Blood vessel pressure difference calculation method and apparatus based on angiographic data at single body position, and electronic device and storage medium

Abstract

A blood vessel pressure difference calculation method and apparatus based on angiographic data at a single body position, and an electronic device and a storage medium. The method comprises: acquiring angiographic data at a single body position (S1); determining an actual lumen model of a target blood vessel and an actual lumen geometry parameter of the actual lumen model (S2); determining a blood flow velocity V in the target blood vessel (S3); determining a proximal end point and a distal end point of a blood vessel segment of interest (S4); determining a reference lumen model of the target blood vessel and a reference lumen geometry parameter of the reference lumen model (S5); determining a difference change function D(xp) on the basis of the difference between a reference lumen geometry parameter and an actual lumen geometry parameter at any position p between the proximal end point and the distal end point (S6); and calculating a pressure difference ΔP between the position p and the proximal end point on the basis of the difference change function D(xp) and the blood flow velocity V (S7).

Description

Method, device, electronic device and storage medium for calculating vascular pressure difference based on single-position angiography data

[0001] This application claims priority to the Chinese patent application filed with the China Patent Office on June 16, 2023, with application number 202310723083.6. The entire contents of the above application are incorporated by reference into this application. Technical Field

[0002] The present application relates to the field of medical technology, and for example, to a method, device, electronic device, and storage medium for calculating vascular pressure difference based on single-position angiography data. Background Art

[0003] Coronary heart disease has become a major public health problem that currently plagues the vast majority of Chinese people. It has a large number of patients, a high incidence rate, and a high mortality rate, which has brought a heavy burden to patients' families, medical institutions, and society. Percutaneous Coronary Intervention (PCI) is a very important means of treating coronary heart disease. In 2020, 968,000 cases have been performed nationwide. Whether the myocardium is ischemic is an important factor for doctors to formulate treatment strategies for coronary heart disease. Currently, the most common clinical diagnosis method for myocardial ischemia is to observe the degree of stenosis of the vascular anatomical structure based on coronary angiography (Coronary Arterio Graphy, CAG) or intravascular imaging (Intravascular Ultrasound (Intravascular Ultrasound, IVUS) or Optical Coherence Tomography (Optical Coherence Tomography, OCT)), thereby further inferring the degree of myocardial ischemia in patients, but it is impossible to accurately feedback the relationship between the lesion and the degree of myocardial ischemia.

[0004] With the accumulation of more and more clinical evidence, the position of coronary physiology in the diagnosis and treatment of coronary heart disease is becoming more and more important. A large number of research results show that PCI treatment guided by coronary physiology can effectively reduce the incidence of adverse events in patients. Among them, the Fractional Flow Reserve (FFR) based on pressure guidewire has become the "gold standard" for assessing whether coronary artery stenosis leads to myocardial ischemia. However, FFR has some disadvantages, such as the need for invasive interventional consumables and vasodilators such as adenosine, complicated operation, and high price. It does not conform to the clinical usage scenarios in China, and the usage rate is less than one percent, which greatly limits the popularization and application of vascular physiology in China.

[0005] In recent years, medical imaging-based computational vascular physiology technologies, exemplified by quantitative flow fraction (QFR), have rapidly developed. QFR measurement, which requires only routine coronary angiography, uses lumen segmentation and reconstruction, hemodynamic calculations, and other analyses to monitor the severity of myocardial ischemia caused by stenosis in real time during interventional procedures. This allows for the development and optimization of interventional strategies, eliminating the need for consumables and vasodilators. It is convenient and cost-effective, and is expected to significantly expand the clinical penetration of vascular physiology, enhance diagnostic accuracy, and improve patient outcomes.

[0006] The QFR prototype requires the patient to reach a state of maximal hyperemia. Three-dimensional reconstruction is performed using two projections with a 25° difference in angle. Combined with the patient's individualized blood flow velocity, QFR measurement and analysis are completed. Using the gold standard FFR as a reference, the initial generation of QFR achieved an accuracy of 88%. However, because this technology still requires the injection of vasodilators, its clinical application remains limited, and it has not been widely adopted.

[0007] The first generation of QFR technology for clinical application was developed in 2016, significantly simplifying the calculation process. During operation, QFR calculation can be completed by performing a routine coronary angiography with a body position difference of ≥25° without the need for medication injection. This not only reduces the difficulty of analysis and measurement, but also significantly optimizes the speed of detection and improves clinical practicality. Using FFR as a reference, the second-generation QFR technology has a diagnostic accuracy of 92.7%, with excellent consistency and correlation with FFR.

[0008] However, this technology still requires two coronary angiograms for 3D reconstruction of the vessels and calculation of 3D QFR, placing stringent data requirements on the patient. Clinically, not all patients have two high-quality coronary angiograms. Conventional diagnostic and treatment procedures involve acquiring angiograms from two angles of the same vessel. Some of these angles can exhibit vessel overlap, shortening, or insufficient contrast agent filling, leading to reduced image quality and the inability to accurately perform 3D reconstruction. Consequently, 3D QFR calculations may be impossible or inaccurate.

