Patent Description:
According to the statistics of the World Health Organization, cardiovascular diseases have become a "leading killer" of human health. In recent years, the analysis of the physiological and pathological behaviors of cardiovascular diseases using hemodynamics has also become a very important means of diagnosis of the cardiovascular diseases.

Blood flow quantity and flow velocity are very important parameters of hemodynamics. How to measure the blood flow quantity and flow velocity accurately and conveniently has become the focus of many researchers.

Due to different vital signs of different populations, evaluation standards for normal values are slightly different. For example, the myocardial microcirculation function of the elderly is relatively poor, and the blood flow velocity is generally lower than that of the young. If the industry general evaluation standard is used, the blood flow velocity used will be higher than the actual value. The higher blood flow velocity will further affect the coronary artery evaluation parameters, such as: fractional flow reserve FFR, fractional flow reserve during a diastolic phase iFR, and index for microcirculatory resistance iFMR during the diastolic phase.

Therefore, at this stage, how to obtain the index for microcirculatory resistance iFMR according to individual differences, and then calculate an adjusted blood flow velocity in the maximum hyperemia state according to the index for microcirculatory resistance iFMR, to obtain a more targeted blood flow velocity with individualized differences and improve the accuracy of the blood flow velocity calculation, has become an urgent problem in the field of coronary artery technology.

<CIT> and <CIT> disclose devices and methods for calculating the blood flow velocity.

The present disclosure provides a method and an apparatus for calculating an adjusted blood flow velocity in maximum hyperemia state based on index for microcirculatory resistance, a coronary artery analysis system and a computer storage medium, so as to solve the problem of how to obtain a more targeted, individualized blood flow velocity in the maximum hyperemia state according to individualized differences.

In order to achieve the above object, in a first aspect, the present disclosure provides a method for calculating an adjusted blood flow velocity in maximum hyperemia state based on index for microcirculatory resistance, comprising:.

Optionally, in the above method for calculating an adjusted blood flow velocity in maximum hyperemia state based on index for microcirculatory resistance,
<MAT>
wherein vh represents the blood flow velocity in the maximum hyperemia state, v represents an average blood flow velocity in a heartbeat cycle area, z is a constant in the range of <NUM> to <NUM>, and x is a constant in the range of <NUM> to <NUM>; K=<NUM>.

Optionally, in the above method for calculating an adjusted blood flow velocity in maximum hyperemia state based on index of microcirculatory resistance, a manner for acquiring an index for microcirculatory resistance iFMR during a diastolic phase according to a blood flow velocity v, an aortic pressure waveform, and an physiological parameter comprises:.

Optionally, in the above method for calculating an adjusted blood flow velocity in maximum hyperemia state based on index for microcirculatory resistance, the influence parameter k=a×b, wherein a represents a characteristic value of diabetes, b represents a characteristic value of hypertension, and c represents gender.

Optionally, in the above method for calculating an adjusted blood flow velocity in maximum hyperemia state based on index for microcirculatory resistance, if a patient does not suffer from diabetes, then <NUM>≤a≤<NUM>; if the patient suffers from diabetes, then <NUM> < a≤<NUM>;.

Optionally, in the above method for calculating an adjusted blood flow velocity in maximum hyperemia state based on index for microcirculatory resistance, if the patient does not suffer from diabetes, then a=<NUM>; If the patient suffers from diabetes, then a=<NUM>;.

Optionally, in the above method for calculating an adjusted blood flow velocity in maximum hyperemia state based on index for microcirculatory resistance, a manner for acquiring a blood flow velocity comprises:.

Optionally, in the above method for calculating an adjusted blood flow velocity in maximum hyperemia state based on index for microcirculatory resistance, a manner for extracting a blood vessel segment of interest from the group of two-dimensional coronary artery angiogram images comprises:.

Optionally, in the above method for calculating an adjusted blood flow velocity in maximum hyperemia state based on index for microcirculatory resistance, a manner for extracting the centerline of the blood vessel segment comprises:.

Optionally, in the above method for calculating an adjusted blood flow velocity in maximum hyperemia state based on index for microcirculatory resistance, a manner for determining a difference in time taken for a contrast agent flowing through the blood vessel segment in any two frames of the two-dimensional coronary artery angiogram images with the difference being Δt, and determining a difference in centerline length of a sub-segment of the blood vessel segment through which the contrast agent flows in the two frames of two-dimensional coronary artery angiogram image with the difference being ΔL, and solving the blood flow velocity according to the ratio of ΔL to Δt comprises:.

