Hemodynamic assessment of aortic valve stenosis by cardiac computed tomography

Abstract

Systems and methods are provided for performing hemodynamic assessment of aortic valve stenosis by a cardiac computed tomography (CT) scan. The method may include performing a cardiac CT scan of a patient and determining an aortic valve area () of the patient and a left ventricular outflow tract area () of the patient via the CT scan using a computing device, calculating an anatomical dimensionless index () based on the aortic valve area () and the left ventricular outflow tract area (), and determining a severity level of aortic valve stenosis (AS) of the patient based on the aortic valve area (), the left ventricular outflow tract area (), and the anatomical dimensionless index ().

Description

[0001] Cross-references to related applications

[0002] This application claims priority to U.S. Provisional Patent Application No. 63 / 585,623, filed September 27, 2023, the contents of which are incorporated herein by reference in their entirety. Technical Field

[0003] Embodiments of this disclosure relate to systems and methods for performing hemodynamic assessment of aortic stenosis via cardiac computed tomography. Background Technology

[0004] Echocardiography is an imaging technique in which ultrasound is used to image the heart, making it possible to examine the heart. The echocardiography process results in the generation of an echocardiogram (often also called an "echo"), which is the resulting image.

[0005] Echocardiography can be used to quantify the severity of aortic stenosis (AS) based on factors such as aortic valve area (AVA), mean aortic valve gradient, and Doppler-derived dimensionless index (DI).

[0006] Computed tomography (CT) scans are imaging techniques used to image the internal components of the body. During a CT scan, a series of X-ray images of a part of the body are taken from different angles, allowing a computer to generate a series of internal cross-sectional images of the body. Summary of the Invention

[0007] According to the purpose of this disclosure, a method for performing aortic valve stenosis hemodynamic assessment via cardiac computed tomography (CT) scan is provided. The method may include performing a cardiac CT scan of a patient using a CT scanner. The CT scanner may include: a gantry including one or more X-ray generators; a bed configured to support the patient; and a computing device including a processor and memory. The method may include using the computing device to determine the patient's aortic valve area (AVA) via the CT scan. ) and the patient's left ventricular outflow tract area ( Based on the aortic valve area ( ) and left ventricular outflow tract area ( To calculate the dimensionless anatomical index ( ) ), and based on aortic valve area ( ), left ventricular outflow tract area ( ) and anatomical dimensionless index ( Determine the severity of the patient's aortic stenosis (AS).

[0008] According to various embodiments, it is possible to... Calculating the dimensionless index of anatomy .

[0009] According to various embodiments, when Less than 1.3cm 2 and A value less than 0.25 indicates that the severity of the patient's AS is severe.

[0010] According to various embodiments, when At 1.3cm 2 and 2.0cm 2 Between and A score between 0.25 and 0.45 indicates that the severity of a patient's ankylosing spondylitis (AS) can be defined as moderate.

[0011] According to various embodiments, the method may include using a computing device to calculate the average aortic valve gradient according to the following mathematical formula: , in x Equal to the dimensionless index of anatomy ( ).

[0012] According to the purpose of this disclosure, a system is provided for performing hemodynamic assessment of aortic stenosis via cardiac computed tomography (CT) scan. The system may include a CT scanner configured to perform a cardiac CT scan of a patient. The CT scanner may include: a gantry including one or more X-ray generators; and a bed configured to support the patient. The system may include a computing device including a processor and memory. The computing device may be configured to: determine the patient's aortic valve area (…) via the CT scan. ) and the patient's left ventricular outflow tract area ( Based on the aortic valve area ( ) and left ventricular outflow tract area ( To calculate the dimensionless anatomical index ( ) ), and based on aortic valve area ( ), left ventricular outflow tract area ( ) and anatomical dimensionless index ( Determine the severity of the patient's aortic stenosis (AS).

[0013] According to various embodiments, the computing device can be configured to... Calculating the dimensionless index of anatomy .

[0014] According to various embodiments, the computing device can be configured to when Less than 1.3cm 2 and A score less than 0.25 indicates that the severity of the patient's AS is severe.

[0015] According to various embodiments, the computing device can be configured to when At 1.3cm 2 and 2.0cm 2 Between and A score between 0.25 and 0.45 indicates that the severity of the patient's AS is moderate.

[0016] According to various embodiments, the computing device can be configured to calculate the average aortic valve gradient according to the following mathematical formula: , in x Equal to the dimensionless index of anatomy ( ).