[0009] Summary of the Invention

[0010] The present application provides a method for calculating vascular pressure difference based on single-position angiography data, which solves the technical problems in related technologies of low accuracy and inconvenient operation of vascular pressure difference calculation caused by collecting multi-angle angiography data. It only needs to extract single-position angiography data, which can shorten the calculation time of pressure difference and improve the applicability and accuracy of calculated pressure difference.

[0011] The embodiments of the present application disclose a method for calculating vascular pressure difference based on single-position angiography data, comprising:

[0012] Acquire single-position angiography data;

[0013] Determining an actual lumen model of a target blood vessel and actual lumen geometric parameters of the actual lumen model based on the single-position angiography data;

[0014] determining a blood flow velocity V of the target blood vessel based on the actual lumen model;

[0015] Marking the blood vessel segment of interest in the actual lumen model, and determining the proximal end point and the distal end point of the blood vessel segment of interest;

[0016] Determining a reference lumen model of the target blood vessel and reference lumen geometric parameters of the reference lumen model based on the actual lumen model;

[0017] Based on the difference between the reference lumen geometric parameters and the actual lumen geometric parameters at any position p between the proximal end point and the distal end point, the difference variation function D(x p );

[0018] Based on the difference change function D(x p ) and the blood flow velocity V, calculate the pressure difference ΔP between any position p between the proximal end point and the distal end point and the proximal end point.

[0019] Optionally, the target blood vessels include coronary arteries, intracranial arteries, peripheral arteries, branch vessels and vascular trees arising from coronary arteries, branch vessels and vascular trees arising from intracranial arteries, and branch vessels and vascular trees arising from peripheral arteries.

[0020] Optionally, determining the blood flow velocity V of the target blood vessel based on the actual lumen model includes: determining the blood flow velocity V based on a Thrombolysis In Myocardial Infarction (TIMI) counting method or an image segmentation method.

[0021] Optionally, a reference lumen model of the target blood vessel is determined based on the actual lumen model, including: when there is a bifurcation between the proximal end point and the distal end point, the actual lumen model is reconstructed using a stepped descending line segment before the distal end point, and the actual lumen model is reconstructed using a linear descending line segment after the distal end point to determine the reference lumen model.

[0022] Optionally, based on the difference between the reference lumen geometric parameters and the actual lumen geometric parameters at any position p between the proximal end point and the distal end point, a difference variation function D(x p ), including: calculating the difference between the reference lumen geometric parameters and the actual lumen geometric parameters at any position p between the proximal end point and the distal end point as the distance x from the arbitrary position p to the proximal end point increases. p Normalize the changes in the difference and determine the difference change function D(x p ).

[0023] Optionally, based on the difference change function D(x p ) and the blood flow velocity V, calculating the pressure difference ΔP between any position p between the proximal end point and the distal end point and the proximal end point, including: based on the difference change function D(x p ) and blood flow velocity V, and calculate the pressure difference ΔP between any position p between the proximal end point and the distal end point and the proximal end point.

[0024] Optionally, the difference change function D(x p ) and blood flow velocity V, calculating a pressure difference ΔP between any position p between the proximal end point and the distal end point and the proximal end point, comprising:

[0025] Where V is the blood flow velocity, C1, C2, ..., C m Parameter coefficients representing blood flow velocity V, a1, a2, ..., a k They are the difference change functions D(x p ), the scale represents the resolution, p is a natural number greater than or equal to 1, represents the position, x p is the difference between the reference lumen geometry parameter and the actual lumen geometry parameter at position p, k is a natural number greater than or equal to 1, and 2k+1 represents the window size.

[0026] Optionally, the blood flow velocity V includes at least one of the blood flow velocity of the target blood vessel in a state of maximum congestion and the blood flow velocity in a resting state.

[0027] The embodiments of the present application further disclose a device for calculating vascular pressure difference based on single-position angiography data, comprising:

[0028] A data acquisition module, configured to acquire single-position angiography data;

[0029] an actual lumen model determination module configured to determine an actual lumen model of a target blood vessel and actual lumen geometric parameters of the actual lumen model based on the single-position angiography data;

[0030] a velocity acquisition module, configured to determine the blood flow velocity V of the target blood vessel based on the actual lumen model;

[0031] a data marking module configured to mark the blood vessel segment of interest in the actual lumen model and determine the proximal end point and the distal end point of the blood vessel segment of interest;

[0032] a reference lumen model determination module, configured to determine a reference lumen model of the target blood vessel and reference lumen geometric parameters of the reference lumen model based on the actual lumen model;

[0033] The difference change function determination module is configured to determine the difference change function D(x p );

[0034] The vascular pressure difference calculation module is configured to calculate the pressure difference based on the difference change function D(x p ) and the blood flow velocity V, calculate the pressure difference ΔP between any position p between the proximal end point and the distal end point and the proximal end point.