Optionally, in the above method for calculating an adjusted blood flow velocity in maximum hyperemia state based on index for microcirculatory resistance, a manner for determining a difference in time taken a contrast agent flowing through the blood vessel segment in any two frames of the two-dimensional coronary artery angiogram images with the difference being Δt, and determining a difference in centerline length of a sub-segment of the blood vessel segment through which the contrast agent flows in the two frames of two-dimensional coronary artery angiogram image with the difference being ΔL , and solving the blood flow velocity according to the ratio of ΔL to Δt comprises:.

Optionally, in the above method for calculating an adjusted blood flow velocity in maximum hyperemia state based on index for microcirculatory resistance, after the manner for extracting a centerline of the blood vessel segment, and before the manner for determining a difference in time taken for a contrast agent flowing through the blood vessel segment in any two frames of the two-dimensional coronary artery angiogram images with the difference being Δt, and determining a difference in centerline length of a sub-segment of the blood vessel segment through which the contrast agent flows in the two frames of two-dimensional coronary artery angiogram image with the difference being ΔL , the method further comprises:.

Optionally, in the above method for calculating an adjusted blood flow velocity in maximum hyperemia state based on index for microcirculatory resistance, a manner for solving the blood flow velocity according to the ratio of ΔL to Δt comprises:.

In a third aspect, the present disclosure provides an apparatus for calculating an adjusted blood flow velocity in maximum hyperemia state based on index for microcirculatory resistance, used for the above method for adjusting blood flow velocity in maximum hyperemia state based on index for microcirculatory resistance, comprising: a blood flow velocity acquisition unit , an aortic pressure waveform acquisition unit, a physiological parameter acquisition unit, an unit of index for microcirculatory resistance during diastolic phase and an adjustment parameter unit; the unit of index for microcirculatory resistance during diastolic phase is connected with the blood flow velocity acquisition unit, the aortic pressure waveform acquisition unit and the physiological parameter acquisition unit;.

Optionally, the above apparatus for calculating an adjusted blood flow velocity in maximum hyperemia state based on index for microcirculatory resistance further comprises: an image reading unit, a blood vessel segment extraction unit, and a centerline extraction unit connected in sequence, a time difference unit and the physiological parameter acquisition unit both connected to the image reading unit, and the blood flow velocity acquisition unit that respectively connected with the time difference unit and a centerline difference unit, respectively; the centerline difference unit is connected with the centerline extraction unit;.

Optionally, the above apparatus for calculating an adjusted blood flow velocity in maximum hyperemia state based on index of microcirculatory resistance further comprises: a blood vessel skeleton extraction unit and a three-dimensional blood vessel reconstruction unit, both connected to the image reading unit, a contour line extraction unit connected to the blood vessel skeleton extraction unit, the three-dimensional blood vessel reconstruction unit being connected with the physiological parameter acquisition unit, the centerline extraction unit and the contour line extraction unit;.

In a fourth aspect, the present disclosure provides a coronary artery analysis system, comprising: the apparatus for calculating an adjusted blood flow velocity in maximum hyperemia state based on index for microcirculatory resistance according to any one of the above.

In a fifth aspect, the present disclosure provides a computer storage medium having stored thereon a computer program to be executed by a processor, the above method for calculating an adjusted blood flow velocity in maximum hyperemia state based on index for microcirculatory resistance is implemented when the computer program is executed by the processor.

The beneficial effects brought about by the solutions provided by the embodiments of the present disclosure comprise at least the following:.

According to the present disclosure, an index for microcirculatory resistance iFMR during a diastolic phase is acquired according to a blood flow velocity v, an aortic pressure waveform, and an physiological parameter; then an adjustment parameter is obtained by comparing iFMR with K, where the adjustment parameter varies for different values of iFMR, further, a differentiated parameter is obtained according to individualized differences, placing a solid foundation for the accuracy of a blood vessel calculation parameter, then, a corrected blood flow velocity in the maximum hyperemia state is obtained by a product of the adjustment parameter and the blood flow velocity in the maximum hyperemia state, allowing for more targeted, individualized and more accurate measurement results.

The drawings illustrated here are used to provide a further understanding of the present disclosure and constitute a part of the present disclosure. The exemplary embodiments and the descriptions thereof are used to explain the present disclosure, and do not constitute an improper limitation on the present disclosure. In the drawings:.

