Method and device for determining blood flow reserve fraction, electronic equipment and storage medium

Abstract

The application discloses a blood flow reserve fraction determination method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring a coronary angiography image containing a target blood vessel segment, generating an initial three-dimensional blood vessel model of the target blood vessel segment based on the coronary angiography image, and determining first key point information of the target blood vessel segment based on the initial three-dimensional blood vessel model; acquiring an optical coherence tomography image containing the target blood vessel segment, and determining second key point information of the target blood vessel segment based on the optical coherence tomography image; determining a model scaling coefficient based on the first key point information and the second key point information, scaling the initial three-dimensional blood vessel model based on the model scaling coefficient, and obtaining a target three-dimensional blood vessel model; and determining the blood flow reserve fraction based on the target three-dimensional blood vessel model. The above technical solution introduces the optical coherence tomography image, corrects the three-dimensional blood vessel model, improves the accuracy of the three-dimensional blood vessel model, and further improves the accuracy of the blood flow reserve fraction.

Description

Technical Field

[0001] This invention relates to the field of image processing technology, and in particular to a method, apparatus, electronic device, and storage medium for determining fractional blood flow reserve. Background Technology

[0002] Fractional flow reserve (FFR) has become the gold standard for assessing myocardial ischemia. Clinically, methods for obtaining FFR include invasive and non-invasive methods.

[0003] In the process of realizing this invention, the inventors discovered that at least the following technical problems exist in the prior art: the existing methods for obtaining fractional blood flow reserve have the problem of inaccurate fractional blood flow reserve. Summary of the Invention

[0004] This invention provides a method, apparatus, electronic device, and storage medium for determining fractional flow reserve, in order to improve the accuracy of fractional flow reserve.

[0005] According to one aspect of the present invention, a method for determining fractional flow reserve is provided, comprising:

[0006] Acquire a coronary angiography image containing the target vessel segment, generate an initial three-dimensional vessel model of the target vessel segment based on the coronary angiography image, and determine the first key point information of the target vessel segment based on the initial three-dimensional vessel model;

[0007] Acquire an optical coherence tomography (OCT) image containing the target vascular segment, and determine the second key point information of the target vascular segment based on the OCT image;

[0008] Based on the first key point information and the second key point information, a model scaling factor is determined, and the initial three-dimensional blood vessel model is scaled based on the model scaling factor to obtain the target three-dimensional blood vessel model.

[0009] The fractional blood flow reserve is determined based on the target three-dimensional vascular model.

[0010] According to another aspect of the present invention, an apparatus for determining fractional blood flow reserve is provided, comprising:

[0011] The first key point information determination module is used to acquire a coronary angiography image containing the target vessel segment, generate an initial three-dimensional vessel model of the target vessel segment based on the coronary angiography image, and determine the first key point information of the target vessel segment based on the initial three-dimensional vessel model.

[0012] The second key point information determination module is used to acquire an optical coherence tomography image containing the target blood vessel segment, and determine the second key point information of the target blood vessel segment based on the optical coherence tomography image.

[0013] A three-dimensional blood vessel model scaling module is used to determine the model scaling factor based on the first key point information and the second key point information, and to scale the initial three-dimensional blood vessel model based on the model scaling factor to obtain the target three-dimensional blood vessel model.

[0014] The fractional flow reserve determination module is used to determine the fractional flow reserve based on the target three-dimensional vascular model.

[0015] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0016] At least one processor;

[0017] and a memory communicatively connected to the at least one processor;

[0018] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the method for determining the fractional blood flow reserve as described in any embodiment of the present invention.

[0019] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the method for determining the fractional blood flow reserve as described in any embodiment of the present invention.