[0035] Optionally, the reference lumen model determination module is configured to, when there is a bifurcation between the proximal end point and the distal end point, reconstruct the actual lumen model using a stepped descending line segment before the distal end point and reconstruct the actual lumen model using a linear descending line segment after the distal end point.

[0036] Optionally, the difference variation function determination module is configured to determine the difference between the reference lumen geometry parameter and the actual lumen geometry parameter at any position p between the proximal end point and the distal end point as the distance x from the arbitrary position p to the proximal end point increases. p Normalize the changes in the difference and determine the difference change function D(x p ).

[0037] An embodiment of the present application also discloses an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the method for calculating vascular pressure difference based on single-position angiography data in any of the above embodiments is implemented.

[0038] The embodiments of the present application further disclose a storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for calculating the vascular pressure difference based on single-position angiography data in any of the above embodiments is implemented. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] FIG1 is a flowchart showing a method for calculating vascular pressure difference based on single-position angiography data in one embodiment of the present application;

[0040] FIG2 is a block diagram showing a structure of a device for calculating vascular pressure difference based on single-position angiography data in an embodiment of the present application;

[0041] FIG3 shows a structural block diagram of an electronic device in an embodiment of the present application. DETAILED DESCRIPTION

[0042] It should be noted that in this specification, like reference numerals and letters denote like items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings.

[0043] In the description of this embodiment, the terms "upper", "lower", "inner", "bottom", etc. indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, or are the orientations or positional relationships in which the inventive product is conventionally placed when in use. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, they should not be understood as limitations on this application.

[0044] The terms “first”, “second”, etc. are only used for distinguishing descriptions and should not be understood as indicating or implying relative importance.

[0045] In the description of this embodiment, unless otherwise specified or limited, the terms "disposed," "connected," and "connected" should be understood broadly. For example, they may refer to fixed, detachable, or integral connections; mechanical or electrical connections; direct or indirect connections through an intermediary; and internal communication between two components. Those skilled in the art will understand the specific meanings of these terms in this embodiment based on the specific circumstances.

[0046] This embodiment proposes a method for calculating vascular pressure difference based on single-position angiography data, including: acquiring single-position angiography data; determining an actual lumen model of a target blood vessel and actual lumen geometric parameters of the actual lumen model based on the single-position angiography data; determining a blood flow velocity V of the target blood vessel based on the actual lumen model; marking a blood vessel segment of interest in the actual lumen model, and determining a proximal end point and a distal end point of the blood vessel segment of interest; determining a reference lumen model of the target blood vessel and reference lumen geometric parameters of the reference lumen model based on the actual lumen model; determining a difference variation function D(x) based on the difference between the reference lumen geometric parameters and the actual lumen geometric parameters at any position p between the proximal end point and the distal end point.p ); Based on the difference change function D(x p ) and blood flow velocity V, calculate the pressure difference ΔP between any position p between the proximal end point and the distal end point.

[0047] The vascular pressure difference calculation method of the present application only needs to be based on angiography data at a single position (ie, one angle), which shortens the pressure difference calculation time and improves the applicability and accuracy of the pressure difference calculation.

[0048] The following describes a method for calculating vascular pressure difference based on single-position angiography data with reference to FIG1 .

[0049] Step S1: Acquire single-position angiography data.

[0050] Step S1 can collect angiographic data of the target blood vessel through a single projection position. The single projection position in this article refers to collecting angiographic data of the target blood vessel at only one angle. In this technical solution, only the angiographic data of a single blood vessel position needs to be collected to calculate the vascular pressure difference, which shortens the time for obtaining angiographic data.

[0051] The acquisition of angiographic data can be done directly or by selecting the image information corresponding to the vessel segment of interest from the image data of a vessel segment. This embodiment does not impose any restrictions on this. The source of the image information can be directly imported from relevant files, obtained from other resource libraries through real-time configuration connections, or obtained from a stored image information library by searching and locking based on information such as the user's name. This embodiment does not impose any restrictions on this. Optionally, the imaging information is in the Digital Imaging and Communications in Medicine (DICOM) format. DICOM covers nearly all information exchange protocols for the acquisition, archiving, communication, display, and query of medical digital images. Using an open, interconnected architecture and object-oriented approach, it defines a set of objects encompassing various types of medical diagnostic images and related analysis, reporting, and other information. It also defines service classes and command sets for information transmission and exchange, as well as standard message responses. It details techniques for identifying multiple types of information objects, provides service support for application in network environments (Open System Interconnection (OSI) or Transmission Control Protocol / Internet Protocol (TCP / IP)), and structuredly defines manufacturer's conformance statements. Using the DICOM format greatly simplifies the implementation of medical imaging information exchange and facilitates collaboration with other medical application systems, such as hospital information management systems (HIS) and radiology information systems (RIS). Optionally, the image data is 1-1000 frames of images. Within this frame number range, it can ensure clearer images covering multiple angles of each position of the blood vessel segment, improve the accuracy of calculation, and does not increase the computational load, and is easy to obtain.