Reference numerals are explained below:
blood flow velocity acquisition unit <NUM>, blood flow velocity calculation module <NUM>, diastolic blood flow velocity calculation module <NUM>, aortic pressure waveform acquisition unit <NUM>, physiological parameter acquisition unit <NUM>, unit of index for microcirculatory resistance during diastolic phase <NUM>, adjustment parameter unit <NUM>, image reading unit <NUM>, blood vessel segment extraction unit <NUM>, centerline extraction unit <NUM>, time difference unit <NUM>, centerline difference unit <NUM>, blood vessel skeleton extraction unit <NUM>, three-dimensional blood vessel reconstruction unit <NUM>, contour line extraction unit <NUM>, flow velocity correction unit <NUM>, unit of flow velocity in maximum hyperemia state <NUM>.

In order to make objects, technical solutions and advantages of the present disclosure clearer, the technical solutions of the present disclosure will be clearly and completely described below with reference to the specific embodiments and corresponding drawings. It is apparent that the described embodiments are merely part of the embodiments of the present disclosure rather than all of them. Based on the embodiments in the present disclosure, without making creative work, all the other embodiments obtained by a person skilled in the art will fall into the protection scope of the present disclosure.

Hereinafter, a number of embodiments of the present disclosure will be disclosed with drawings. For clear illustration, many practical details will be described in the following description. However, it should be understood that the present disclosure should not be limited by these practical details. In other words, in some embodiments of the present disclosure, these practical details are unnecessary. In addition, in order to simplify the drawings, some conventionally used structures and components will be shown in simple schematic ways in the drawings.

Therefore, at this stage, how to obtain an adjustment parameter according to individual differences, for improving the accuracy of a blood vessel calculation parameter, such as a blood flow velocity, has become an urgent problem in the field of coronary artery technology.

Embodiment <NUM>: In order to solve the above problem, as shown in <FIG>, the present disclosure provides a method for calculating an adjusted blood flow velocity in maximum hyperemia state based on index for microcirculatory resistance, comprising:.

wherein v' represents the corrected blood flow velocity in the maximum hyperemia state, and vh represents a blood flow velocity in the maximum hyperemia state.

In an embodiment of the present disclosure, vh = zv+x;
wherein vh represents the blood flow velocity in the maximum hyperemia state, v represents an average blood flow velocity in a heartbeat cycle area, z is a constant in the range of <NUM> to <NUM>, and x is a constant in the range of <NUM> to <NUM>; K=<NUM>.

The present disclosure provides a method for calculating an adjusted blood flow velocity in maximum hyperemia state based on index for microcirculatory resistance, comprising:
S100, acquiring an index for microcirculatory resistance iFMR during a diastolic phase according to a blood flow velocity v, an aortic pressure waveform, and an physiological parameter; wherein.

All the contents of acquiring coronary artery blood vessel evaluation parameter based on the physiological parameter are within the scope of protection of the present disclosure. After a large number of experimental verifications, histories of having hypertension and diabetes and gender all have impacts on the accuracy of calculating a coronary artery blood vessel evaluation parameter. Therefore, in an embodiment of the present disclosure, an influence parameter k in S180 is calculated by the formula: k=a×b, where a represents a characteristic value of diabetes, b represents a characteristic value of hypertension, and c represents the gender. If a patient does not suffer from diabetes, then <NUM> ≤ a ≤ <NUM>, preferably, a=<NUM>; if the patient suffers from diabetes, then <NUM><a≤<NUM>, preferably, a=<NUM>; if the patient's blood pressure value is greater than or equal to <NUM> mmHg, then <NUM><b≤<NUM>, preferably, b=<NUM>; if the patient's blood pressure value is less than <NUM> mmHg, then <NUM> ≤ b ≤ <NUM>, preferably, b=<NUM>; if the patient is male, then c=<NUM>; if the patient is female, then c =<NUM>~<NUM>, preferably, c=<NUM>.

In an embodiment of the present disclosure, S140 comprises two acquisition methods. As shown in <FIG>, method(<NUM>) comprises:.

In an embodiment of the present disclosure, a manner for acquiring a blood flow velocity by three-dimensional modeling in S100 comprises:.

Δt =m×fps, since each group of two-dimensional coronary artery angiogram images contains multiple frames of two-dimensional coronary artery angiogram images played consecutively, m represents a difference in frame number between two frames of two-dimensional angiogram image selected from each group of two-dimensional coronary artery angiogram images, and fps represents an interval time for switching between two adjacent frames of the image, preferably, fps=<NUM>/<NUM> second.