[0017] According to various embodiments, the frame may have holes through which one or more parts of the patient can pass.

[0018] According to various embodiments, the bed can be configured to allow one or more parts of the patient to move through the opening.

[0019] According to various embodiments, the computing device can be configured to enable a CT scanner to perform a cardiac CT scan of a patient.

[0020] According to the purpose of this disclosure, a system is provided for performing hemodynamic assessment of aortic stenosis via cardiac computed tomography (CT) scan. The system may include a CT scanner configured to perform a cardiac CT scan of a patient. The CT scanner may include: a gantry including one or more X-ray generators; and a bed configured to support the patient. The system may include a computing device including a processor and a memory. The memory may be configured to store programming instructions, which, when executed by the processor, are configured to cause the processor to determine the aortic valve area of ​​the patient via the CT scan. ) and the patient's left ventricular outflow tract area ( Based on the aortic valve area ( ) and left ventricular outflow tract area ( To calculate the dimensionless anatomical index ( ) ), and based on aortic valve area ( ), left ventricular outflow tract area ( ) and anatomical dimensionless index ( Determine the severity of the patient's aortic stenosis (AS).

[0021] According to various embodiments, programming instructions can be configured, when executed by a processor, to cause the processor to... Calculating the dimensionless index of anatomy .

[0022] According to various embodiments, the programming instructions can be configured, when executed by the processor, to cause the processor to: when Less than 1.3cm 2 and A score less than 0.25 indicates that the severity of the patient's AS is severe.

[0023] According to various embodiments, the programming instructions can be configured, when executed by the processor, to cause the processor to: when At 1.3cm 2 and 2.0cm 2 Between and A score between 0.25 and 0.45 indicates that the severity of the patient's AS is moderate.

[0024] According to various embodiments, the programming instructions, when executed by the processor, can be configured to cause the processor to calculate the average aortic valve gradient according to the following mathematical formula: , in x Equal to the dimensionless index of anatomy ( ).

[0025] According to various embodiments, the frame may have holes through which one or more parts of the patient can pass.

[0026] According to various embodiments, the programming instructions, when executed by the processor, can be configured to cause the processor to perform a cardiac CT scan of the patient.

[0027] According to various embodiments, the bed can be configured to allow one or more parts of the patient to move through the opening. Attached Figure Description

[0028] The accompanying drawings are included to provide a further understanding of this disclosure and are incorporated in and constitute a part of this application. The drawings illustrate embodiments of the disclosure and, together with the description, serve to explain the principles of the disclosure. In the drawings:

[0029] Figure 1 An example computed tomography (CT) scanner according to various embodiments of the present disclosure is shown;

[0030] Figure 2A An orthogonal stretched view generated by example CT of the ascending aorta and aortic root according to various embodiments of the present disclosure is shown, along with a corresponding vertical plane showing the tip of the aortic valve.

[0031] Figure 2B An orthogonal stretched view generated by example CT of the ascending aorta and aortic root according to various embodiments of the present disclosure is shown, along with a corresponding vertical plane illustrating the aortic rings;

[0032] Figure 2C An orthogonal stretched view generated by example CT of the ascending aorta and aortic root according to various embodiments of the present disclosure is shown, along with a corresponding vertical plane showing the aortic valve annulus, LVOT, and aortic valve.

[0033] Figure 3 A graphical representation of the relationship between the AVA of cardiac CT scans and the AVA of echocardiography according to embodiments of the present disclosure is shown;

[0034] Figure 4 A graphical representation of the relationship between the DI of a cardiac CT scan and the DI of an echocardiogram according to an embodiment of the present disclosure is shown;

[0035] Figure 5 A graphical representation of the relationship between the echocardiographic DI and the mean pressure gradient of the echocardiogram according to an embodiment of the present disclosure is shown.

[0036] Figure 6 A graphical representation of the relationship between the DI (displacement index) of a cardiac CT scan and the mean pressure gradient of an echocardiogram, according to embodiments of the present disclosure, is shown; and

[0037] Figure 7 Example elements of a computing device according to exemplary embodiments of the present disclosure are shown. Detailed Implementation

[0038] The terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit this disclosure. As used herein, the singular forms “a,” “an,” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. These terms are intended only to distinguish one component from another, and these terms do not limit the nature, order, or sequence of the constituent components. It will be further understood that, when used in this specification, the terms “comprising” and / or “including” specify the presence of the stated features, integers, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. As used herein, the term “and / or” includes any and all combinations of one or more of the associated listed items. Throughout the specification, unless expressly stated to the contrary, the word “comprising” and variations such as “including” or “containing” will be understood to imply the inclusion of the stated elements but not exclude any other elements. Additionally, the terms “unit,” “-er,” “-or,” and “module” described in the specification mean a unit for performing at least one function and operation, and can be implemented by hardware components or software components and combinations thereof.