[0052] The image data includes at least a portion of a cardiac cycle. For example, the image data may include one or more complete cardiac cycles, or may include half a cardiac cycle.

[0053] Target vessels include coronary arteries, intracranial arteries, peripheral arteries, branch vessels and vascular trees arising from coronary arteries, branch vessels and vascular trees arising from intracranial arteries, and branch vessels and vascular trees arising from peripheral arteries.

[0054] In this embodiment, the image data can be obtained by X-ray detection means.

[0055] Step S2: Based on the single-position angiography data, determine the actual lumen model of the target blood vessel and the actual lumen geometric parameters of the actual lumen model.

[0056] Based on single-position angiography data, characteristic parameters of the target vessel are extracted. These parameters may include the type of the target vessel (e.g., left anterior descending coronary artery (LAD), right coronary artery (RCA), left circumflex coronary artery (LCX)), shape, outline, length, diameter, or radius. Based on the characteristic parameters of the target vessel, an actual lumen model of the target vessel and the actual lumen geometry parameters of the actual lumen model are determined.

[0057] For example, the actual lumen geometric parameter described herein may refer to the diameter or radius of the actual lumen model.

[0058] Step S3: Determine the blood flow velocity V of the target blood vessel based on the actual lumen model.

[0059] In this application, blood flow velocity V includes the blood flow velocity Vhyper when the target vessel is in a state of maximum hyperemia and / or the blood flow velocity Vrest when the target vessel is in a state of rest. When a drug such as adenosine / adenosine triphosphate (ATP) is injected into the target vessel and the target vessel is in a state of maximum hyperemia, the blood flow velocity V calculated based on the angiography data is the blood flow velocity Vhyper when the target vessel is in a state of rest. When the target vessel is in a state of rest, the blood flow velocity V calculated based on the angiography data is the blood flow velocity Vrest when the target vessel is in a state of maximum hyperemia.

[0060] In one embodiment of the present application, the blood flow velocity V is the average flow velocity of the contrast agent in the target blood vessel during the angiography process obtained using the grayscale time fitting function; or the average flow velocity of the contrast agent in the target blood vessel during the angiography process obtained by calculating using the TIMI frame counting method.

[0061] In another embodiment of the present application, the blood flow velocity Vhyper in the maximum hyperemia state is the blood flow velocity V after the blood vessels are fully dilated by the injection of adenosine.

[0062] In other possible implementations, deep learning can be used to segment the angiography data to obtain a segmented image of the target blood vessel; based on the segmented image of the target blood vessel, the length of the blood vessel in each frame of the segmented image is calculated; and the blood flow velocity V of the blood vessel is obtained based on the change in the calculated blood vessel length over time.

[0063] The blood flow velocity of the main vessel or the blood flow velocity of the branch vessel can be obtained by the above method.

[0064] Step S4: Mark the blood vessel segment of interest in the actual lumen model, and determine the proximal end point and the distal end point of the blood vessel segment of interest.

[0065] The vessel segment of interest in the actual lumen model is marked, and the proximal and distal endpoints of the vessel segment of interest are determined. This marking includes but is not limited to manual marking. The vessel of interest can be selected by marking the proximal and distal endpoints along the axial direction of the actual lumen model. In this application, the "proximal end" refers to the end of the vessel segment of interest that is first passed by blood flow; the "distal end" refers to the end of the vessel segment of interest that is later passed by blood flow.

[0066] Step S5: Based on the actual lumen model, determine the reference lumen model of the target blood vessel and the reference lumen geometric parameters of the reference lumen model.

[0067] Based on the actual lumen model, the reference lumen model of the target blood vessel is determined, including: if there is a bifurcation between the proximal end point and the distal end point, the actual lumen model is reconstructed using a stepped descending line segment before the distal end point, and the actual lumen model is reconstructed using a linear descending line segment after the distal end point to determine the reference lumen model of the target blood vessel.

[0068] When reconstructing the actual lumen model, it is first segmented and labeled. The segment of the actual lumen model preceding the distal endpoint of the vessel of interest is defined as the first segment, and the segment following the distal endpoint is defined as the second segment. The first segment is divided into sections. If there is a bifurcation between the proximal and distal endpoints, the first segment is reconstructed using a stepped descending line segment, with each broken line segment being a linear segment. The second segment is reconstructed using a linear descending line segment. A reference lumen model of the target vessel is constructed based on the actual lumen model.

