may be any combination of software and / or hardware located within the computing environment 300 that provides image processing capabilities on image data stored in the image data storage 306.

[0035] The computing environment may also include a 3D measurement and analysis module 320. The 3D measurement and analysis module 320 may be software complementary and / or integrated with the image processing module 308. The 3D measurement and analysis module 320 may include an application configured to determine / estimate a minimum cross-section of a fluid passageway, such as the neo-LVOT 106b / 106c. As described in more detail below, the 3D measurement and analysis module 320 may generally be used to determine accurate measurements of various aspects of a fluid or air passageway (e.g., a patient's anatomy) and simulated positioning of features within the passageway (e.g., an occlusion, a stenosis, an implant such as a prosthetic mitral valve 104b, etc.) to determine a minimum cross-section of a fluid or air passageway, such as the neo-LVOT 106b / 106c. Similar to the image processing module 308, the 3D measurement and analysis module 320 may be a network-based application accessed via a web browser by one or more client devices 304. It may also be a native application installed on the operating system of a computer, such as, for example, the client device 304. In yet other embodiments, the 3D measurement and analysis module 320 may be a network application executed as a client / server implementation. In certain embodiments, the 3D measurement and analysis module 320 may operate on a 3D model generated by the image processing module 308. Alternatively or additionally, the 3D measurement and analysis module 320 may operate on image data, for example, from the image data storage 306. Performing measurements on the image data may, in certain embodiments, eliminate the step of generating a three-dimensional model. However, performing measurements on the 3D model may produce more accurate results because features such as centerlines and cross sections of anatomical structures may be more accurately determined and the deleterious effects of noise or other artifacts in the image data may be reduced.

[0036] Various embodiments may be implemented using general and / or special purpose computing devices. Referring now to FIG. 4, an example of a computing device 400 suitable for implementing various embodiments is shown. The computer system 400 may generally take the form of computer hardware configured to execute certain processes and instructions in accordance with various aspects of one or more embodiments described herein. The computer hardware may be a single computer or multiple computers configured to cooperate. The computing device 400 includes a processor 403. The processor 403 may be one or more standard personal computer processors, such as those designed and / or distributed by Intel, Advanced Micro Devices, Apple, or ARM. The processor 403 may also be a more specialized processor specifically designed for processing and / or analyzing images. The computing device 400 may also include a display 404. The display 404 may be a standard computer monitor, such as a well-known LCD monitor. The display 404 may also take the form of a display integrated into the body of the computing device, as in, for example, an all-in-one computing device or a tablet computer.

[0037] The computing device 400 may also include input / output devices 406. These may include standard peripherals such as a keyboard, mouse, printer, and other basic I / O software and hardware. The computing device 400 may further include memory 408. The memory 408 may take a variety of forms. For example, the memory 408 may include volatile memory 410. The volatile memory 410 may be some form of random access memory, and may typically be configured to allow executable software modules to be loaded into the memory so that they can be executed by the processor 403 in a manner well known in the art. The software modules may be stored in non-volatile memory 413. The non-volatile memory 413 may take the form of a hard disk drive, flash memory, solid state hard drive, or some other form of non-volatile memory. The non-volatile memory 413 may also be used to store non-executable data, such as database files. In some examples, the computing device 400 may include a non-transitory computer readable medium having stored thereon code for performing the techniques and methods described herein.

[0038] The computing device 400 may also include a network interface 414. The network interface may take the form of a network interface card and its corresponding software drivers and / or firmware configured to provide the system 400 with access to a network (e.g., the Internet, etc.). The network interface card 414 may be configured to access various types of networks, such as those described above in connection with FIG. 3. For example, the network interface card 414 may be configured to access a private network that is not publicly accessible. The network interface card 414 may also be configured to access a wireless network using a wireless data transfer technology, such as an EVDO, WiMax, or LTE network. Although a single network interface 414 is shown in FIG. 4, there may be multiple network interface cards 414 to access different types of networks. Furthermore, a single network interface card 414 may be configured to enable access to multiple different types of networks.

[0039] In general, the computing environment 300 shown in Figure 3 may generally include one, several, or many different types of computing devices 400 that cooperate to perform various embodiments described below. For example, the image data storage 306 may be part of a server-based system, such as a PACS system, and may be accessible to the image processing module 308 and / or the 3D measurement and analysis module 320 via a network interface 414. Those skilled in the art will readily appreciate that a variety of different types of computing devices and network configurations may be implemented to perform the inventive systems and methods disclosed herein.

[0040] (Data Acquisition) In certain embodiments, a user, such as a clinician, engineer, technician, etc., can use a computing device to obtain data. The data can include one or more images of a region of the fluid or air passageway (e.g., a patient's anatomy) to be evaluated. The images can include any suitable (e.g., medical) images for viewing the fluid or air passageway (e.g., a computed tomography (CT) scan, etc.). The images can be contrast-enhanced images, such as angiographic images. In some examples, the images can be two-dimensional (2D), three-dimensional (3D), or four-dimensional (4D) images. A 4D image can cover a particular duration, such as an entire cardiac cycle or a partial cardiac cycle. A 2D or 3D image can include an instantaneous snapshot of the fluid or air passageway (e.g., an end-systolic anatomy of a cardiac structure).

[0041] In some examples, the computing device 400 may be used to display an image such that a structure of interest (e.g., a patient's anatomy) can be visualized. For example, in the case of TMVR, the structure of interest may be the heart, the left ventricle of the heart (e.g., the left ventricle 101 in FIG. 1 ) (possibly including the mitral and aortic valves (e.g., the mitral valve 104a and the aortic valve 105 in FIG. 1 )), or the left side of the heart. In some examples, the computing device 400 may be used to create a virtual 3D model of the structure of interest. For example, based on the CT image, a 3D surface model may be created from the blood pool volume of the heart or a portion thereof (e.g., the left side of the heart or the left ventricle), from any calcifications, from other parts of the anatomy, and / or from any prosthetic devices already present in the patient. Such a 3D surface model may be created by segmenting the CT image. In other examples, the visualization of the structure of interest may include one or more 2D (e.g., medical) images, multiplanar reconstruction (MPR) images, or volume-rendered (e.g., medical) images. In some examples, the visualization of the structure of interest may include display of any combination of 2D, 3D, or 4D images.