[0020] The technical solution of this invention involves acquiring a coronary angiography image containing a target vessel segment, generating an initial three-dimensional vessel model of the target vessel segment based on the coronary angiography image, and then determining the first key point information of the target vessel segment based on the initial three-dimensional vessel model. Further, it involves acquiring an optical coherence tomography image containing the target vessel segment, and then determining the second key point information of the target vessel segment based on the optical coherence tomography image. Further, it involves determining a model scaling factor based on the first and second key point information, and then scaling the initial three-dimensional vessel model according to the model scaling factor to obtain the target three-dimensional vessel model. This achieves the correction of the three-dimensional vessel model, improving its accuracy. Finally, it determines the fractional flow reserve based on the corrected target three-dimensional vessel model, improving the accuracy of the fractional flow reserve.

[0021] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a flowchart of a method for determining fractional blood flow reserve according to Embodiment 1 of the present invention;

[0024] Figure 2 This is a schematic diagram of a three-dimensional blood vessel model reconstruction according to an embodiment of the present invention;

[0025] Figure 3 This is a flowchart of a method for determining fractional blood flow reserve according to Embodiment 2 of the present invention;

[0026] Figure 4 This is a flowchart of a method for determining fractional blood flow reserve according to Embodiment 3 of the present invention;

[0027] Figure 5 This is a schematic diagram of a device for determining fractional blood flow reserve according to Embodiment 4 of the present invention;

[0028] Figure 6 This is a schematic diagram of the structure of an electronic device that implements the method for determining the fractional blood flow reserve according to embodiments of the present invention. Detailed Implementation

[0029] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0030] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be used interchangeably where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or device that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or devices. The acquisition, storage, use, and processing of data in the technical solutions of this application all comply with the relevant provisions of national laws and regulations.

[0031] Example 1

[0032] Figure 1 This is a flowchart of a method for determining fractional flow reserve (FVR) according to Embodiment 1 of the present invention. This embodiment is applicable to situations where FVR is determined based on multimodal data. The method can be executed by a FVR determination device, which can be implemented in hardware and / or software and can be configured in electronic devices such as terminals or servers. Figure 1 As shown, the method includes:

[0033] S110. Obtain a coronary angiography image containing the target vessel segment, generate an initial three-dimensional vessel model of the target vessel segment based on the coronary angiography image, and determine the first key point information of the target vessel segment based on the initial three-dimensional vessel model.

[0034] In this embodiment, coronary angiography images refer to medical image data containing target vessel segments, and there can be multiple such images. The target vessel segment refers to a coronary artery with stenosis.

[0035] Specifically, multiple coronary angiography images containing the target vessel segment can be reconstructed to obtain an initial three-dimensional vessel model of the target vessel segment.

[0036] Optionally, acquiring coronary angiography images containing the target vessel segment includes: acquiring coronary angiography images containing the target vessel segment from at least two angles; correspondingly, generating an initial three-dimensional vessel model of the target vessel segment based on the coronary angiography images includes: annotating the coronary angiography images containing the target vessel segment from at least two angles to obtain vessel contour images containing the target vessel segment from at least two angles; and generating an initial three-dimensional vessel model based on the vessel contour images containing the target vessel segment from at least two angles.

[0037] For example, a coronary angiography image containing the target vessel segment at a first angle and a coronary angiography image containing the target vessel segment at a second angle are obtained from a preset storage path. The first angle and the second angle can differ by more than or equal to 25 degrees. Further, the coronary angiography images containing the target vessel segment at the first angle and the coronary angiography images containing the target vessel segment at the second angle are annotated to obtain a vessel contour image at the first angle. Figure 2 Top left) and second angle blood vessel contour images ( Figure 2 (Lower left), and then, based on the image morphology imaging method, an initial three-dimensional blood vessel model is generated from the blood vessel contour images at the first angle and the second angle. Figure 2 right).

[0038] In this embodiment, the first key point information refers to the information associated with key points in the initial three-dimensional blood vessel model. This information can be length or area, etc., and is not specifically limited here. Key points may include, but are not limited to, the location of the blood vessel opening, the location of the blood vessel bifurcation, and the narrowest point of the blood vessel.

[0039] Specifically, the first key point information of the initial three-dimensional vascular model can be obtained by measuring software measurement tools or other measurement methods.

[0040] S120. Acquire an optical coherence tomography (OCT) image containing the target vascular segment, and determine the second key point information of the target vascular segment based on the OCT image.