[0039] In this document, when terms such as “first” and “second” are used to modify nouns, such use is intended only to distinguish one item from another and is not intended to require order unless otherwise specified. Furthermore, terms of relative position such as “vertical” and “horizontal” or “front” and “back” are intended to be relative to each other and are not required to be absolute, and refer only to one possible position of the device associated with these terms, depending on the orientation of the device.

[0040] "Electronic device" or "computing device" refers to a device that includes a processor and memory. Each device may have its own processor and / or memory, or the processor and / or memory may be shared with other devices, as in a virtual machine or container arrangement. The memory may contain or receive programming instructions that, when executed by the processor, cause the electronic device to perform one or more operations according to the programming instructions.

[0041] The terms "memory," "memory device," "computer-readable storage medium," "data storage," "data storage facility," etc., refer to non-transitory means of storing computer-readable data, programming instructions, or both thereon. Unless otherwise specified, the terms "memory," "memory device," "computer-readable storage medium," "data storage," "data storage facility," etc., are intended to include a single device embodiment, an embodiment in which multiple memory devices together or jointly store a set of data or instructions, and various sections within such devices.

[0042] The terms “processor” and “processing device” refer to hardware components of an electronic device configured to execute programmed instructions. Unless otherwise specified, the singular terms “processor” or “processing device” are intended to include embodiments of a single processing device and embodiments of multiple processing devices performing processing together or jointly.

[0043] The term "module" refers to a set of computer-readable programmable instructions executed by a processor, which causes the processor to perform a specified function.

[0044] Although the exemplary embodiments are described as using multiple units to perform the exemplary processes, it should be understood that the exemplary processes may also be performed by one or more modules. Furthermore, it should be understood that the term controller / control unit refers to a hardware device that includes a memory and a processor and is specifically programmed to perform the processes described herein. The memory is configured to store modules, and the processor is specifically configured to execute said modules to perform one or more processes further described below.

[0045] Furthermore, the control logic of this disclosure can be embodied on a non-transitory computer-readable medium containing executable programmable instructions that are executed by a processor, controller, etc. Examples of computer-readable media include, but are not limited to, ROM, RAM, optical disc (CD)-ROM, magnetic tape, floppy disk, flash drive, smart card, and optical data storage device. The computer-readable medium can also be distributed across a network-coupled computer system, allowing it to be stored and executed in a distributed manner, such as, for example, via a telematics server or a controller area network (CAN).

[0046] Unless otherwise specified or obvious from the context, as used herein, the term “about” should be understood as being within the normal tolerance range in the field, such as within 2 standard deviations of the mean. “About” can be understood as being within 10%, 9%, 8%, 7%, 6%, 5%, 4%, 3%, 2%, 1%, 0.5%, 0.1%, 0.05%, or 0.01% of said value.

[0047] In the following, some embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. Throughout the drawings, the same reference numerals will be used to denote the same or equivalent elements. Furthermore, detailed descriptions of well-known features or functions will be omitted so as not to unnecessarily obscure the spirit of the present disclosure.

[0048] Hereinafter, a system and method for performing hemodynamic assessment of aortic stenosis by cardiac computed tomography according to embodiments of the present disclosure will be described with reference to the accompanying drawings.

[0049] Now for reference Figure 1 The present disclosure illustratively depicts a computed tomography (CT) scanner 100 according to various embodiments thereof.

[0050] According to various embodiments, the CT scanner 100 may include a gantry 105, a port 110, and a table / couch 115.

[0051] According to various embodiments, the bed / treatment bed 115 can be configured to support a patient during a CT scan. The bed / treatment bed 115 may include a headrest 120 and / or other components for positioning one or more portions of the patient's body. The bed / treatment bed 120 may be positioned on a base 125. According to various embodiments, the bed / treatment bed 115 can be configured to move, thereby positioning a portion of the patient within an opening 110.