[0042] FIG. 5 is a 2D CT image of an example of a patient's heart 502. As described above, multiple 2D images may be captured of the patient's heart 502 from different perspectives or at different positions to generate a 3D model of the heart 502 or a portion thereof. For example, FIG. 6 is an example of a combination of multiple orthogonal 2D images used to generate a 3D model 602 of a structure of interest, such as the patient's heart 502 or a portion of the patient's heart. In this example, the image processing module of FIG. 3 may be used to retrieve images from the image data store 306, combine the 2D images, and generate the 3D model 602. In one example, the structure of interest includes the left ventricle 101, the mitral valve 104a, and the aortic valve 105. Thus, the 3D model 602 includes models of these elements of the patient's heart 502.

[0043] 7 is a cross-sectional view of the structure of interest 711 from the 3D model 602 of FIG. 6. In some examples, once the 3D model 602 is created, the image processing module 308 may be utilized to generate one or more cross-sectional views of the structure of interest. In this example, the image processing module 308 uses a cutout along a plane perpendicular to the mitral valve 704 and the aortic valve 705 so that the user can see inside the left ventricle 701. In some examples, the display of the structure of interest 711 may be adapted to reflect the state after the planned treatment. That is, the user may adapt the graphical representation of the structure of interest 711 to include a virtual model of an implant, such as a prosthesis.

[0044] FIG. 8 is a cross-sectional view of the structure of interest 711 from the 3D model 602 of FIG. 6. In this example, the graphical representation of the structure of interest 711 is adapted to include a virtual model of a prosthesis 804 (in this example, a prosthetic mitral valve). In some examples, the virtual model of the prosthesis 804 may be shaped based on its brand, type, and size. In some examples, the adaptation of the graphical representation of the structure of interest 711 may be based on the planned orientation and position of the prosthesis 804 relative to the structure of interest. The virtual model of the prosthesis 804 may be a 2D or 3D model of the prosthesis 804. It is incorporated into one or more 2D medical images and / or a virtual 3D model of the structure of interest. The virtual model of the prosthesis 804 may include a schematic diagram, such as a cylinder, or a more lifelike 3D model of the actual device. It may be a parameterized virtual object, a model loaded from a file, or a model loaded from a library of device templates.

[0045] The virtual placement of the prosthesis 804 within the patient's anatomy can correspond to a planned outcome of the treatment. For example, the treatment outcome may be planned prior to data collection and used to validate the treatment plan by virtually placing the prosthesis 804 within the patient's anatomy. In some embodiments, the virtual treatment plan can be created or modified during visualization of the structure of interest 711. For example, the treatment plan may be created or modified by a user, such as a medical professional, or a non-medical professional, such as a technician or engineer, by visually or automatically identifying anatomical structures within the display and / or based on a planning algorithm that directs the selection and position of the prosthesis 804. In some examples, the selection of the device size and / or the selection of the device location (e.g., position and orientation) is made relative to the patient's anatomy. For example, with respect to features of the patient's anatomy, with respect to anatomical landmarks, with respect to geometric primitives (such as coordinate systems, planes, lines, vectors or points) derived from such features or landmarks, or with respect to measurements made of or between such features, landmarks or geometric primitives. In other embodiments, obtaining the virtual treatment plan may include loading a previously created virtual treatment plan from a file, database, or any other medium.

[0046] (Determining the region of interest within the structure of interest) Figure 9 is a cross-sectional view of a structure of interest 711 from the 3D model 602 of Figure 6. In this example, the graphical representation of the structure of interest 711 is adapted to include a 3D virtual model of a prosthesis 804 (in this example, a prosthetic mitral valve). A region of interest 902 is then determined and visually incorporated into the structure of interest 711. In this example, the region of interest 902 is between a first plane 906 through the aortic valve and a second plane 908 tangent to the lower edge 904 of the prosthesis 804. The second plane 908 may be parallel to the first plane 906.

[0047] The computing device 400 may be used to determine the region of interest 902 using the structure of interest 711 with the displayed prosthesis 804. In some examples, the region of interest 902 may be determined visually by a user and / or an algorithm. For example, the region of interest 902 may be manually indicated by a user on a representation of the structure of interest 711 (e.g., before the incorporation of the prosthesis as shown in FIG. 7) or on a fitted representation of the structure of interest (e.g., after the incorporation of the prosthesis as shown in FIG. 8 and FIG. 9). In another example, the region of interest may be automatically determined, e.g., by an algorithm based on anatomical structures identified manually or algorithmically in the structure of interest 711 and / or the surrounding area. For example, the first plane 906 may be determined as the best-fit plane through the annulus of the aortic valve. The annulus may be manually indicated by a user on one or more representations of the structure of interest 711 or may be automatically detected using any suitable feature recognition technique known in the art.

[0048] The region of interest 902 may include the entire structure of interest 711 or only a portion of the structure where a fluid flow obstruction may be expected. In some examples, the region of interest 902 may include the LVOT 106a and / or the neo-LVOT 106b / 106c, both of which are bounded by the aortic valve, the basal septum, the intervalvular fibers, and the curved anterior mitral leaflet. In some examples, the curved anterior mitral leaflet may be approximated by a user or an algorithm by identifying the outer wall of the representation of the prosthesis. In some examples, the region of interest 902 may include the entire left ventricle, optionally excluding the volume occupied by the 3D virtual model of the prosthesis 804.

[0049] An example of a process for determining the region of interest 902 includes the following steps: (i) a user may utilize the image processing module 308 or the measurement and analysis module 320 (e.g., Mimics application, 3D Slicer, etc., from Materialise NV) on the computing device 400 to detect and indicate a structural element (e.g., aortic valve) in a 2D image or 3D / 4D model using 2D and / or 3D feature recognition algorithms with or without manual or initial visual identification of the structural element by the user (e.g., the user may provide an initial indication of which structural aspect, such as the aortic valve annulus, corresponds to which portion of the model or image); (ii) upon recognition of the structural aspect, the algorithm may insert a first plane 906 through the aortic valve of the displayed structure of interest 711; and (iii) the first plane 906 may be translated into the left ventricle until it meets the lower edge 904 of the prosthesis 804. In this example, the translated first plane is displayed on the structure of interest 711 as a second plane 908. In this case, the region of interest 902 may be limited to a cross section of the aortic valve or fitted blood pool volume between the first plane 906 and the second plane 908 (e.g., blood pool volume minus the volume of the representation of the prosthesis 804). In some embodiments, steps (i) and / or (ii) may be replaced by a user manually indicating the first plane 906. For example, the user may indicate three points on the structure of interest 711 (e.g., the aortic valve cusps) and draw the first plane through them.