[0069] Based on the reference lumen model, a reference lumen geometric parameter of the reference lumen model is determined. For example, the reference lumen geometric parameter herein may refer to the diameter or radius of the reference lumen model.

[0070] In other possible implementations, the centerline of the reference lumen model can be extracted based on the determined actual lumen model of the target vessel and the reference lumen model. Methods for extracting the centerline of the reference lumen model include, but are not limited to, methods based on traditional algorithms such as distance transform, minimum path, and morphological processing, Voronoi diagrams, and deep learning-based methods. Centerline extraction methods are not limited to the aforementioned methods.

[0071] Based on the center line of the reference tubular model, a perpendicular line is drawn from any point on the center line to the outline of the reference tubular model. Usually, the perpendicular line includes a first line segment and a second line segment. The first line segment is located outside the outline of the actual tubular model, and the second line segment is located inside the actual tubular model. Based on the second line segment, the actual tubular geometric parameters of the actual tubular model are determined.

[0072] The actual lumen geometry parameters obtained in this way can further improve the accuracy of pressure difference calculation in the case of lesions such as vascular stenosis.

[0073] Step S6: Based on the difference between the reference lumen geometry parameters and the actual lumen geometry parameters at any position p between the proximal end point and the distal end point, determine the difference change function D(x p ).

[0074] Step S6 includes: calculating the difference between the reference lumen geometric parameters and the actual lumen geometric parameters at any position p between the proximal end point and the distal end point as the distance x from the arbitrary position p to the proximal end point increases. p Normalize the changes in the difference and determine the difference change function D(x p ).

[0075] For example, any position p between the proximal endpoint and the distal endpoint may include multiple arbitrary positions p1, p2, and p3. The actual lumen geometry parameters and reference lumen geometry parameters at p1 are R1 and R2, respectively; the actual lumen geometry parameters and reference lumen geometry parameters at p2 are R3 and R4, respectively; and the actual lumen geometry parameters and reference lumen geometry parameters at p3 are R5 and R6, respectively. Calculate the difference between the actual lumen geometry parameters and the reference lumen geometry parameters at any position p1 as the distance x from p1 to the proximal endpoint increases. p1 The difference between the actual lumen geometry parameters and the reference lumen geometry parameters at any position p2 changes with the distance x from p2 to the proximal end point. p2 The change of and the difference between the actual lumen geometric parameters and the reference lumen geometric parameters at any position p3 with the distance x from p3 to the proximal end point p3 The difference between the actual lumen geometry parameters and the reference lumen geometry parameters at different arbitrary positions p changes with the distance x from p to the proximal end point. p Normalize the changes in the difference and determine the difference change function D(x p ).

[0076] Step S7: Based on the difference change function D(x p ) and blood flow velocity V, calculate the pressure difference ΔP between any position p between the proximal end point and the distal end point.

[0077] Based on the difference change function D(x p) and blood flow velocity V, calculate the pressure difference ΔP between any position p and the proximal end point between the proximal end point and the distal end point, including: based on the difference change function D(x p ) and blood flow velocity V, calculate the pressure difference ΔP between any position p and the proximal end point between the proximal end point and the distal end point, and the calculation formula is as follows:

[0078] Where V is the blood flow velocity, C1, C2, ..., C m Parameter coefficients representing blood flow velocity V, a1, a2, ..., a k are the weighted coefficients of the difference change function D(x) of the actual lumen model at different scales, where the scale represents the resolution of the angiography data, and x p is the difference between the reference lumen geometry parameters and the actual lumen geometry parameters at position p, k is a natural number greater than or equal to 1, and 2k+1 represents the window size, which can be understood as a multiple of the angiography data resolution.

[0079] C1, C2, ..., C m Parameter coefficients representing blood flow velocity, including factors affecting blood viscosity, blood turbulence, and the viscosity coefficient, are included. m is a natural number greater than or equal to 1, representing the impact of different parameter coefficients on blood flow velocity. This is used to correct the pressure difference ΔP and ensure the accuracy of the pressure difference ΔP calculation. Optionally, in this application, the value of m is 2. When m is 2, C1 is the parameter coefficient generated by blood flow friction, and C2 is the parameter coefficient generated by blood turbulence.

[0080] D(x p ) represents the difference change function at position P, D(x p-k ) represents the difference change function at the Pk position, D(x p+k ) represents the difference change function at the P+k position.

[0081] Indicates the mean of the difference change function within the window when the window is 3; Indicates the mean of the difference change function within the window when the window is 2K+1.

[0082] The pressure difference ΔP calculated by the above technical means can adapt to narrow blood vessels of multiple scales and has higher repeatability.