[0052] The gantry 105 may include one or more X-ray generators configured to generate and direct X-rays toward the patient. According to various embodiments, the gantry 105 may be configured to rotate to position the patient within the aperture 110, thereby allowing X-rays to reach the patient at various angles, thus enabling the capture of CT scans.

[0053] A CT scan is an imaging technique that uses a CT scanner 100 to image the internal components of the body. During a CT scan, a series of X-ray images of sections of the body are taken at different angles, allowing a computer to generate a series of internal cross-sectional images of the body.

[0054] CT scans can be performed to image various parts of the body. A cardiac CT scan is a CT scan of the patient's heart. Cardiac CT scans are routinely performed to assess the aortic valve annulus size during transcatheter aortic valve implantation (TAVIER).

[0055] While echocardiography can be used to quantify the dimensionless index (DI) derived from Doppler, cardiac CT scans can be used to derive the anatomical DI based on the continuity formula according to Formula 1. Mathematical Formula 1 Mathematical formula 2

[0056] Formula 1 is similar to Formula 2, where VTI is the Doppler velocity-time integral (VTI) quantified by echocardiography, and LVOT is the left ventricular outflow tract.

[0057] According to various embodiments, cardiac CT scans can be used to derive anatomical dissection (DI) using aortic circle measurements derived from cardiac CT, rather than the LVOT area derived from CT, with results similar to, for example... Figures 2A-2C As shown. For example, in... Figures 2A-2CIn this work, orthogonal stretched views from test CT scans are illustrated, according to various embodiments of the present disclosure.

[0058] like Figure 2A As shown, an orthogonal stretched view of the ascending aorta and the aortic root is illustrated, along with a corresponding vertical plane showing the tip of the aortic valve. Figure 2A In this study, the aortic valve area (AVA) was measured to be 0.96 cm². 2 ,equal .

[0059] like Figure 2B As shown, an orthogonal stretched view of the ascending aorta and the aortic root is illustrated, along with the corresponding vertical plane showing the aortic valve annulus. Figure 2B middle, The measured length is 3.74 cm. 2 .

[0060] like Figure 2C As shown, an orthogonal stretched view of the ascending aorta and the aortic root is illustrated, along with the corresponding vertical plane showing the aortic valve annulus. Figure 2C In China, the area of ​​LVOT The measured value is 2.94 cm. 2 .

[0061] According to various embodiments, the DI derived from the aortic valve annulus can be obtained using mathematical formula 3. . Mathematical Formula 3

[0062] use Figures 2A-2B The exemplary measurements obtained, DI derived from the aortic valve annulus, It was calculated as 0.26 .

[0063] According to various embodiments, the DI derived from LVOT can be obtained using mathematical formula 4. . Mathematical expression 4

[0064] Used in Figure 2A and Figure 2C The example measurements obtained, DI exported from LVOT, It was calculated as 0.33 .

[0065] According to various embodiments, cardiac CT scans can be used to demonstrate and and The relationship between the mean pressure gradient on echocardiography and the overall assessment of AS is used to provide a comprehensive evaluation.

[0066] A retrospective analysis of cardiac CT scans and systolic images was performed (n=86), quantifying the maximum AVA and DI, and reviewing echocardiographic results. Statistical analyses included descriptive measures, regression, and correlation analyses.

[0067] A retrospective analysis was performed on a group of individuals with a mean age of 73 ± 14 years, of whom 53% were male. It is 2±1.3cm 2 Using aortic valve annulus It is 0.40±0.21, similar to... The derived value is 0.42±0.22.

[0068] Echocardiography showed a left ventricular ejection fraction (LVEF) of 57±11% and an arterial velocity (AVA) of 1.48±1.09 cm. 2 The average gradient was 29.6±19.8 mmHg, and the DI was 0.41±0.26. Similar to ,but Significantly higher than .

[0069] and and and Significantly correlated, among which They are equal to 0.94 and 0.85 respectively. Moderately correlated with the mean aortic valve gradient. This suggests that mathematical formula 5 can be used to... Estimate the mean gradient of the aorta. Mathematical formula 5

[0070] according to Figure 6 , yes .

[0071] Data shows that and It provides a comprehensive assessment of the severity of aortic stenosis (AS), similar to an echocardiographic assessment. AS refers to the gradual hardening of the aortic valve. The aortic valve is the area of ​​the body through which the heart pumps blood. This hardening that occurs in AS narrows the aortic valve, reducing or impairing the heart's ability to pump blood through it.