[0050] In some embodiments, the region of interest 902 may extend into the left atrium to include more than the LVOT and neo-LVOT (e.g., neo-LVOT extension 106c in FIG. 1). FIG. 10 is a cross-sectional view of a 2D CT image of an example of a patient's heart 1000. In this example, the 2D CT image includes a cross-sectional view of the left ventricle 1001, the left atrium 1002, the aorta 1003, a virtual model 1004 of the prosthesis (e.g., note that the virtual model is a 2D model for implementation in a 2D image), the LVOT 1006a, the neo-LVOT 1006b, an extension of the neo-LVOT 1006c, and a centerline or guide curve 1009 of the LVOT 1006a, the neo-LVOT 1006b, and the extension 1006c. In this example, the region of interest (eg, the combination of the LVOT 1006a, the neo-LVOT 1006b, and the extension 1006c) can further include a volume bounded by a plane tangent to the lower edge 904 of the representation of the prosthesis 804 on the posterior side.

[0051] Other boundaries may also be defined. For example, a 2D or 3D guide curve 1009 through (part of) the structure of interest, including or excluding the volume occupied by said representation 1004 of the prosthesis, may be indicated by the user or calculated by an algorithm. For example, the guide curve may be calculated as a centerline through the left ventricle and the aorta. That is, in some embodiments, the centerline of the flow path may be calculated using the boundaries of the structure of interest, such as the lumen of the blood vessel through which the fluid flows, to determine the center of the flow path. In this example, the centerline may be bounded by the intervalvular fibers and the base septum, meaning that the centerline is equidistant to both structural elements. To obtain a 2D guide curve, the 2D centerline may be calculated based on a 2D representation of the structure of interest (e.g., a 2D medical image). To obtain a 3D guide curve, the 3D centerline may be calculated based on a 3D representation of the structure of interest (e.g., a 3D model such as a surface model). As mentioned above, performing these steps in 3D will yield more reliable results, since it allows the complete three-dimensional shape of the anatomical structure to be taken into account. A plane perpendicular to the guide curve 1009 may then be determined as the boundary facing the fluid outlet of the structure of interest (e.g., the aortic valve). In an example, this may be a plane perpendicular to the guide curve 1009 and tangent to the lower edge of the representation 1004 of the prosthesis on the side closest to the fluid outlet (e.g., the anterior side). In another example, this may be a plane perpendicular to the guide curve 1009 and tangent to the lower edge of the representation 1004 of the prosthesis on the side furthest from the fluid outlet (e.g., the posterior side). In yet another example, this may be a plane perpendicular to the guide curve 1009 at another location (e.g., tangent to the native mitral annulus on the anterior or posterior side).

[0052] In some embodiments, calcification and / or existing hardware is subtracted from the blood pool volume or a portion of the blood pool volume to determine the region of interest. Thus, the region of interest (e.g., LVOT 1006a, neo-LVOT 1006b, and / or extension 1006c) may be mentally defined by the user or may be stored as a separate virtual entity or collection of entities. In some examples, the region of interest is stored as a virtual 3D model, such as a virtual 3D surface model (e.g., a virtual 3D surface model of the anatomical structure of LVOT 1006a, neo-LVOT 1006b, and / or extension 1006c). In other examples, the region of interest may be stored as one or more planes, surfaces, polygons, triangles, lines, curves, splines, cylinders, or other geometric primitives that define a portion of the structure of interest. In some embodiments, the region of interest and / or its boundaries may be visualized instead of, in addition to, or overlaid on the adapted representation.

[0053] (Define a guide curve through the region of interest) FIG. 11 is a cross-sectional view of the structure of interest 711 from the 3D model 602 of FIG. 6. In this example, a guide curve 1102 is determined and visually fitted to the structure of interest 711. Here, the guide curve 1102 includes a first portion 1102a that is the centerline of the region of interest (e.g., LVOT 1006a and neo-LVOT 1006b of FIG. 10) and a second portion 1102b that is the centerline of an extension of the region of interest (e.g., extension 1006c of FIG. 10). In some examples, the position and orientation of the guide curve 1102 may be determined and a graphical representation of the guide curve 1102 may be incorporated into the representation of the structure of interest 711 (e.g., before the incorporation of the prosthesis) or may be incorporated onto the fitted representation of the structure of interest (e.g., after the incorporation of the prosthesis). The guide curve 1102 may be determined based on characteristics of the region of interest (e.g., the guide curve may include the centerline of the region of interest). The centerline may be calculated automatically using any suitable centerline algorithm known in the art. The robustness of some of these algorithms may be modified by applying them to an extended region of interest (e.g., incorporating the neo-LVOT extension 1006c or extending further into the left ventricle or aorta).

[0054] In another example, the guide curve 1102 may be generated between two points selected by a user or an algorithm. For example, the user may arbitrarily select two points on the displayed structure of interest 711. Or, the algorithm may select two points at opposite ends of the structure of interest 711 or region of interest. In this case, the algorithm may select two points such that both points are located in the center of a fluid or air flow path (e.g., in this example, the left ventricle). In other examples, the first point may be: (i) any point in the structure of interest 711, (ii) a manually indicated point in the structure of interest 711, (iii) an anatomical landmark of the structure of interest 711 (e.g., the tip of the left ventricle), or (iv) the center of the region of interest including or excluding the volume of said representation of the prosthesis 804 (e.g., the centroid of the blood pool volume of the left ventricle, optionally excluding the volume of the prosthesis 804 in its planned position, any calcification, and / or any existing hardware). The second point may be a point near the fluid outlet of the structure of interest 711, such as any point near the aortic valve, a manually indicated point near the aortic valve, or an automatically determined point such as the center of the aortic valve. In some examples, multiple points may be added between the first and second points to provide the user with more control over the direction of the guide curve. In some examples, the guide curve may include one or more straight line segments and / or one or more curved segments, such as a spline curve, between the selected points.