The present disclosure provides a method for calculating an adjusted blood flow velocity in maximal hyperemia state based on physiological parameter, comprising:.

An embodiment of the present disclosure provides a method for acquiring coronary artery blood vessel evaluation parameter based on physiological parameter, comprising the above method for acquiring blood flow velocity in maximal hyperemia state based on physiological parameter. A coronary artery blood vessel evaluation parameter comprises: fractional flow reserve FFR, index for microcirculatory resistance IMR, index for microcirculatory resistance iFMR during a diastolic phase, fractional flow reserve iFR during the diastolic phase and the like.

As shown in <FIG> , the present disclosure provides an apparatus for calculating an adjusted blood flow velocity in maximum hyperemia state based on index for microcirculatory resistance, which is used for the above method for calculating an adjusted blood flow velocity in maximum hyperemia state based on index for microcirculatory resistance, comprising: a blood flow velocity acquisition unit <NUM>, an aortic pressure waveform acquisition unit <NUM>, a physiological parameter acquisition unit <NUM>, a unit of index for microcirculatory resistance during diastolic phase <NUM> and an adjustment parameter unit <NUM>. The unit of index for microcirculatory resistance during diastolic phase <NUM> is connected with the blood flow velocity acquisition unit <NUM>, the aortic pressure waveform acquisition unit <NUM> and the physiological parameter acquisition unit <NUM>. The blood flow velocity acquisition unit <NUM> is configured to acquire a blood flow velocity v. The aortic pressure waveform acquisition unit <NUM> is configured to acquire, in real time, an aortic pressure waveform changing over time. The physiological parameter acquisition unit <NUM> is configured to acquire physiological parameters of a patient, comprising gender and disease history. The unit of index for microcirculatory resistance during diastolic phase <NUM> is configured to receive the blood flow velocity v, the aortic pressure waveform, and the physiological parameters sent by the blood flow velocity acquisition unit <NUM>, the aortic pressure waveform acquisition unit <NUM>, and the physiological parameter acquisition unit <NUM>, and then to obtain an index for microcirculatory resistance iFMR during a diastolic phase according to the blood flow velocity v, the aortic pressure waveform, and the physiological parameters. The adjustment parameter unit <NUM> is configured to receive iFMR value of the unit of index for microcirculatory resistance during diastolic phase <NUM>. An adjustment parameter r is equal to <NUM> if the index for microcirculatory resistance during the diastolic phase iFMR<K; the adjustment parameter r satisfies a formula <MAT> if the index for microcirculatory resistance during the diastolic phase iFMR≥K; where K is a positive number less than <NUM>.

As shown in <FIG>, an embodiment of the present disclosure further comprises: a flow velocity correction unit <NUM> connected to the adjustment parameter unit <NUM>, a unit of flow velocity in maximum hyperemia state <NUM> connected to the flow velocity correction unit <NUM>. The unit of flow velocity in maximum hyperemia state <NUM> is configured to calculate a blood flow velocity in a maximum hyperemia state according to vh =zv+x; vh represents the blood flow velocity in the maximum hyperemia state, v represents an average blood flow velocity in a heartbeat cycle area, z is a constant in the range of <NUM> to <NUM>, and x is a constant in the range of <NUM> to <NUM>.