[0072] According to various embodiments, when Less than 1.3cm 2 and A score less than 0.25 indicates an acute syndrome (AS) that is considered severe (a level of severe severity). These values ​​generally correspond to a score less than 1.0 cm. 2 of Less than 0.25 And an echocardiographic mean pressure gradient greater than 40 mmHg. According to various embodiments, when… Roughly 1.3cm 2 and 2.0cm 2 Between and Generally, an AS score between 0.25 and 0.45 can be considered moderate (moderate severity). These values ​​roughly correspond to a score of approximately 1 cm. 2 and 1.5cm 2 Between It is roughly between 0.25 and 0.50. The mean echocardiographic pressure gradient is generally between 20 mmHg and 40 mmHg. However, it should be noted that other values ​​for determining the severity level of AS may be incorporated while maintaining the spirit and function of this disclosure.

[0073] For example, as shown in Table 1, echocardiography, CT (using LVOT), and CT (using aortic annulus) can be used to determine DI, mean aortic valve pressure gradient (mmHg), and aortic valve area (AVA) (cm). 2 Generally, an increase in the mean aortic valve pressure gradient and / or a decrease in the aortic valve amplitude (AVA) indicate an increase in the severity of aortic aortic syndrome (AS). Table 1

[0074] As shown in Table 1, the CT and echocardiograms are consistent, indicating severe AS in the patients shown in Table 1.

[0075] Aortic mean gradient derived from echocardiography, and This is the current reference standard for non-invasive assessment of AS severity. However, echocardiographic assessment depends on the acoustic window and the ability to obtain Doppler-derived velocity measurements parallel to the flow direction, which can be difficult to obtain. CT is not constrained by these limitations because it provides 3D time-resolved spatial data independent of the acoustic window. Therefore, using CT technology to quantify the AS severity of this disclosure is superior to existing techniques, systems, and skills in assessing patients with poor acoustic windows, and is an improvement upon existing techniques, systems, and skills because it is not limited by the acoustic window and the ability to obtain Doppler-derived velocity measurements parallel to the flow direction, addressing a long-standing need in analyzing AS severity in patients with poor acoustic windows.

[0076] Additionally, echocardiography may contain measurement errors in the LVOT area derived from echocardiography, as well as errors in the velocity gradient across the LVOT and aortic valve. This can lead to conflicting values ​​for aortic valve severity based on the estimated mean gradient and the calculated aortic valve area. However, in CT-derived planar aortic valve area, the annular area and LVOT area are consistent and accurate, and the data indicate... The ability to correlate with echocardiographic AVA and estimate aortic gradient provides another improvement to existing techniques, systems, and skills. This allows the CT techniques of this disclosure to complement echocardiographic techniques.

[0077] Despite severe aortic stenosis, some patients present with a low aortic gradient (and are labeled as having low-flow, low-gradient aortic stenosis). Assessing these patients is challenging. The CT technique of this disclosure allows for the assessment of these patients and complements echocardiography. Furthermore, the CT technique of this disclosure can be used to determine the severity of patients who have undergone prosthetic aortic valve implantation. Assessment of these patients is often difficult due to limited acoustic windows and reverberation artifacts that typically accompany echocardiography. However, because the CT technique of this disclosure is not hindered by limited acoustic windows and reverberation artifacts, it again demonstrates superiority over existing techniques and methods.

[0078] According to various embodiments, the techniques of this disclosure can be extended to other heart valves, such as, but not limited to, the mitral valve, pulmonary valve, and tricuspid valve, to assess valvular heart disease. Additionally, according to various embodiments, the techniques of this disclosure can be extended to assess patients with hypertrophic cardiomyopathy (patients with thickened myocardium who have an increasing gradient on LVOT).

[0079] According to various embodiments, artificial intelligence (AI) can be incorporated into methods for estimating aortic pressure and aortic valve area. This will allow for qualitative and quantitative assessment of AS severity, similar to the methods outlined above. Another advantage of this technology is the ability to embed AI algorithms into scanners for triage of patients suspected of having aortic stenosis.

[0080] exist Figures 3-6 Examples illustrating various relationships between echocardiography and cardiac CT scans are provided.

[0081] like Figure 3 As shown, according to an embodiment of the present disclosure, a graphical representation illustrating the relationship between the AVA of cardiac CT scans and the AVA of echocardiography is depicted.