[0055] In some examples, the guide curve 1102 is manually defined by a user (e.g., the user may hand-draw the guide curve on the depiction or the adapted depiction). The user may include a medical professional or a non-medical professional such as an engineer or technician, or any other suitable user. Alternatively, the guide curve 1102 is determined algorithmically based on the depiction or the adapted depiction. For example, the guide curve 1102 may be determined as a straight line between a first point and a second point. Alternatively, the guide curve 1102 may be determined as a centerline of the structure of interest 711 and / or the region of interest, including or excluding the volume of said representation of the prosthesis 804. In this case, the algorithm may determine the guide curve 1102 such that the guide curve 1102 follows the centerline defined by the structure of interest 711 and / or the region of interest. For example, the algorithm may determine (a part of) the path of the guide curve 1102 based on the wall of the aorta such that the guide curve 1102 follows a path that is substantially in the center of the blood flow path.

[0056] In some examples, instead of defining the guide curve 1102 as a centerline through the structure of interest 711 and / or region of interest, the guide curve 1102 may be defined as a straight line segment (e.g., not necessarily centered) through the structure of interest 711 and / or region of interest (e.g., along the blood flow path of the aorta). In some examples, the guide curve 1102 may be defined as a line segment (e.g., not necessarily centered or straight) through the structure of interest 711 and / or region of interest. In other examples, the guide curve 1102 may be a straight line segment or a curve, such as a spline, that substantially follows the fluid flow path from a first point to a second point.

[0057] The guide curve 1102 may be visually displayed as an object on the 2D image data or on a 3D / 4D model. In some examples, the guide curve 1102 may be a 2D curve (e.g., fully defined in one plane and graphically represented on a single 2D image, a single MPR image, or a 3D model) or may be a 3D object represented on a single 2D image, a single MPR image, or a 3D / 4D model.

[0058] (Multiple evaluation plane definitions) As mentioned above, the guide curve 1102 may be a curve or line that substantially follows the flow path of the fluid / air or may be the centerline of (a part of) the structure of interest 711 or region of interest. In some embodiments, one or more planes may be defined and optionally visually displayed along the guide curve 1102 to determine the cross-sectional surface area of ​​the structure of interest or region of interest. Thus, the one or more planes may intersect with the surrounding anatomical structures shown in the 2D image or 3D / 4D model and define a closed cross-section through which the fluid / air flows. Since laminar flow can be expected to flow substantially parallel to the guide curve, one or more planes perpendicular to the guide curve provide the best basis for the assessment of fluid flow obstructions. Thus, determining the cross-sectional surface area of ​​a particular region provides the user with information indicating whether possible obstructions to the fluid / air flow arise from the prosthesis.

[0059] FIG. 12 is a diagram showing a conceptual guide curve 1102 having multiple planes 1202 defined orthogonally to the guide curve 1102. Here, the multiple planes 1202 are defined orthogonally to the guide curve 1102 at (e.g., regular) intervals along the guide curve 1102. The intervals may be determined by an algorithm based on the length of the guide curve 1102, the slope of the anatomical structure along the guide curve 1102, etc. In zones with higher probability of occlusion, a smaller interval may be selected, and vice versa. The user may also determine the interval to balance between accuracy and computational load, such as a value between 1 mm and 2 cm (e.g., 2 mm, 3 mm, 4 mm, 5 mm, 6 mm, 7 mm, 8 mm, 9 mm, 1 cm, or 1.5 cm). The multiple planes 1202 may constitute multiple evaluation planes.

[0060] It should be noted that a manually drawn guide curve 1102 may be less accurate than an algorithmically determined guide curve 1102, and that an automatically determined guide curve 1102 may not reflect all anatomical features (e.g., local protrusions or depressions) along the anatomical boundaries of the region of interest (e.g., the wall of the aorta or the wall of the respiratory passages).

[0061] FIG. 13 is a diagram illustrating a conceptual guide curve 1102 having a first plane 1302a of the plurality of planes 1202. As shown in FIG. 13, the first plane 1302a refers to one of the planes 1202. Also, the rotated first plane 1302b refers to a rotation of the first plane 1302a about the first axis 1304. Although not shown, additional rotations of the first plane 1302a about the first axis 1304 may be included, and the rotated positions of each of the first planes 1302a may be added to the plurality of evaluation planes. Thus, in the context of the plurality of planes 1202 along the guide curve 1102, each of the plurality of planes 1202 is in a first position, resulting in a first plurality of evaluation planes (e.g., one evaluation plane corresponding to each of the plurality of planes 1202). However, additional evaluation planes may be generated by incrementally rotating one or more of the plurality of planes 1202. For example, each incremental rotation of the first plane 1302a may result in an additional evaluation plane (e.g., the rotated first plane 1302b).

[0062] The multiple planes 1202 may be generated orthogonally along the guide curve 1102 and rotated about a local rotation axis to provide additional evaluation planes. For example, each of the multiple planes 1202 may be rotated about a local rotation axis at an angle increment in one or more directions. In this example, the first plane 1302a may be rotated along a first axis 1304 (e.g., tangent to the first plane 1302a / locally perpendicular to the guide curve 1102) passing through the intersection of the first plane 1302a and the guide curve 1102. Alternatively, or in addition, the first plane 1302a may be rotated along a second axis 1306 (e.g., tangent to the guide curve 1102 and the first axis 1304 / locally perpendicular). Each plane may be rotated at one or more (e.g., fixed) angle increments, such as 1°, 2°, 5°, 10°, 12°, or 15°. After each rotation, the resulting rotated plane, e.g., plane 1302b, may be added to the multiple evaluation planes. That way, a rotation of the first plane 1302a may result in multiple different evaluation planes.

[0063] Thus, a plurality of evaluation planes (e.g., a second plurality of planes) can be defined along the guide curve 1102 by rotating one or more of the plurality of planes 1202 about one or more axes tangent / perpendicular to the guide curve 1102 at one or more angle increments. In one example, one or more of the plurality of evaluation planes correspond to a first rotation of one of the one or more of the plurality of planes 1202 (e.g., the first plane 1302a) about a first axis 1304 perpendicular to the guide curve 1102 at one or more angle increments, respectively. Thus, each of the plurality of planes 1202 and each of the plurality of evaluation planes may intersect the anatomical structure at a different location (e.g., at a region of interest). In another example, one or more of the multiple evaluation planes corresponds to a second rotation of a plane (e.g., the first plane 1302a) of the one or more of the multiple planes 1202 about a second axis 1306 that is perpendicular to the guide curve 1102 and the first axis 1304. In some examples, an intersection between the plane and the anatomical structure can define a transverse plane of the anatomical structure, as discussed further below.