[0083] The present application also proposes a vascular pressure difference calculation device 10 based on single-position angiography data, as shown in FIG2 , comprising: a data acquisition module 11, configured to acquire single-position angiography data; an actual lumen model determination module 12, configured to determine the actual lumen model of the target blood vessel and the actual lumen geometric parameters of the actual lumen model based on the single-position angiography data; a velocity acquisition module 13, configured to determine the blood flow velocity V of the target blood vessel based on the actual lumen model; a data marking module 14, configured to mark the blood vessel segment of interest in the actual lumen model and determine the proximal end point and distal end point of the blood vessel segment of interest respectively; a reference lumen model determination module 15, configured to determine the reference lumen model of the target blood vessel and the reference lumen geometric parameters of the reference lumen model based on the actual lumen model; and a difference change function determination module 16, configured to determine the difference change function D(x) based on the difference between the reference lumen geometric parameters and the actual lumen geometric parameters at any position p between the proximal end point and the distal end point. p ); Vascular pressure difference calculation module 17, set based on the difference change function D (x p ) and blood flow velocity V, calculate the pressure difference ΔP between any position p between the proximal end point and the distal end point.

[0084] In one possible embodiment, the reference lumen model determination module 15 is configured to, when there is a bifurcation between the proximal end point and the distal end point, use a stepped descending line segment to reconstruct the actual lumen model before the distal end point, and use a linear descending line segment to reconstruct the actual lumen model after the distal end point.

[0085] In a possible embodiment, the vascular pressure difference calculation device based on single-position angiography data further includes a normalization module configured to calculate the difference between the reference lumen geometric parameters and the actual lumen geometric parameters at any position p between the proximal end point and the distal end point as the distance x from the arbitrary position p to the proximal end point increases. p Normalize the changes in the difference function D(x p ).

[0086] In a possible embodiment, the difference variation function determination module is configured to calculate the difference between the reference lumen geometric parameter and the actual lumen geometric parameter at any position p between the proximal end point and the distal end point as the distance x from the arbitrary position p to the proximal end point increases. p Normalize the changes in the difference and determine the difference change function D(x p ).

[0087] In conjunction with Figure 3, the present application also provides an electronic device 20, including a memory 21, a processor 22, and a computer program stored in the memory 21 and executable on the processor 22. When the processor 22 executes the computer program, it implements the vascular pressure difference calculation method based on single-position angiography data in any of the aforementioned embodiments.

[0088] The electronic device 20 also includes a network interface 23, an input device 24, and a display device 25. The above interfaces and devices can be interconnected via a bus architecture. The bus architecture can include any number of interconnected buses and bridges. Multiple circuits of one or more central processing units (CPUs) represented by the processor 22 and one or more memories represented by the memory 21 are connected together. Among them, the memory 21 may include, for example, system memory, fixed non-volatile storage media, etc. The system memory may be a memory that stores an operating system, application programs, a boot loader, and other programs. The bus architecture can also connect various other circuits such as peripheral devices, voltage regulators, and power management circuits. It can be understood that the bus architecture is used to achieve connection and communication between these components. In addition to the data bus, the bus architecture also includes a power bus, a control bus, and a status signal bus, which are all well known in the art and therefore will not be described in detail herein.

[0089] The network interface 23 can be connected to a network (such as the Internet, a local area network, etc.), obtain relevant data from the network, and save the data in a hard disk.

[0090] The input device 24 can receive instructions input by the operator and send the instructions to the processor 22 for execution by the processor 22. The input device 24 can include a keyboard or a pointing device (e.g., a mouse, a trackball, a touchpad, or a touch screen).

[0091] The display device 25 can display the results obtained by the processor 22 executing the instructions.

[0092] Memory 21 is configured to store programs and data necessary for the operation of the operating system, as well as data such as intermediate results in the calculation process of processor 22. It will be understood that the memory 21 in the embodiment of the present application can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM) or a flash memory. The volatile memory can be a random access memory (RAM), which is used as an external cache. The memory of the apparatus and method described herein includes, but is not limited to, these and any other suitable types of memories.

[0093] In some embodiments, the memory 21 stores the following elements, executable modules or data structures, or their subsets, or their extensions: an operating system and an application program. The operating system includes a variety of system programs, such as a framework layer, a core library layer, a driver layer, etc., for implementing a variety of basic services and processing hardware-based tasks. The application program includes a variety of application programs, such as a browser, etc., for implementing a variety of application services. The program for implementing the method of the embodiment of the present application can be included in the application program.

[0094] The methods disclosed in the above embodiments of the present application can be applied to or implemented by the processor 22. The processor 22 may be an integrated circuit chip with signal processing capabilities. During implementation, the steps of the above methods can be completed by hardware integrated logic circuits in the processor or by software instructions. The above processor 22 can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components, and can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of the present application. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of the present application can be executed by a hardware decoding processor or by a combination of hardware and software modules in the decoding processor. The software modules can be located in a storage medium well-known in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in the memory 21, and the processor 22 reads the information in the memory 21 and, in conjunction with its hardware, completes the steps of the above methods.