[0082] like Figure 4As shown, according to an embodiment of the present disclosure, a graphical representation illustrating the relationship between the DI of a cardiac CT scan and the DI (echo dimensionless index or EDI) of an echocardiogram is presented.

[0083] like Figure 5 As shown, according to an embodiment of the present disclosure, a graphical representation illustrating the relationship between echocardiographic DI and the mean pressure gradient (aortic valve mean gradient or AVMG) is depicted.

[0084] like Figure 6 As shown, according to an embodiment of the present disclosure, a graphical representation illustrating the relationship between the DI of a cardiac CT scan and the mean pressure gradient of an echocardiogram is presented.

[0085] Now for reference Figure 7 The present invention provides an illustration of an example architecture of a computing device 700. According to an exemplary embodiment, one or more functions of this disclosure may be implemented by a computing device, such as, for example, computing device 700 or a computing device similar to computing device 700.

[0086] Figure 7 The hardware architecture represents an example implementation of a representative computing device configured to perform one or more methods and apparatuses for hemodynamic assessment of aortic stenosis via cardiac computed tomography, as described herein. Therefore, Figure 7 The computing device 700 can be configured to implement at least a portion of the methods described herein and / or implement the systems described herein (e.g., Figure 1 At least a portion of the functionality of a CT scanner 100. According to various embodiments, Figure 1 The CT scanner 100 may include one or more computing devices 700. According to various embodiments, the computing device 700 may be configured to cause the CT scanner 100 to perform one or more CT scans (e.g., cardiac CT scans).

[0087] Some or all of the components of the computing device 700 may be implemented as hardware, software, and / or a combination of hardware and software. Hardware may include, but is not limited to, one or more electronic circuits. Electronic circuits may include, but are not limited to, passive components (e.g., resistors and capacitors) and / or active components (e.g., amplifiers and / or microprocessors). Passive and / or active components may be adapted, arranged, and / or programmed to perform one or more of the methods, processes, or functions described herein.

[0088] like Figure 7As shown, computing device 700 may include a user interface 702, a central processing unit (“CPU”) 706, a system bus 710, a memory 712 connected to and accessible by other parts of computing device 700 via the system bus 710, and a hardware entity 714 connected to the system bus 710. The user interface may include input and output devices configured to facilitate user-software interaction for controlling the operation of computing device 700. Input devices may include, but are not limited to, a physical and / or touch keyboard 740. Input devices may be connected to computing device 700 via a wired or wireless connection (e.g., a Bluetooth® connection). Output devices may include, but are not limited to, a speaker 742, a display 744, and / or a light-emitting diode 746.

[0089] At least some of the hardware entities 714 may be configured to perform actions involving accessing and using memory 712, which may be random access memory (RAM), a disk drive and / or optical disc read-only memory (CD-ROM), and other suitable memory types. Hardware entity 714 may include a disk drive unit 816 that includes a computer-readable storage medium 718 on which one or more sets of instructions 720 (e.g., programming instructions, such as, but not limited to, software code) configured to implement one or more of the methods, processes, or functions described herein may be stored. The instructions 720 may also reside wholly or at least partially within memory 712 and / or CPU 706 during execution by computing device 700.

[0090] The memory 712 and CPU 706 may also constitute a machine-readable medium. As used herein, the term "machine-readable medium" refers to a single or multiple media (e.g., a centralized or distributed database and / or associated caches and servers) that store one or more sets of instructions 720. The term "machine-readable medium" as used herein also refers to any medium capable of storing, encoding, or carrying a set of instructions 720 for execution by the computing device 700 and causing the computing device 700 to perform any one or more methods of this disclosure. According to various embodiments, one or more computer application programs 724 may be stored on the memory 712.

[0091] The above-described features and functions, as well as alternatives, can be combined into many other different systems or applications. Various substitutions, modifications, variations, or improvements can be made by those skilled in the art, each of which is intended to be covered by the disclosed embodiments.

Claims

1. A method for performing hemodynamic assessment of aortic stenosis via cardiac computed tomography (CT) scan, comprising: A cardiac CT scan of the patient was performed using a CT scanner. The CT scanner includes: A rack, including one or more X-ray generators; The bed was configured to support the patient; and Computing devices, including processors and memory; and Using the computing device: Determined via the CT scan: The patient's aortic valve area ( );and The patient's left ventricular outflow tract area ( ); Based on the aortic valve area ( ) and the area of ​​the left ventricular outflow tract ( ) Calculate the dimensionless index of anatomy ( );and Based on the aortic valve area ( The area of ​​the left ventricular outflow tract ( ) and the anatomical dimensionless index ( Determine the severity of the patient's aortic stenosis (AS).