[0041] In this embodiment, the optical coherence tomography (OCT) image refers to an image containing the target blood vessel segment, and there can be multiple such images. The second key point information refers to information associated with key points in the OCT image, which can be information such as length or area, and is not specifically limited here. It should be noted that the key points in the OCT image and the key points in the initial 3D blood vessel model can correspond one-to-one, meaning the key points in both models represent the same blood vessel location.

[0042] For example, multiple optical coherence tomography (OCT) images containing the target vascular segment can be obtained from a preset storage path, and then the second key point information of the OCT images can be measured by software measurement tools or other measurement methods.

[0043] S130. Determine the model scaling factor based on the first key point information and the second key point information, and scale the initial three-dimensional blood vessel model based on the model scaling factor to obtain the target three-dimensional blood vessel model.

[0044] In this embodiment, the ratio of the first key point information to the second key point information can be used as the model scaling factor. The initial three-dimensional blood vessel model can then be scaled based on the scaling factor, thereby correcting the three-dimensional blood vessel model and improving its accuracy.

[0045] S140. Determine the fractional blood flow reserve based on the target three-dimensional vascular model.

[0046] In this embodiment, the fractional flow reserve is determined based on the corrected three-dimensional vascular model, which improves the accuracy of the fractional flow reserve.

[0047] The technical solution of this invention involves acquiring a coronary angiography image containing a target vessel segment, generating an initial three-dimensional vessel model of the target vessel segment based on the coronary angiography image, and then determining the first key point information of the target vessel segment based on the initial three-dimensional vessel model. Further, it involves acquiring an optical coherence tomography image containing the target vessel segment, and then determining the second key point information of the target vessel segment based on the optical coherence tomography image. Further, it involves determining a model scaling factor based on the first and second key point information, and then scaling the initial three-dimensional vessel model according to the model scaling factor to obtain the target three-dimensional vessel model. This achieves the correction of the three-dimensional vessel model, improving its accuracy. Finally, it determines the fractional flow reserve based on the corrected target three-dimensional vessel model, improving the accuracy of the fractional flow reserve.

[0048] Example 2

[0049] Figure 3This is a flowchart of a method for determining the fractional blood flow reserve (FVRRR) according to Embodiment 2 of the present invention. The method in this embodiment can be combined with various optional schemes in the FVRRR determination methods provided in the above embodiments. The FVRRR determination method provided in this embodiment has been further optimized. Optionally, the first key point information includes the distance between the beginning and end key points of the target vessel segment in the initial three-dimensional vascular model and the vessel cross-sectional area corresponding to multiple key points on the target vessel segment in the initial three-dimensional vascular model; the second key point information includes the distance between the beginning and end key points of the target vessel segment in the optical coherence tomography (OCT) image and the vessel cross-sectional area corresponding to multiple key points on the target vessel segment in the OCT image; correspondingly, the model scaling factor is determined based on the first key point information and the second key point information, and the initial three-dimensional vascular model is then scaled based on the model scaling factor. The process of scaling to obtain a target three-dimensional blood vessel model includes: determining a length scaling factor based on the distance between the beginning and end key points of the target blood vessel segment in the initial three-dimensional blood vessel model and the distance between the beginning and end key points of the target blood vessel segment in the optical coherence tomography (OCT) image; determining an area scaling factor based on the cross-sectional areas of the blood vessels corresponding to multiple key points on the target blood vessel segment in the initial three-dimensional blood vessel model and the cross-sectional areas of the blood vessels corresponding to multiple key points on the target blood vessel segment in the OCT image; and scaling the initial three-dimensional blood vessel model based on the length scaling factor and the area scaling factor to obtain the target three-dimensional blood vessel model.

[0050] like Figure 3 As shown, the method includes:

[0051] S210. Obtain a coronary angiography image containing the target vessel segment, generate an initial three-dimensional vessel model of the target vessel segment based on the coronary angiography image, and determine the first key point information of the target vessel segment based on the initial three-dimensional vessel model. The first key point information includes the distance between the key point at the beginning of the target vessel segment and the key point at the end of the target vessel segment in the initial three-dimensional vessel model, and the vessel cross-sectional area corresponding to multiple key points on the target vessel segment in the initial three-dimensional vessel model.