[0064] FIG. 14 illustrates a conceptual guide curve 1102 having a rotated first plane 1302b corresponding to a rotation of one of the planes 1202. Note that, as illustrated in FIG. 14, there is a first rotated plane 1302b and an additional rotated plane 1402 corresponding to a further rotation of the rotated plane 1302b about another third axis 1404, which is different from the axis about which the first plane 1302a is rotated to generate the rotated plane 1302b. Additional rotations may be included, and each rotation of the rotated first plane 1302b may be added to the multiple evaluation planes. Additionally, any one or more rotated planes generated from any one or more planes 1202 may be further rotated along a different axis and the result added to the multiple evaluation planes. In this example, the rotated first plane 1302b may be rotated through the intersection along a third axis 1404 (tangential / locally perpendicular to the guide curve 1102 and perpendicular to the first axis 1304) at one or more (e.g., fixed) angle increments, such as 1°, 2°, 3°, 5°, 10°, 12°, 15°, 20°, 30°, 45°, or 90°, to complete a full circle (e.g., 35 rotations over 10° or 17 rotations over 20°). Thus, one or more of the rotations of one or more planes of the plurality of planes 1202 may be further rotated along a corresponding third axis 1404. Additional evaluation planes may be defined by combining rotations at zero or more angle increments about the three axes. In an example, each rotation process may be followed by one or more further rotation processes, where during each process, each plane is rotated in a different direction. In one example, a rotation of a plane about the third axis 1404 may be performed on a plane only after a rotation of that plane about the first axis 1304, the second axis 1306, and / or any additional axes. After each rotation operation, the resulting plane is added to the multiple evaluation planes.

[0065] 3 may perform the generation of multiple planes 1202 and guide curves 1102, as well as any plane rotations and cross-section measurements for each plane. Extending multiple evaluation planes with plane rotations can overcome local inaccuracies of manually prescribed or automatically calculated guide curves and improve the chances of finding the true minimum cross-section through the region of interest.

[0066] (Determination of cross-sectional size) In some embodiments, a cross-sectional surface area of ​​an anatomical structure (e.g., in a region of interest) can be determined where each of the multiple planes 1202 intersects the anatomical structure. In one example, an algorithm may generate a segmented image or shape (e.g., a polygon, closed polyline, or closed curve) of the intersection between each plane and the lumen of the anatomical structure through which the fluid / air flows, and then calculate the cross-sectional surface area. The same may be done for each angle increment of rotation of the plane.

[0067] For example, in the adapted representation of a 2D image, a user or an algorithm may calculate the distance from one edge where a plane intersects an anatomical structure to the other edge where the same plane intersects the other side of the anatomical structure. In another example, the adapted representation of the structure of interest may include a 3D surface model of the region of interest, and the surface area of ​​a cross section of the region of interest in the evaluation plane can be determined by first determining the intersection of the evaluation plane with the anatomical structure of the 3D surface model, and then determining the surface area of ​​the cross section. In some examples, the determination of the surface area of ​​the cross section of the 3D model may be performed by an algorithm using 3D geometric operations.

[0068] Optionally, one or more evaluation planes may be discarded based on their location relative to (i) the representation of the prosthesis, (ii) the structure of interest, (iii) the region of interest, or (iv) the boundaries of any of these entities. For example, blood flow may be expected to flow perpendicular to the aortic valve, so all evaluation planes that intersect the aortic valve may be discarded. In another example, if fluid flow obstruction due to the placement of a prosthesis is evaluated, all evaluation planes that do not intersect the representation of the prosthesis may be discarded.

[0069] In some embodiments, the minimum cross-section is determined by finding the minimum surface area among all or the remaining evaluation planes (e.g., among each of the planes and each of their rotations). This minimum surface area can be interpreted as a measure of the passageway still available for fluid / air flow after the planned medical procedure, or as a measure of the level of obstruction that will result from the planned medical procedure. The minimum surface area may be determined via an algorithm or manually by the user.

[0070] In some instances, the determination of the minimum cross-section may allow the user to accept, reject, or modify the pre-planned treatment. The methods described herein may be repeated across multiple virtual treatment plans to compare and select the optimal treatment plan (e.g., to select the prosthesis type and size and / or prosthesis location that best suits the patient).

[0071] In some examples, the multiple planes defined along the guide curve may be divided into multiple subsets of one or more planes that share an intersection with the guide curve. In this example, the smallest cross-section of the one or more planes in the subset is determined for each subset. Thus, the multiple cross-sections can be used to evaluate the fluid / air flow in the structure of interest and / or region of interest. For example, all evaluation planes that share the same intersection with the guide curve can be grouped into one subset (e.g., all evaluation planes generated by rotating a first plane around one or more axes and / or points). As such, the change in the smallest cross-sectional surface area may be tracked along the guide curve.

[0072] In some examples, the minimum surface area profile may be generated based on the minimum surface area of ​​each of two or more subsets along the guide curve. This provides the advantage of being able to distinguish between isolated stenosis (e.g., a localized narrowing of the passageway) and tunnel-type stenosis (e.g., a narrowing over a relatively long distance). Multiple cross-sectional surface areas may be graphically profiled and presented as a graph (e.g., where the interval along the guide curve is presented along the horizontal axis and the cross-sectional size of the anatomical structure is presented along the vertical axis). For example, both FIG. 15 and FIG. 16 are example graphs showing the cross-sectional area along the centerline or guide curve of a fluid or air passageway. In this example, FIG. 15 can show an isolated stenosis, while FIG. 16 can show a tunnel-type stenosis.

[0073] Alternatively or additionally, the cross-sectional surface areas of anatomical structures may be presented graphically in the adapted representation, for example, as a false-color overlay on the structures and / or regions of interest showing cross-sectional sizes, where the surface colors of the 3D model are mapped to different cross-sectional sizes.