[0095] It is understood that the embodiments described herein may be implemented using hardware, software, firmware, middleware, microcode, or a combination thereof. For hardware implementation, the processing unit may be implemented in one or more ASICs, DSPs, digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays, general-purpose processors, controllers, microcontrollers, microprocessors, or other electronic units or a combination thereof for performing the functions described herein.

[0096] For software implementation, the techniques described herein may be implemented by modules (e.g., procedures, functions, etc.) that perform the functions described herein. The software codes may be stored in the memory 21 and executed by the processor 22. The memory 21 may be implemented in the processor 22 or external to the processor 22.

[0097] In the embodiment of the present application, the electronic device 20 determines the actual lumen model, the actual lumen geometric parameters of the actual lumen model, and the blood flow velocity V of the target blood vessel through the single-position angiography data, and determines the reference lumen model and the reference lumen geometric parameters of the reference lumen model based on the actual lumen model. Based on the difference between the reference lumen geometric parameters and the actual lumen geometric parameters at any position p between the proximal end point and the distal end point, the difference change function D(x p ), and based on the difference change function D(x) and the blood flow velocity V, the pressure difference ΔP between any position p between the proximal end point and the distal end point is calculated.

[0098] The electronic device 20 for calculating pressure difference realizes the automation calculation of the pressure difference ΔP between any position p between the proximal end point and the distal end point on the target blood vessel. The calculated pressure difference is more accurate and the calculation method is relatively simple.

[0099] The present application also provides a storage medium having a computer program stored thereon, which, when executed by the processor 22, implements the method for calculating the vascular pressure difference based on unit volume angiography data in any of the aforementioned embodiments. Those skilled in the art should understand that the embodiments of the present application can be provided as methods, devices, or computer program products. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable non-transitory storage media (including but not limited to disk storage, portable compact disk read-only memory (CD-ROM), optical storage, etc.) containing computer-usable program code.

[0100] The storage medium stores computer-readable code, and when the computer-readable code is executed by one or more processors 22, the following steps are performed: Step S1: Acquire single-position angiography data; Step S2: Determine the actual lumen model of the target blood vessel and the actual lumen geometric parameters of the actual lumen model based on the single-position angiography data; Step S3: Determine the blood flow velocity V of the target blood vessel based on the actual lumen model; Step S4: Mark the blood vessel segment of interest in the actual lumen model and determine the proximal end point and distal end point of the blood vessel segment of interest respectively; Step S5: Determine the reference lumen model of the target blood vessel and the reference lumen geometric parameters of the reference lumen model based on the actual lumen model; Step S6: Determine the difference change function D(x) based on the difference between the reference lumen geometric parameters and the actual lumen geometric parameters at any position p between the proximal end point and the distal end point p ); Step S7: Based on the difference change function D(x p) and blood flow velocity V, calculate the pressure difference ΔP between any position p between the proximal end point and the distal end point.

[0101] When executed by processor 22, this computer-readable code implements multiple processes of the aforementioned embodiment of the method for calculating vascular pressure differences based on single-position angiography data, achieving the same technical effect. To avoid repetition, the detailed processes are not described here. The storage medium may be, for example, ROM, RAM, a magnetic disk, or an optical disk.

[0102] The multiple functional units in the multiple embodiments of the present application can be integrated into one processing unit, or each functional unit can be integrated into one processing unit, or two or more functional units can be integrated into one processing unit. The above-mentioned integrated functional units can be implemented in the form of hardware or in the form of hardware plus software functional units. The technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above-mentioned embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0103] In addition, the present application is described in terms of the flowcharts and / or block diagrams of the methods, devices, and computer program products of the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate a device for implementing the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0104] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a product including an instruction device that implements the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0105] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0106] It should be noted that in some alternative implementations, the functions noted in the blocks may occur in a different order than that noted in the accompanying figures. For example, two consecutive blocks may actually be executed substantially in parallel, or they may sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flow charts, and combinations of blocks in the block diagrams and / or flow charts, may be implemented using a dedicated hardware-based system that performs the specified functions or actions, or may be implemented using a combination of dedicated hardware and computer instructions.

Claims

1. A method for calculating vascular pressure difference based on single-position angiography data, comprising: Acquiring single-position angiography data; Determining an actual lumen model of a target blood vessel and actual lumen geometric parameters of the actual lumen model based on the single-position angiography data; Determining the blood flow velocity V of the target blood vessel based on the actual lumen model; Marking the blood vessel segment of interest of the actual lumen model, and determining the proximal end point and the distal end point of the blood vessel segment of interest respectively; Determining a reference lumen model of the target blood vessel and reference lumen geometric parameters of the reference lumen model based on the actual lumen model; Based on the difference between the reference lumen geometric parameters and the actual lumen geometric parameters at any position p between the proximal end point and the distal end point, the difference variation function D(x p ); Based on the difference change function D(x p ) and the blood flow velocity V, calculate the pressure difference ΔP between any position p between the proximal end point and the distal end point and the proximal end point.