[0052] S220. Obtain an optical coherence tomography (OCT) image containing the target blood vessel segment, and determine second key point information of the target blood vessel segment based on the OCT image. The second key point information includes the distance between the key point at the beginning of the target blood vessel segment and the key point at the end of the target blood vessel segment in the OCT image, and the cross-sectional area of ​​the blood vessel corresponding to multiple key points on the target blood vessel segment in the OCT image.

[0053] S230. Determine the length scaling factor based on the distance between the key point at the beginning and the key point at the end of the target blood vessel segment in the initial three-dimensional blood vessel model and the distance between the key point at the beginning and the key point at the end of the target blood vessel segment in the optical coherence tomography image.

[0054] For example, the ratio of the distance between the beginning key point and the end key point of the target blood vessel segment in the initial three-dimensional blood vessel model to the distance between the beginning key point and the end key point of the target blood vessel segment in the optical coherence tomography image can be used as the length scaling factor.

[0055] S240. Determine the area scaling factor based on the cross-sectional area of ​​the blood vessel corresponding to multiple key points on the target blood vessel segment in the initial three-dimensional blood vessel model and the cross-sectional area of ​​the blood vessel corresponding to multiple key points on the target blood vessel segment in the optical coherence tomography image.

[0056] For example, the number of key points can be n. The cross-sectional areas of the blood vessels corresponding to multiple key points on the target blood vessel segment in the initial three-dimensional blood vessel model are denoted as S1, S2...Sn; the cross-sectional areas of the blood vessels corresponding to multiple key points on the target blood vessel segment in the optical coherence tomography image are denoted as S1', S2'...Sn'; further, the ratio of the n key points can be R1, R2...Rn; where Rn=Sn / Sn'; further, the area scaling factor=(R1+R2+...+Rn) / n.

[0057] S250. The initial three-dimensional blood vessel model is scaled based on the length scaling factor and the area scaling factor to obtain the target three-dimensional blood vessel model.

[0058] Specifically, the initial three-dimensional blood vessel model is scaled in both length and area by using length scaling factor and area scaling factor, thereby improving the accuracy of the three-dimensional blood vessel model.

[0059] S260. Determine the fractional blood flow reserve based on the target three-dimensional vascular model.

[0060] The technical solution of this invention improves the accuracy of the three-dimensional blood vessel model by scaling the length and area of ​​the initial three-dimensional blood vessel model as a whole through length scaling factor and area scaling factor.

[0061] Example 3

[0062] Figure 4This is a flowchart of a method for determining the fractional flow reserve (FVR) according to Embodiment 3 of the present invention. The method in this embodiment can be combined with various optional schemes in the methods for determining the FVR provided in the above embodiments. The method for determining the FVR provided in this embodiment has been further optimized. Optionally, determining the FVR based on the target three-dimensional vascular model includes: determining the pressure drop of the target vascular segment of the target three-dimensional vascular model; and determining the FVR based on the pressure drop of the target vascular segment of the target three-dimensional vascular model.

[0063] like Figure 4 As shown, the method includes:

[0064] S310. Obtain a coronary angiography image containing the target vessel segment, generate an initial three-dimensional vessel model of the target vessel segment based on the coronary angiography image, and determine the first key point information of the target vessel segment based on the initial three-dimensional vessel model.

[0065] S320. Acquire an optical coherence tomography (OCT) image containing the target vascular segment, and determine the second key point information of the target vascular segment based on the OCT image.

[0066] S330. Determine the model scaling factor based on the first key point information and the second key point information, and scale the initial three-dimensional blood vessel model based on the model scaling factor to obtain the target three-dimensional blood vessel model.

[0067] S340. Determine the pressure drop of the target vascular segment in the target three-dimensional vascular model.