[0074] As mentioned above, the techniques described herein may also be used to identify the type of stenosis in a patient's anatomy. In one example, a threshold may be determined for the number of evaluation plane subsets and / or the length of the section of the guide curve along which a stenosis may be identified. Stenosis below this threshold (e.g., a small number of relatively smaller cross-sectional sizes in one area than other cross-sectional sizes outside the area) may be identified as an isolated stenosis. Stenosis above this threshold (e.g., a large number of relatively smaller cross-sectional sizes in one area than other cross-sectional sizes outside the area) may be identified as a tunnel-type stenosis. That is, a relatively localized or short distance of small cross-sectional sizes will likely correspond to an isolated stenosis, while a relatively widespread distance of small cross-sectional sizes will likely correspond to a tunnel-type stenosis.

[0075] In some examples, cross-sectional values ​​for both the pre-treatment state (e.g., using a visual representation of the structure of interest pre-treatment) and the post-treatment state (e.g., using a visual representation of the structure of interest matched with the prosthesis post-treatment) can be calculated and presented to the user. Here, the minimum cross-sectional area may be determined in the pre-treatment state (e.g., the minimum cross-sectional area is determined in the original representation of the anatomical structure, not the adapted representation). This can result in the minimum cross-sectional area of ​​the LVOT. The minimum cross-sectional area may then be determined in the post-treatment state (e.g., the minimum cross-sectional area is determined in the adapted representation). The system according to certain embodiments may then display the ratio of the post-treatment minimum cross-sectional area to the pre-treatment minimum cross-sectional area as a measure of the remaining fluid / air passageway or as a measure of the obstruction of the fluid / air passageway. For example:

[0076]

number

[0077] In some examples, the system may display the ratio of the determined minimum cross-section of the region of interest to the cross-section of the pre-treatment structure in the same evaluation plane.

[0078] 17 is a flow chart illustrating a process 1700 for determining a minimum neo-LVOT cross-sectional surface area, according to certain embodiments. It should be noted that in certain embodiments, process 1700 is a computer-implemented process. Additionally, certain blocks may be performed automatically, manually by a user of a computing device, or partially manual and partially automatic based on input from a user of a computing device. The user may be a medical professional or a non-medical professional, such as a technician or engineer. Additionally, certain blocks may be optional, and some of the methods described may be performed as separate methods.

[0079] Process 1700 begins at block 1702 by generating a model of a structure based on multiple images of the structure. The structure includes at least one fluid flow path.

[0080] Process 1700 may proceed to block 1704 by identifying an occlusion element in a model of the structure. The occlusion element affects at least one fluid flow path in the model.

[0081] Process 1700 may proceed to block 1706 by determining a region of at least one fluid flow path for flow analysis. In some examples, the flow analysis includes the processes depicted in blocks 1708-1714. For example, process 1700 may proceed to block 1708 by defining a guide curve along at least a portion of at least one fluid flow path. Process 1700 may proceed to block 1710 by defining a plurality of planes along the guide curve, where each of the plurality of planes is orthogonal to the guide curve and intersects the region to define at least some of a plurality of cross-sections of the region. Process 1700 may proceed to block 1712 by determining which one of the plurality of cross-sections has a minimum surface area. Process 1700 may proceed to block 1714 by displaying the size of the minimum surface area.

[0082] In some instances, the occlusion element is a virtual model of a prosthesis inserted into the model.

[0083] In some examples, the process 1700 further includes selecting a virtual model of the obstruction element based on the treatment plan to improve fluid flow in the second fluid flow path.

[0084] In some examples, defining the guide curve includes selecting a first point at a first location of the at least one fluid flow path; and selecting a second point at a second location of the at least one fluid flow path, where defining the guide curve includes defining the guide curve from the first point to the second point such that the guide curve follows a direction of fluid flow through the at least one fluid flow path.

[0085] In some examples, defining the guide curve includes determining a centerline of at least a portion of the at least one fluid flow path. The centerline may be determined based on a lumen of the at least one fluid flow path. For example, defining the guide curve may include calculating a centerline path of the at least one fluid flow path, where the centerline path is bounded by the structure and the guide curve follows the centerline path.

[0086] In some examples, the process 1700 further includes spacing each of the plurality of planes from another one of the plurality of planes at regular intervals along the guide curve; rotating one or more of the plurality of planes about an intersection between one or more of the plurality of planes and the guide curve, where the one or more of the plurality of planes are rotated at an angular increment along a first axis; and determining a surface area of ​​each cross-section corresponding to each angular increment along the first axis.

[0087] In some examples, the process 1700 further includes rotating one or more of the plurality of planes about an intersection between one or more of the plurality of planes and the guide curve, where rotating one or more of the plurality of planes by an angular increment along a second axis; and determining a surface area of ​​each cross-section corresponding to each angular increment along the second axis.

[0088] In some examples, the process 1700 further includes defining a second plurality of planes, each of the second plurality of planes corresponding to a rotation of one of one or more of the plurality of planes about a first axis perpendicular to the guide curve, each of the second plurality of planes intersecting the region to define at least some of a plurality of cross-sections of the region.

[0089] In some examples, the process 1700 further includes defining a third plurality of planes, each of the third plurality of planes corresponding to a rotation of one of one or more of the plurality of planes about a second axis perpendicular to the guide curve and the first axis, each of the second plurality of planes intersecting the region to define at least some of the multiple cross-sections of the region.

[0090] In some examples, the process 1700 further includes defining a fourth plurality of planes, each of the fourth plurality of planes corresponding to a rotation of one of one or more of the plurality of planes, the second plurality of planes, or the third plurality of planes about a third axis tangent to the guide curve, each of the second plurality of planes intersecting the region to define at least some of the multiple cross-sections of the region.

[0091] In some examples, process 1700 further includes dividing the plurality of planes into two or more subsets, where each of the two or more subsets includes one or more planes, and determining which one of the plurality of cross-sections has the smallest surface area includes determining which one of the one or more planes in each subset has the smallest surface area.

[0092] In some instances, each subset consists of a selection of planes that share an intersection with the guide curve.

[0093] In some examples, the process 1700 further includes generating a minimum surface area profile by profiling the minimum surface area along the guide curve based on the minimum surface area of ​​each of the two or more subsets.

[0094] In some examples, the process 1700 further includes identifying an isolated stenosis or a tunnel-type stenosis based on the minimum surface area profile.

[0095] In some examples, the multiple images include multiple computed tomography (CT) scans of the structure.

[0096] In some examples, determining the area of ​​the at least one fluid flow path further includes utilizing feature recognition software to identify a portion of the structure that includes the area.