2. The method of claim 1, wherein: The target blood vessel includes at least one of the following: Coronary arteries, intracranial arteries, peripheral arteries, branch vessels and vascular trees arising from coronary arteries, branch vessels and vascular trees arising from intracranial arteries, and branch vessels and vascular trees arising from peripheral arteries.

3. The method of claim 1, wherein: The determining of the blood flow velocity V of the target blood vessel based on the actual lumen model includes: determining the blood flow velocity V based on a TIMI frame counting method or an image segmentation method.

4. The method of claim 1, wherein: The method of determining the reference lumen model of the target blood vessel based on the actual lumen model includes: when there is a bifurcation between the proximal end point and the distal end point, reconstructing the actual lumen model by using a stepped descending line segment before the distal end point and reconstructing the actual lumen model by using a linear descending line segment after the distal end point to determine the reference lumen model.

5. The method of claim 1, wherein: The difference variation function D(x) is determined based on the difference between the reference lumen geometric parameters and the actual lumen geometric parameters at any position p between the proximal end point and the distal end point. p ),include: The difference between the reference lumen geometric parameters and the actual lumen geometric parameters at any position p between the proximal end point and the distal end point varies with the distance x from the arbitrary position p to the proximal end point. p The change of is normalized to determine the difference change function D(x p ).

6. The method of claim 5, wherein: The difference change function D(x p ) and the blood flow velocity V, calculating the pressure difference ΔP between any position p between the proximal end point and the distal end point and the proximal end point, comprising: Based on the difference change function D(x p ) and blood flow velocity V, and calculate the pressure difference ΔP between any position p between the proximal end point and the distal end point and the proximal end point.

7. The method of claim 6, wherein: The difference change function D(x) based on different windows p ) and blood flow velocity V, calculating a pressure difference ΔP between any position p between the proximal end point and the distal end point and the proximal end point, comprising: Where V is the blood flow velocity, C1, C2, ..., C m Represents the parameter coefficients of blood flow velocity V, a1, a2, ..., a k are the difference change functions D(x) of the actual lumen model at different scales. p ), the scale represents the resolution, p is a natural number greater than or equal to 1, represents the position, x p is the difference between the reference lumen geometry parameter and the actual lumen geometry parameter at position p, k is a natural number greater than or equal to 1, and 2k+1 represents the window size.

8. The method of claim 1, wherein: The blood flow velocity V includes at least one of the blood flow velocity when the target blood vessel is in a maximum hyperemia state and the blood flow velocity when the target blood vessel is in a resting state.

9. A device for calculating blood vessel pressure difference based on single-position angiography data, comprising: A data acquisition module, configured to acquire single-position angiography data; an actual lumen model determination module, configured to determine an actual lumen model of a target blood vessel and actual lumen geometric parameters of the actual lumen model based on the single-position angiography data; A velocity acquisition module, configured to determine the blood flow velocity V of the target blood vessel based on the actual lumen model; A data marking module, configured to mark the blood vessel segment of interest of the actual lumen model, and respectively determine the proximal end point and the distal end point of the blood vessel segment of interest; a reference lumen model determination module, configured to determine a reference lumen model of the target blood vessel and reference lumen geometric parameters of the reference lumen model based on the actual lumen model; The difference change function determination module is configured to determine the difference change function based on the difference between the reference lumen geometric parameters and the actual lumen geometric parameters at any position p between the proximal end point and the distal end point. D(x p ); The blood vessel pressure difference calculation module is configured to calculate the blood vessel pressure difference based on the difference change function D(x p ) and the blood flow velocity V, calculate the pressure difference ΔP between any position p between the proximal end point and the distal end point and the proximal end point.

10. The device of claim 9, wherein: The reference lumen model determination module is configured to, when there is a bifurcation between the proximal end point and the distal end point, reconstruct the actual lumen model using a stepped descending line segment before the distal end point and reconstruct the actual lumen model using a linear descending line segment after the distal end point.

11. The device according to claim 9, wherein: The difference variation function determination module is configured to determine the difference between the reference lumen geometry parameter and the actual lumen geometry parameter at any position p between the proximal end point and the distal end point as the distance x from the arbitrary position p to the proximal end point increases. p The change of is normalized to determine the difference change function D(x p ).

12. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method for calculating vascular pressure difference based on single-position angiography data as claimed in any one of claims 1 to 8 when executing the computer program.

13. A storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the method for calculating the vascular pressure difference based on single-position angiography data according to any one of claims 1 to 8 is implemented.

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