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WO2022109907A1 - Procédé et support de stockage pour l'acquisition précise d'une gamme de lésions sténosées - Google Patents

Procédé et support de stockage pour l'acquisition précise d'une gamme de lésions sténosées Download PDF

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Publication number
WO2022109907A1
WO2022109907A1 PCT/CN2020/131703 CN2020131703W WO2022109907A1 WO 2022109907 A1 WO2022109907 A1 WO 2022109907A1 CN 2020131703 W CN2020131703 W CN 2020131703W WO 2022109907 A1 WO2022109907 A1 WO 2022109907A1
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WIPO (PCT)
Prior art keywords
blood vessel
interval
pipe diameter
stenotic lesion
curve
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Ceased
Application number
PCT/CN2020/131703
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English (en)
Chinese (zh)
Inventor
王鹏
刘广志
王之元
徐磊
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Suzhou Rainmed Medical Technology Co Ltd
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Suzhou Rainmed Medical Technology Co Ltd
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Publication of WO2022109907A1 publication Critical patent/WO2022109907A1/fr
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0012—Biomedical image inspection
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/60—Analysis of geometric attributes
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H30/00—ICT specially adapted for the handling or processing of medical images
    • G16H30/40—ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10072—Tomographic images
    • G06T2207/10081—Computed x-ray tomography [CT]
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30101—Blood vessel; Artery; Vein; Vascular