[0068] In this embodiment, the pressure drop of the target blood vessel segment can be calculated using pressure drop calculation formulas or computational fluid dynamics simulations, and no specific limitation is made here.

[0069] Optionally, determining the target vascular segment pressure drop of the target three-dimensional vascular model includes: determining the vascular viscous resistance coefficient, vascular inertial resistance coefficient, and vascular flow rate of the target three-dimensional vascular model; and determining the target vascular segment pressure drop of the target three-dimensional vascular model based on the vascular viscous resistance coefficient, vascular inertial resistance coefficient, and the vascular flow rate.

[0070] For example, the formula for calculating the pressure drop in the target vascular segment is as follows:

[0071] ΔP=C1×Q+C2×Q 2 ;

[0072] Where ΔP represents the pressure drop in the target vascular segment, C1 represents the vascular viscous resistance coefficient, C2 represents the vascular inertial resistance coefficient, and Q represents the vascular flow rate. K1 represents the coefficient related to blood vessel diameter, μ is the blood viscosity coefficient, d0 represents blood vessel diameter, and A0 represents blood vessel area; ρ represents blood density, A s k represents the area of ​​the narrowed blood vessel. e This represents a coefficient with a value range of 0.8-1.4; Q = αV m β Where α and β are empirical coefficients, with α ranging from 1.2 to 1.5 and β ranging from 0.5 to 1.5, V m Indicates the volume of blood vessels.

[0073] Optionally, determining the pressure drop of the target vascular segment in the target three-dimensional vascular model includes: performing computational fluid dynamics simulation on the target three-dimensional vascular model to obtain the pressure drop of the target vascular segment in the target three-dimensional vascular model.

[0074] In this embodiment, the core of the computational fluid dynamics simulation is solving the Navier-Stokes equations. For example, the Navier-Stokes equations include the continuity equation and the momentum equation, as follows:

[0075] Continuity equation:

[0076]

[0077] Momentum equation:

[0078]

[0079] Where u, v, and w represent the velocity components in the three directions, x, y, and z represent the coordinate components in the three directions of any point in the target three-dimensional blood vessel model, t represents time, U represents the velocity vector, div represents the divergence, which is used to characterize the strength of the vector field divergence at each point in space, τ represents shear stress, ρ represents blood density, p represents pressure, and Fx, Fy, and Fz represent the volume forces in the three directions.

[0080] By solving the Navier-Stokes equations, the pressure and velocity at each point in the target three-dimensional blood vessel model at any given time can be obtained. Thus, the pressure drop of the target blood vessel segment can be calculated based on the pressure and velocity at each point in the target three-dimensional blood vessel model.

[0081] S350. Determine the fractional blood flow reserve based on the pressure drop of the target vascular segment in the target three-dimensional vascular model.

[0082] Specifically, the mean pressure at the coronary artery inlet can be obtained; the fractional flow reserve can be determined based on the mean pressure at the coronary artery inlet and the pressure drop of the target vessel segment in the target three-dimensional vessel model.

[0083] For example, the formula for calculating fractional flow reserve is as follows:

[0084]

[0085] Among them, P a This represents the average pressure at the coronary artery inlet, which can be measured using a pressure guidewire.

[0086] The technical solution of this invention calculates the pressure drop of the target blood vessel segment using a pressure drop calculation formula or computational fluid dynamics simulation, and then determines the fractional flow reserve based on the pressure drop of the target blood vessel segment. Compared with the prior art, the pressure drop is considered when calculating the fractional flow reserve, thereby improving the accuracy of the fractional flow reserve.

[0087] Example 4

[0088] Figure 5 This is a schematic diagram of a device for determining the fractional blood flow reserve provided in Embodiment 4 of the present invention. Figure 5 As shown, the device includes:

[0089] The first key point information determination module 410 is used to acquire a coronary angiography image containing the target vessel segment, generate an initial three-dimensional vessel model of the target vessel segment based on the coronary angiography image, and determine the first key point information of the target vessel segment based on the initial three-dimensional vessel model.