2. The method according to claim 1, wherein, according to Calculate the dimensionless index of the anatomy .

3. The method according to claim 1, wherein, when Less than 1.3cm 2 and When the value is less than 0.25, the severity level of the patient's AS is defined as severe.

4. The method according to claim 1, wherein, when At 1.3cm 2 With 2.0cm 2 Between and When the value is between 0.25 and 0.45, the severity of the patient's AS is defined as moderate.

5. The method of claim 1, further comprising using the computing device to calculate the mean aortic valve gradient according to the following mathematical formula: ， in x Equal to the dimensionless index of anatomy ( ).

6. A system for performing hemodynamic assessment of aortic stenosis via cardiac computed tomography (CT) scan, comprising: A CT scanner configured to perform a cardiac CT scan of a patient, wherein the CT scanner includes: A rack, including one or more X-ray generators; and The bed was configured to support the patient; and A computing device, including a processor and a memory, wherein the computing device is configured to: Determined via the CT scan: The patient's aortic valve area ( );and The patient's left ventricular outflow tract area ( ); Based on the aortic valve area ( ) and the area of ​​the left ventricular outflow tract ( ) Calculate the dimensionless index of anatomy ( );and Based on the aortic valve area ( The area of ​​the left ventricular outflow tract ( ) and the anatomical dimensionless index ( Determine the severity of the patient's aortic stenosis (AS).

7. The system according to claim 6, wherein, The computing device is configured to according to Calculate the dimensionless index of the anatomy .

8. The system according to claim 6, wherein, when Less than 1.3cm 2 and When the value is less than 0.25, the severity level of the patient's AS is defined as severe.

9. The system according to claim 6, wherein, when At 1.3cm 2 With 2.0cm 2 Between and When the value is between 0.25 and 0.45, the severity of the patient's AS is defined as moderate.

10. The system according to claim 6, wherein, The computing device is configured to calculate the average aortic valve gradient according to the following mathematical formula: ， in x Equal to the dimensionless index of anatomy ( ).

11. The system according to claim 6, wherein, The frame forms holes through which one or more portions of the patient can pass.

12. The system according to claim 11, wherein, The bed is configured to allow one or more parts of the patient to move through the opening.

13. The system according to claim 6, wherein, The computing device is configured to cause the CT scanner to perform a cardiac CT scan on the patient.

14. A system for performing hemodynamic assessment of aortic stenosis via cardiac computed tomography (CT) scan, comprising: A CT scanner configured to perform a cardiac CT scan of a patient, wherein the CT scanner includes: A rack, including one or more X-ray generators; and The bed was configured to support the patient; and A computing device includes a processor and a memory, wherein the memory is configured to store programming instructions that, when executed by the processor, are configured to cause the processor to: Determined via the CT scan: The patient's aortic valve area ( );and The patient's left ventricular outflow tract area ( ); Based on the aortic valve area ( ) and the area of ​​the left ventricular outflow tract ( ) Calculate the dimensionless index of anatomy ( );and Based on the aortic valve area ( The area of ​​the left ventricular outflow tract ( ) and the anatomical dimensionless index ( Determine the severity of the patient's aortic stenosis (AS).

15. The system according to claim 14, wherein, The programming instructions, when executed by the processor, are also configured to cause the processor to, according to Calculate the dimensionless index of the anatomy .

16. The system according to claim 14, wherein, The programming instructions, when executed by the processor, are also configured to cause the processor to: when Less than 1.3cm 2 and When the value is less than 0.25, the severity level of the patient's AS is defined as severe.

17. The system according to claim 14, wherein, The programming instructions, when executed by the processor, are also configured to cause the processor to: when At 1.3cm 2 With 2.0cm 2 Between and When the value is between 0.25 and 0.45, the severity of the patient's AS is defined as moderate.

18. The system according to claim 14, wherein, The programming instructions, when executed by the processor, are also configured to cause the processor to calculate the average aortic valve gradient according to the following mathematical formula: ， in x Equal to the dimensionless index of anatomy ( ).

19. The system according to claim 14, wherein, The frame forms holes through which one or more portions of the patient can pass.

20. The system according to claim 14, wherein, The programming instructions, when executed by the processor, are also configured to cause the processor to perform a cardiac CT scan of the patient.

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