[0097] Using the above-described systems and methods, a standardized method provides physicians and researchers with the ability to determine the minimum neo-LVOT area for transcatheter mitral valve repair research and development, as well as appropriate sizing in the context of the patient and treatment plan. While the above specific examples relate to the mitral valve, those skilled in the art will appreciate that the above principles, systems, and methods may be readily applied in connection with other types of surgical procedures and other regions of the anatomy. For example, in some embodiments, the valve may be a pulmonary branch valve, tricuspid valve, etc. In other embodiments, the above-described systems and methods may be used in the treatment of pulmonary stenosis, other valves, left atrial appendage (LAA) closure procedures, stent grafts for aortic aneurysms, cerebral aneurysm devices, valve annulus evaluation (e.g., minimum area / maximum area), etc. In certain embodiments, the described systems and methods may be used for the treatment of airways, airway conditions, and placement of prosthetic devices (e.g., stents, grafts, valves, drug delivery systems, etc.) within the airways, and the like.

[0098] It should be understood that any feature described in connection with any one embodiment may be used alone or in combination with the other features described, and may also be used with one or more features of any other embodiment or in any combination of any other embodiment. Moreover, equivalents and modifications not described above may also be employed without departing from the scope of the disclosure, which is defined in the appended claims.

[0099] The methods disclosed herein include one or more steps or actions for achieving the described method. Method steps and / or actions may be interchanged with one another without departing from the scope of the claims. In other words, unless a specific order of steps or actions is specified, the order and / or use of specific steps and / or actions may be changed without departing from the scope of the claims. Additionally, one or more blocks / steps may be removed or added. For example, only portions of process 1700 illustrated with respect to FIG. 17, such as blocks 1702-1714, may be performed in certain embodiments to determine which cross-section has the smallest surface area.

[0100] The methods disclosed herein include one or more steps or actions to achieve the described method. Various embodiments disclosed herein provide for the use of a computer system to perform certain or all of the method steps or actions. Those skilled in the art will readily understand that such steps may be partially or fully automated. Various embodiments disclosed herein include method steps that are partially or fully performed by a user or require user input. Those skilled in the art will readily understand that the user may be a medical professional or a non-medical professional such as a technician or engineer.

[0101] Various embodiments disclosed herein provide for the use of a computer system to perform certain features. Those skilled in the art will readily appreciate that these embodiments may be implemented using many different types of computing devices, including both general-purpose and / or specialized computing system environments and configurations. Examples of well-known computing systems, environments, and / or configurations suitable for use in connection with the above-described embodiments may include, but are not limited to, personal computers, server computers, handheld or laptop devices, multiprocessor systems, microprocessor-based systems, programmable consumer electronics products, network PCs, minicomputers, mainframe computers, distributed computing environments that include any of the above systems or devices, and the like. These devices may include stored instructions that, when executed by a microprocessor in a computing device, cause the computing device to perform specified operations to execute the instructions. As used herein, instructions refer to computer-implemented steps for processing information in a system. Instructions may be implemented in software, firmware, or hardware and include any type of programmed steps performed by components of the system.

[0102] The microprocessor may be any conventional general-purpose single-chip or multi-chip microprocessor, such as a Pentium® processor, a Pentium® Pro processor, an 8051 processor, a MIPS® processor, a Power PC® processor, or an Alpha® processor. Additionally, the microprocessor may be any conventional special-purpose microprocessor, such as a digital signal processor or a graphics processor. A microprocessor typically has conventional address lines, conventional data lines, and one or more conventional control lines.

[0103] The aspects and embodiments disclosed herein may be implemented as a method, apparatus, or article of manufacture using standard programming or engineering techniques to generate software, firmware, hardware, or any combination thereof. As used herein, the term "article of manufacture" refers to code or logic implemented in hardware or non-transitory computer-readable media, such as optical storage devices, as well as volatile or non-volatile memory devices, such as signals, carrier waves, or transitory computer-readable media. Such hardware may include, but is not limited to, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), complex programmable logic devices (CPLDs), programmable logic arrays (PLAs), microprocessors, or other similar processing devices. [Brief description of the drawings]

[0104] [Figure 1] 1 and 2 are diagrams showing cross-sections of the heart. [Diagram 2] 1 and 2 are diagrams showing cross-sections of the heart. [Diagram 3] FIG. 3 is an example of a suitable computing environment for implementing certain embodiments described herein. [Figure 4] FIG. 4 is an example of a computing device suitable for implementing various embodiments. [Diagram 5] FIG. 5 is an example of a two-dimensional (2D) computed tomography (CT) image of a patient's heart. [Figure 6] FIG. 6 is an example of a combination of multiple orthogonal 2D images used to generate a three-dimensional (3D) model of a patient's heart. [Figure 7] FIG. 7 is a cross-sectional view of a structure of interest from the 3D model of FIG. [Figure 8] FIG. 8 is a cross-sectional view of a structure of interest from the 3D model of FIG. [Figure 9] FIG. 9 is a cross-sectional view of a structure of interest from the 3D model of FIG. [Figure 10] FIG. 10 is a cross-sectional view of a 2D CT image of one embodiment of a patient's heart. [Figure 11] FIG. 11 is a cross-sectional view of a structure of interest from the 3D model of FIG. [Figure 12] FIG. 12 is a diagram illustrating a conceptual guide curve having a number of planes defined perpendicular to the guide curve. [Figure 13] FIG. 13 is a diagram illustrating a conceptual guide curve having a first plane among a plurality of planes. [Figure 14] FIG. 14 is a diagram showing a conceptual guide curve obtained by rotating a first plane among a plurality of planes. [Figure 15] 15 and 16 are example graphs showing cross-sectional areas along centerlines or guide curves of fluid or air passages. [Figure 16] 15 and 16 are example graphs showing cross-sectional areas along centerlines or guide curves of fluid or air passages. [Figure 17] FIG. 17 is a flow diagram illustrating a process for creating multiple cross sections, in accordance with certain embodiments.