[0090] The second key point information determination module 420 is used to acquire an optical coherence tomography image containing the target blood vessel segment, and determine the second key point information of the target blood vessel segment based on the optical coherence tomography image.

[0091] The three-dimensional blood vessel model scaling module 430 is used to determine the model scaling factor based on the first key point information and the second key point information, and to scale the initial three-dimensional blood vessel model based on the model scaling factor to obtain the target three-dimensional blood vessel model.

[0092] The fractional blood flow reserve determination module 440 is used to determine the fractional blood flow reserve based on the target three-dimensional vascular model.

[0093] The technical solution of this invention involves acquiring a coronary angiography image containing a target vessel segment, generating an initial three-dimensional vessel model of the target vessel segment based on the coronary angiography image, and then determining the first key point information of the target vessel segment based on the initial three-dimensional vessel model. Further, it involves acquiring an optical coherence tomography image containing the target vessel segment, and then determining the second key point information of the target vessel segment based on the optical coherence tomography image. Further, it involves determining a model scaling factor based on the first and second key point information, and then scaling the initial three-dimensional vessel model according to the model scaling factor to obtain the target three-dimensional vessel model. This achieves the correction of the three-dimensional vessel model, improving its accuracy. Finally, it determines the fractional flow reserve based on the corrected target three-dimensional vessel model, improving the accuracy of the fractional flow reserve.

[0094] In some optional implementations, the first key point information includes the distance between the key point at the beginning and the key point at the end of the target blood vessel segment in the initial three-dimensional blood vessel model, and the cross-sectional area of ​​the blood vessel corresponding to each of the multiple key points on the target blood vessel segment in the initial three-dimensional blood vessel model; the second key point information includes the distance between the key point at the beginning and the key point at the end of the target blood vessel segment in the optical coherence tomography (OCT) image, and the cross-sectional area of ​​the blood vessel corresponding to each of the multiple key points on the target blood vessel segment in the OCT image.

[0095] Correspondingly, the 3D blood vessel model scaling module 430 is specifically used for:

[0096] The length scaling factor is determined based on the distance between the key points at the beginning and end of the target blood vessel segment in the initial three-dimensional blood vessel model and the distance between the key points at the beginning and end of the target blood vessel segment in the optical coherence tomography image.

[0097] The area scaling factor is determined based on the cross-sectional area of ​​the blood vessel corresponding to multiple key points on the target blood vessel segment in the initial three-dimensional blood vessel model and the cross-sectional area of ​​the blood vessel corresponding to multiple key points on the target blood vessel segment in the optical coherence tomography image.

[0098] The initial three-dimensional blood vessel model is scaled based on the length scaling factor and the area scaling factor to obtain the target three-dimensional blood vessel model.

[0099] In some optional implementations, the first key point information determination module 410 may be specifically used for:

[0100] Acquire coronary angiography images containing the target vessel segment from at least two angles;

[0101] The coronary angiography images containing the target vessel segment at least two angles are annotated to obtain vessel contour images containing the target vessel segment at least two angles.

[0102] An initial three-dimensional vascular model is generated based on the vascular contour images containing the target vascular segment from at least two angles.

[0103] In some alternative implementations, the fractional flow reserve determination module 440 includes:

[0104] A vessel segment pressure drop determination unit is used to determine the target vessel segment pressure drop of the target three-dimensional vessel model.

[0105] The fractional flow reserve determination unit is used to determine the fractional flow reserve based on the pressure drop of the target vascular segment in the target three-dimensional vascular model.

[0106] In some alternative implementations, the vessel segment pressure drop determination unit may specifically be used for:

[0107] Determine the viscous drag coefficient, vascular inertial drag coefficient, and blood flow rate of the target three-dimensional vascular model;

[0108] The target vascular segment pressure drop of the target three-dimensional vascular model is determined based on the vascular viscous resistance coefficient, the vascular inertial resistance coefficient, and the vascular flow rate.

[0109] In some alternative implementations, the vessel segment pressure drop determination unit may specifically be used for:

[0110] Computational fluid dynamics simulation was performed on the target three-dimensional blood vessel model to obtain the pressure drop of the target blood vessel segment of the target three-dimensional blood vessel model.