As shown in <FIG>, an embodiment of the present application further comprises: an image reading unit <NUM>, a blood vessel segment extraction unit <NUM>, and a centerline extraction unit <NUM> connected in sequence, a time difference unit <NUM> and the physiological parameter acquisition unit <NUM> connected to the image reading unit <NUM>, and the blood flow velocity acquisition unit <NUM> respectively connected with the time difference unit <NUM> and a centerline difference unit <NUM>. The centerline difference unit <NUM> is connected with the centerline extraction unit <NUM>. The image reading unit <NUM> is configured to read a group of two-dimensional coronary artery angiogram image of at least one body position. The blood vessel segment extraction unit <NUM> is configured to receive two-dimensional coronary artery angiogram images sent by the image reading unit <NUM>, and to extract a blood vessel segment of interest in the images. The centerline extraction unit <NUM> is configured to receive the blood vessel segment sent by the blood vessel segment extraction unit <NUM>, and to extract the centerline of the blood vessel segment. The time difference unit <NUM> is configured to receive any two frames of the two-dimensional coronary artery angiogram images sent by the image reading unit <NUM>, and to determine a difference in time taken for a contrast agent flowing through the blood vessel segment in the two frames of two-dimensional coronary artery angiogram image with the difference being Δt. The centerline difference unit <NUM> is configured to receive the centerline of a sub-segment of the blood vessel segment flowed through by the contrast agent in the two frames of two-dimensional coronary artery angiogram image sent by the centerline extraction unit, and to determine a difference in centerline length of the sub-segment of the blood vessel segment through which the contrast agent flows in the two frames of two-dimensional coronary artery angiogram image with the difference being ΔL. The blood flow velocity acquisition unit <NUM> comprises a blood flow velocity calculation module <NUM> and a diastolic blood flow velocity calculation module <NUM>. The blood flow velocity calculation module <NUM> is respectively connected to the time difference unit <NUM> and the centerline difference unit <NUM>. The diastolic blood flow velocity calculation module <NUM> is connected with the blood flow velocity calculation module <NUM>. The blood flow velocity calculation module <NUM> is configured to receive the ΔL and the Δt sent by the time difference unit <NUM> and the centerline difference unit <NUM>, and to solve the blood flow velocity according to the ratio of ΔL to Δt. The diastolic blood flow velocity calculation module <NUM> is configured to receive the blood flow velocity sent by the blood flow velocity calculation module <NUM>, and to select a maximum value of the blood flow velocity as a blood flow velocity during a diastolic phase. The physiological parameter acquisition unit <NUM> is configured to receive the two-dimensional coronary artery angiogram images of the image reading unit <NUM>, to acquire a physiological parameter of a patient, image shooting angles and imaging distance, and to transmit the physiological parameter, image shooting angles and imaging distance to the unit of index for microcirculatory resistance during diastolic phase <NUM>.

The above imaging distance may be understood as: when synthesizing a three-dimensional model by two plane images, as long as the distance between the object and the imaging plane, the image shooting angle, and the two two-dimensional plane images are known, the three-dimensional model can be generated through the principle of three-dimensional imaging.

In an embodiment of the present application, the apparatus further comprises: a blood vessel skeleton extraction unit <NUM> and a three-dimensional blood vessel reconstruction unit <NUM>, both connected to the image reading unit <NUM>, a contour line extraction unit <NUM> connected to the blood vessel skeleton extraction unit <NUM>. The three-dimensional blood vessel reconstruction unit <NUM> is connected with the physiological parameter acquisition unit <NUM>, the centerline extraction unit <NUM> and the contour line extraction unit <NUM>. The blood vessel skeleton extraction unit <NUM> is configured to receive the two-dimensional coronary artery angiogram images sent by the image reading unit <NUM>, and to extract a blood vessel skeleton in the images. The contour line extraction unit <NUM> is configured to receive the blood vessel skeleton of the blood vessel skeleton extraction unit <NUM>, and to extract a contour line of the blood vessel segment of interest according to the blood vessel skeleton. The three-dimensional blood vessel reconstruction unit <NUM> is configured to receive the contour line, the image shooting angles and the centerline sent by the contour line extraction unit <NUM>, the physiological parameter acquisition unit <NUM> and the centerline extraction unit <NUM>, and to receive the two-dimensional coronary artery angiogram images sent by the image reading unit <NUM> in order to synthesize a three-dimensional blood vessel model by projecting at least two body positions' two-dimensional coronary angiogram images which have been extracted centerline and contour line of the blood vessel onto a three-dimensional plane according to the geometric structure information of the blood vessel segment. The centerline extraction unit <NUM> is configured to re-extract the centerline of the blood vessel segment from the three-dimensional blood vessel model of the three-dimensional blood vessel reconstruction unit <NUM>, and to re-acquire the length of the centerline.

The present disclosure provides a coronary artery analysis system, which comprises the apparatus for calculating an adjusted blood flow velocity in maximum hyperemia state based on index for microcirculatory resistance according to any one of the above.

The present disclosure provides a computer storage medium having stored thereon a computer program to be executed by a processor, wherein the above method for calculating an adjusted blood flow velocity in maximum hyperemia state based on index for microcirculatory resistance is implemented when the computer program is executed by the processor.