Claims

1. generating a model of the structure based on a plurality of images of the structure, the structure including at least one fluid flow path, the structure being an anatomical structure of the patient; identifying an occlusion element in a model of the structure, the occlusion element affecting the at least one fluid flow path in the model; determining a region of the at least one fluid flow path for flow analysis; performing said flow analysis; The flow analysis is defining a guide curve along at least a portion of the at least one fluid flow path; defining a first plurality of planes along the guide curve, each of the first plurality of planes being perpendicular to the guide curve and intersecting the region to define at least some of a plurality of cross-sections of the region; defining a second plurality of planes, each of the second plurality of planes corresponding to a rotation of one of the first plurality of planes about a first axis perpendicular to the guide curve, each of the second plurality of planes intersecting the region to define at least some of the plurality of cross-sections of the region; determining which one of the plurality of cross-sections has a smallest surface area; and indicating the size of the minimum surface area; Including, A method for assessing fluid flow.

2. The method of claim 1 , wherein the occlusion element is a virtual model of a prosthetic device inserted into the model.

3. The model of the structure includes a model of at least a portion of the patient's heart; the region of the at least one fluid flow path for the flow analysis includes a left ventricular outflow tract of the at least a portion of the heart of the patient; and The method of claim 2 , wherein the virtual model of the prosthesis comprises a virtual model of a prosthetic mitral valve.

4. The method of claim 2, further comprising a step of selecting the virtual model of the obstruction element based on a treatment plan to improve fluid flow in a second fluid flow path.

5. The step of defining the guide curve comprises: selecting a first point at a first location of the at least one fluid flow path; and selecting a second point at a second location of the at least one fluid flow path; 2. The method of claim 1, wherein defining the guide curve comprises defining the guide curve from the first point to the second point such that the guide curve follows a direction of fluid flow through the at least one fluid flow path.

6. The step of defining the guide curve includes the step of calculating a centerline path of the at least one fluid flow path; the centerline path is bounded by the structure; and The method of claim 1 , wherein the guide curve follows the centerline path.

7. defining a third plurality of planes; each of the third plurality of planes corresponds to a rotation of one of the first plurality of planes about a second axis perpendicular to the guide curve and the first axis; The method of claim 1 , wherein each of the third plurality of planes intersects the region to define at least some of the plurality of cross-sections of the region.

8. defining a fourth plurality of planes; each of the fourth plurality of planes corresponds to a rotation of one of the second plurality of planes about a third axis tangent to the guide curve; The method of claim 1 , wherein each of the fourth plurality of planes intersects the region to define at least some of the plurality of cross-sections of the region.

9. dividing the plurality of planes into two or more subsets, where each of the two or more subsets includes one or more planes; and The method of claim 1 , wherein determining which one of the plurality of cross-sections has a smallest surface area comprises determining which one of the one or more planar surfaces in each subset has a smallest surface area.

10. The method of claim 9 , wherein each subset consists of a selection of planes that share an intersection with the guide curve.

11. The method of claim 10 , further comprising generating a minimum surface area profile by profiling a minimum surface area along the guide curve based on a minimum surface area of ​​each of the two or more subsets.

12. 12. The method of claim 11, further comprising identifying an isolated stenosis or a tunnel-type stenosis based on the minimum surface area profile.

13. The method of claim 1 , wherein the plurality of images comprises a plurality of computed tomography (CT) scans of the structure.

14. Memory, a processor communicatively coupled to the memory; Including, The processor and the memory generating a model of a structure based on a plurality of images of the structure, the structure including at least one fluid flow path, the structure being an anatomical structure of the patient; identifying an occlusion element within the model of the structure, the occlusion element affecting the at least one fluid flow path within the model; determining a region of the at least one fluid flow path for flow analysis; and configured to perform the flow analysis; The flow analysis is defining a guide curve along at least a portion of the at least one fluid flow path; defining a first plurality of planes along the guide curve, each of the first plurality of planes being perpendicular to the guide curve and intersecting the region to define at least some of a plurality of cross-sections of the region; defining a second plurality of planes, each of the second plurality of planes corresponding to a rotation of one of the first plurality of planes about a first axis perpendicular to the guide curve, each of the second plurality of planes intersecting the region to define at least some of the plurality of cross-sections of the region; determining which one of the plurality of cross-sections has a smallest surface area; and indicating the size of the minimum surface area. Including, A device for evaluating fluid flow.

15. The device of claim 14 , wherein the occlusion element is a virtual model of a prosthesis inserted into the model.

16. The model of the structure includes a model of at least a portion of the patient's heart; the region of the at least one fluid flow path for the flow analysis includes a left ventricular outflow tract of the at least a portion of the heart of the patient; and The apparatus of claim 15 , wherein the virtual model of the prosthesis includes a virtual model of a prosthetic mitral valve.

17. The device of claim 15, wherein the processor and memory are further configured to select the virtual model of the obstruction element based on a treatment plan to improve fluid flow in a second fluid flow path.

18. The step of defining the guide curve comprises: selecting a first point at a first location of the at least one fluid flow path; and Selecting a second point at a second location of the at least one fluid flow path. Including, 15. The apparatus of claim 14, wherein defining the guide curve comprises defining the guide curve from the first point to the second point such that the guide curve follows a direction of fluid flow through the at least one fluid flow path.

19. The method of claim 19, wherein the processor and the memory are configured to define the guide curve and are further configured to calculate a centerline path of the at least one fluid flow path; the centerline path is bounded by the structure; and The apparatus of claim 14 , wherein the guide curve follows the centerline path.

20. a non-transitory computer readable medium storing instructions that, when executed by a processor of an apparatus, cause the apparatus to perform a method for assessing fluid flow; The method comprises: generating a model of the structure based on a plurality of images of the structure, the structure including at least one fluid flow path, the structure being an anatomical structure of the patient; identifying an occlusion element in a model of the structure, the occlusion element affecting the at least one fluid flow path in the model; determining a region of the at least one fluid flow path for flow analysis; performing said flow analysis; The flow analysis is defining a guide curve along at least a portion of the at least one fluid flow path; defining a first plurality of planes along the guide curve, each of the first plurality of planes being perpendicular to the guide curve and intersecting the region to define at least some of a plurality of cross-sections of the region; defining a second plurality of planes, each of the second plurality of planes corresponding to a rotation of one of the first plurality of planes about a first axis perpendicular to the guide curve, each of the second plurality of planes intersecting the region to define at least some of the plurality of cross-sections of the region; determining which one of the plurality of cross-sections has a smallest surface area; and indicating the size of the minimum surface area; Including, Non-transitory computer-readable medium.

Images