[0111] In some alternative implementations, the fractional blood flow reserve determination unit may specifically be used for:

[0112] Obtain the mean pressure at the coronary artery inlet;

[0113] The fractional flow reserve is determined based on the mean pressure at the coronary artery inlet and the pressure drop of the target vessel segment in the target three-dimensional vascular model.

[0114] The fractional flow reserve determination device provided in the embodiments of the present invention can execute the fractional flow reserve determination method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of executing the method.

[0115] Example 5

[0116] Figure 6A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0117] like Figure 6 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded into the RAM 13 from storage unit 18. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An I / O interface 15 is also connected to the bus 14.

[0118] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0119] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as a method for determining the fractional blood flow reserve, which includes:

[0120] Acquire a coronary angiography image containing the target vessel segment, generate an initial three-dimensional vessel model of the target vessel segment based on the coronary angiography image, and determine the first key point information of the target vessel segment based on the initial three-dimensional vessel model;

[0121] Acquire an optical coherence tomography (OCT) image containing the target vascular segment, and determine the second key point information of the target vascular segment based on the OCT image;

[0122] Based on the first key point information and the second key point information, a model scaling factor is determined, and the initial three-dimensional blood vessel model is scaled based on the model scaling factor to obtain the target three-dimensional blood vessel model.

[0123] The fractional blood flow reserve is determined based on the target three-dimensional vascular model.

[0124] In some embodiments, the method for determining fractional flow reserve may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or mounted on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the method for determining fractional flow reserve described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the method for determining fractional flow reserve by any other suitable means (e.g., by means of firmware).

[0125] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), system-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0126] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0127] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0128] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0129] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0130] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0131] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0132] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for determining fractional blood flow reserve, characterized in that, include: Acquire a coronary angiography image containing the target vessel segment, generate an initial three-dimensional vessel model of the target vessel segment based on the coronary angiography image, and determine the first key point information of the target vessel segment based on the initial three-dimensional vessel model; Acquire an optical coherence tomography (OCT) image containing the target vascular segment, and determine the second key point information of the target vascular segment based on the OCT image; Based on the first key point information and the second key point information, a model scaling factor is determined, and the initial three-dimensional blood vessel model is scaled based on the model scaling factor to obtain the target three-dimensional blood vessel model. The fractional blood flow reserve is determined based on the target three-dimensional vascular model. The first key point information includes the distance between the key point at the beginning and the key point at the end of the target blood vessel segment in the initial three-dimensional blood vessel model, and the cross-sectional area of ​​the blood vessel corresponding to each of the multiple key points on the target blood vessel segment in the initial three-dimensional blood vessel model; the second key point information includes the distance between the key point at the beginning and the key point at the end of the target blood vessel segment in the optical coherence tomography image, and the cross-sectional area of ​​the blood vessel corresponding to each of the multiple key points on the target blood vessel segment in the optical coherence tomography image. Accordingly, the step of determining the model scaling factor based on the first key point information and the second key point information, and scaling the initial three-dimensional blood vessel model based on the model scaling factor to obtain the target three-dimensional blood vessel model, includes: The length scaling factor is determined based on the distance between the key points at the beginning and end of the target blood vessel segment in the initial three-dimensional blood vessel model and the distance between the key points at the beginning and end of the target blood vessel segment in the optical coherence tomography image. The area scaling factor is determined based on the cross-sectional area of ​​the blood vessel corresponding to multiple key points on the target blood vessel segment in the initial three-dimensional blood vessel model and the cross-sectional area of ​​the blood vessel corresponding to multiple key points on the target blood vessel segment in the optical coherence tomography image. The initial three-dimensional blood vessel model is scaled based on the length scaling factor and the area scaling factor to obtain the target three-dimensional blood vessel model.