A person skilled in the art knows that various aspects of the present disclosure can be implemented as a system, a method, or a computer program product. Therefore, each aspect of the present disclosure can be specifically implemented in the following forms, namely: complete hardware implementation, complete software implementation (including firmware, resident software, microcode, etc.), or a combination of hardware and software implementations, which here can be collectively referred to as "circuit", "module" or "system". In addition, in some embodiments, various aspects of the present disclosure may also be implemented in the form of a computer program product in one or more computer-readable media, and the computer-readable medium contains computer-readable program code. Implementation of a method and/or a system of embodiments of the present disclosure may involve performing or completing selected tasks manually, automatically, or a combination thereof.

For example, hardware for performing selected tasks according to the embodiment(s) of the present disclosure may be implemented as a chip or a circuit. As software, selected tasks according to the embodiment(s) of the present disclosure can be implemented as a plurality of software instructions executed by a computer using any suitable operating system. In the exemplary embodiment(s) of the present disclosure, a data processor performs one or more tasks according to the exemplary embodiment(s) of a method and/or system as described herein, such as a computing platform for executing multiple instructions. Optionally, the data processor comprises a volatile memory for storing instructions and/or data, and/or a non-volatile memory for storing instructions and/or data, for example, a magnetic hard disk and/or movable medium. Optionally, a network connection is also provided. Optionally, a display and/or user input device, such as a keyboard or mouse, are/is also provided.

Any combination of one or more computer readable media can be utilized. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (non-exhaustive list) of computer-readable storage media would include the following:
Electrical connection with one or more wires, portable computer disk, hard disk, random access memory (RAM), read only memory (ROM), erasable programmable read only memory (EPROM or flash memory), optical fiber, portable compact disk read only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination of the above. In this document, the computer-readable storage medium can be any tangible medium that contains or stores a program, and the program can be used by or in combination with an instruction execution system, apparatus, or device.

The computer-readable signal medium may include a data signal propagated in baseband or as a part of a carrier wave, which carries computer-readable program code. This data signal for propagation can take many forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium may also be any computer-readable medium other than the computer-readable storage medium. The computer-readable medium can send, propagate, or transmit a program for use by or in combination with the instruction execution system, apparatus, or device.

The program code contained in the computer-readable medium can be transmitted by any suitable medium, including, but not limited to, wireless, wired, optical cable, RF, etc., or any suitable combination of the above.

For example, any combination of one or more programming languages can be used to write computer program codes for performing operations for various aspects of the present disclosure, including object-oriented programming languages such as Java, Smalltalk, C++, and conventional process programming languages, such as "C" programming language or similar programming language. The program code can be executed entirely on a user's computer, partly on a user's computer, executed as an independent software package, partly on a user's computer and partly on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to a user's computer through any kind of network including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (for example, connected through Internet provided by an Internet service provider).

It should be understood that each block of the flowcharts and/or block diagrams and combinations of blocks in the flowcharts and/or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to the processor of general-purpose computers, special-purpose computers, or other programmable data processing devices to produce a machine, which produces a device that implements the functions/actions specified in one or more blocks in the flowcharts and/or block diagrams when these computer program instructions are executed by the processor of the computer or other programmable data processing devices.

It is also possible to store these computer program instructions in a computer-readable medium. These instructions make computers, other programmable data processing devices, or other devices work in a specific manner, so that the instructions stored in the computer-readable medium generate an article of manufacture comprising instructions for implementation of the functions/actions specified in one or more blocks in the flowcharts and/or block diagrams.

Computer program instructions can also be loaded onto a computer (for example, a coronary artery analysis system) or other programmable data processing equipment to facilitate a series of operation steps to be performed on the computer, other programmable data processing apparatus or other apparatus to produce a computer-implemented process, which enable instructions executed on a computer, other programmable device, or other apparatus to provide a process for implementing the functions/actions specified in the flowcharts and/or one or more block diagrams.

Claim 1:
A computer-implemented method for calculating an adjusted blood flow velocity in maximum hyperemia state based on index for microcirculatory resistance, characterized by comprising:
acquiring an index for microcirculatory resistance iFMR during a diastolic phase according to a blood flow velocity v, an aortic pressure waveform, and an physiological parameter;
making an adjustment parameter r equal to <NUM> if the index for microcirculatory resistance iFMR during the diastolic phase is less than K; making the adjustment parameter r satisfy a formula <MAT> if the index for microcirculatory resistance iFMR during the diastolic phase is greater than or equal to K, wherein K is a positive number less than <NUM>;
acquiring a corrected blood flow velocity in a maximum hyperemia state according to a formula v' = rvh;
wherein v' represents the corrected blood flow velocity in the maximum hyperemia state, and vh represents a blood flow velocity in the maximum hyperemia state.