2. The method according to claim 1, characterized in that, The acquisition of coronary angiography images containing the target vessel segment includes: Acquire coronary angiography images containing the target vessel segment from at least two angles; Accordingly, the generation of the initial three-dimensional vascular model of the target vascular segment based on the coronary angiography image includes: The coronary angiography images containing the target vessel segment at least two angles are annotated to obtain vessel contour images containing the target vessel segment at least two angles. An initial three-dimensional vascular model is generated based on the vascular contour images containing the target vascular segment from at least two angles.

3. The method according to claim 1, characterized in that, The determination of fractional blood flow reserve based on the target three-dimensional vascular model includes: Determine the pressure drop of the target vascular segment in the target three-dimensional vascular model; The fractional flow reserve is determined based on the pressure drop of the target vascular segment in the target three-dimensional vascular model.

4. The method according to claim 3, characterized in that, Determining the pressure drop of the target vascular segment in the target three-dimensional vascular model includes: Determine the viscous drag coefficient, vascular inertial drag coefficient, and blood flow rate of the target three-dimensional vascular model; The target vascular segment pressure drop of the target three-dimensional vascular model is determined based on the vascular viscous resistance coefficient, the vascular inertial resistance coefficient, and the vascular flow rate.

5. The method according to claim 3, characterized in that, Determining the pressure drop of the target vascular segment in the target three-dimensional vascular model includes: Computational fluid dynamics simulation was performed on the target three-dimensional blood vessel model to obtain the pressure drop of the target blood vessel segment of the target three-dimensional blood vessel model.

6. The method according to claim 3, characterized in that, The determination of the fractional flow reserve based on the pressure drop of the target vessel segment in the target three-dimensional vascular model includes: Obtain the mean pressure at the coronary artery inlet; The fractional flow reserve is determined based on the mean pressure at the coronary artery inlet and the pressure drop of the target vessel segment in the target three-dimensional vascular model.

7. A device for determining fractional blood flow reserve, characterized in that, include: The first key point information determination module is used to acquire a coronary angiography image containing the target vessel segment, generate an initial three-dimensional vessel model of the target vessel segment based on the coronary angiography image, and determine the first key point information of the target vessel segment based on the initial three-dimensional vessel model. The second key point information determination module is used to acquire an optical coherence tomography image containing the target blood vessel segment, and determine the second key point information of the target blood vessel segment based on the optical coherence tomography image. A three-dimensional blood vessel model scaling module is used to determine the model scaling factor based on the first key point information and the second key point information, and to scale the initial three-dimensional blood vessel model based on the model scaling factor to obtain the target three-dimensional blood vessel model. A fractional flow reserve determination module is used to determine the fractional flow reserve based on the target three-dimensional vascular model. The first key point information includes the distance between the key point at the beginning and the key point at the end of the target blood vessel segment in the initial three-dimensional blood vessel model, and the cross-sectional area of ​​the blood vessel corresponding to each of the multiple key points on the target blood vessel segment in the initial three-dimensional blood vessel model; the second key point information includes the distance between the key point at the beginning and the key point at the end of the target blood vessel segment in the optical coherence tomography image, and the cross-sectional area of ​​the blood vessel corresponding to each of the multiple key points on the target blood vessel segment in the optical coherence tomography image. Correspondingly, the 3D blood vessel model scaling module is specifically used for: The length scaling factor is determined based on the distance between the key points at the beginning and end of the target blood vessel segment in the initial three-dimensional blood vessel model and the distance between the key points at the beginning and end of the target blood vessel segment in the optical coherence tomography image. The area scaling factor is determined based on the cross-sectional area of ​​the blood vessel corresponding to multiple key points on the target blood vessel segment in the initial three-dimensional blood vessel model and the cross-sectional area of ​​the blood vessel corresponding to multiple key points on the target blood vessel segment in the optical coherence tomography image. The initial three-dimensional blood vessel model is scaled based on the length scaling factor and the area scaling factor to obtain the target three-dimensional blood vessel model.

8. An electronic device, characterized in that, The electronic device includes: At least one processor; and a memory communicatively connected to the at least one processor; The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the method for determining the fractional blood flow reserve according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the method for determining the fractional blood flow reserve as described in any one of claims 1-6.

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