Definitions

  • the invention relates to the technical field of coronary medicine, in particular to a method and a storage medium for accurately acquiring a stenotic lesion interval.
  • FFR is one of the coronary vascular evaluation parameters, and the microcirculation resistance index IMR belongs to the coronary vascular evaluation parameters.
  • the existing technology can obtain the stenotic lesion interval through different methods, all of them are by defining the stenotic position, extending from the stenotic position to both ends, and extending to the preset parameters to obtain the starting position and ending position of the stenotic lesion, thereby obtaining the stenotic lesion. interval.
  • the fixed preset parameters are unable to cope with the diversity of blood vessels, resulting in insufficient intensive reading of the stenotic lesion interval.
  • the present invention provides a method and a storage medium for accurately acquiring stenotic lesion intervals, so as to solve the problem of insufficient precision of stenotic lesion intervals due to the inability of fixed preset parameters to deal with the diversity of blood vessels.
  • the present application provides a method for accurately obtaining a narrow lesion interval, including:
  • the misjudged stenotic region is removed from the first stenotic lesion interval to obtain a second stenotic lesion interval.
  • the preliminary judgment, the method for obtaining the first narrow lesion interval includes:
  • the first stenosis lesion interval is obtained.
  • the method for fitting a normal blood vessel diameter and obtaining a fitting diameter curve includes:
  • i represents the curve sampling point of the ith pipe diameter
  • n represents the sum of the number of pipe diameter curve sampling
  • xi represents the length of the curve sampling point of the ith pipe diameter
  • y i represents the pipe diameter at xi ;
  • the method for obtaining the first stenosis position according to the fitted diameter curve and the real diameter curve includes:
  • the intersection is the first entry point of the narrow area, otherwise, the intersection is the first exit of the narrow area point;
  • the curve between the first entry point and the first exit point is the preliminarily determined stenosis position, that is, the first stenotic lesion interval.
  • the method for removing a misjudged narrow lesion area from the first narrow lesion interval to obtain a second narrow lesion interval includes;
  • the misjudged stenosis region is removed from the first stenotic lesion interval according to the stenosis degree and the length of the blood vessel center line to obtain a second stenotic lesion interval.
  • the method for calculating a stenosis degree includes:
  • A represents the stenosis degree of the blood vessel
  • D min represents the minimum diameter of the blood vessel between the first entry point and the first exit point
  • D in and D out represent the vessel diameter of the first entry point and the first exit point, respectively vascular diameter.
  • the method for obtaining a second stenotic lesion interval by removing a misjudged stenotic area from the first stenotic lesion interval according to the stenosis degree and the length of the blood vessel centerline include:
  • the stenotic area obtained after removing the misjudged area is the second stenotic lesion interval.
  • the above-mentioned method for accurately obtaining a narrow lesion interval further includes:
  • the two points where the fitted pipe diameter interval curve and the real pipe diameter curve intersect are a second entry point and a second exit point, and the second entry point and the second The interval between the exit points is the third stenotic lesion interval.
  • the above-mentioned method for accurately obtaining the stenotic lesion interval includes:
  • 3D modeling is carried out according to the real-time diameter D t of the blood vessel, the length L of the blood vessel center line and the stenosis interval to form a 3D vessel model with stenotic lesion interval;
  • N-edge meshing is performed along the circumference of the three-dimensional blood vessel model with stenotic lesions to form a single-layer mesh model, where N ⁇ 6;
  • the surface layering process is performed on the single-layer grid model to form a double-layer grid model, that is, a blood vessel mathematical model.
  • N-edge meshing is performed along the circumference of the three-dimensional blood vessel model with stenotic lesion intervals to form a single-layer grid model, where N ⁇ 6 methods include:
  • every N triangle combination is converted into an N-sided shape to form an N-sided initial mesh
  • the method for meshing along the circumference of the three-dimensional blood vessel model with stenotic lesion intervals using triangles as the smallest unit includes:
  • the method for performing surface layering processing on the single-layer grid model to form a double-layer grid model includes:
  • Three-dimensional modeling is performed according to the blood vessel wall thickness h, the blood vessel starting diameter D, the blood vessel ending diameter D and the blood vessel centerline length L, and a three-dimensional truncated truncated model is formed on the inner surface or outer surface of the single-layer mesh model;
  • N-edge grid division is performed along the circumference of the three-dimensional truncated truncated model to form another single-layer grid model;
  • Two layers of the single-layer grid model and the blood vessel wall thickness h form the double-layer grid model, that is, the blood vessel mathematical model.
  • the present application provides a computer storage medium, and when the computer program is executed by a processor, the above-mentioned method for accurately acquiring a narrow lesion interval can be implemented.
  • the present application provides a method and a storage medium for accurately obtaining a stenosis lesion interval, and further corrects the vascular stenosis with coarse precision by refitting the three-dimensional modeling of the vessel wall to ensure the accuracy of the stenosis lesion interval.
  • FIG. 1 is a flowchart of an embodiment of a method for accurately obtaining a narrow lesion interval according to the present application
  • Fig. 2 is the flow chart of S100 of this application.
  • Fig. 5 is the flow chart of S200 of this application.
  • FIG. 7 is a flowchart of S230 of the application.
  • FIG. 10 is a flowchart of another embodiment of the method for accurately obtaining a stenotic lesion interval according to the present application.
  • the present application provides a method for accurately obtaining a narrow lesion interval, including:
  • N-edge meshing is performed along the circumference of the three-dimensional blood vessel model with stenotic lesions to form a single-layer mesh model, where N ⁇ 6, including:
  • S121 along the circumference of the three-dimensional blood vessel model with the stenotic lesion interval, perform grid division with triangles as the smallest unit, including: dividing the three-dimensional blood vessel model with the narrow lesion interval into K segments, and in each segment of the three-dimensional blood vessel model On the circumferential surface, the triangle is used as the smallest element for mesh division.
  • every N triangle combination is converted into an N-sided shape to form an N-sided initial mesh
  • the surface layering process is performed on the single-layer grid model to form a double-layer grid model, that is, a blood vessel mathematical model, including:
  • the two-layer single-layer grid model and the blood vessel wall thickness h form a double-layer grid model, that is, a blood vessel mathematical model.
  • i represents the curve sampling point of the ith pipe diameter
  • n represents the sum of the number of pipe diameter curve sampling
  • xi represents the length of the curve sampling point of the ith pipe diameter
  • y i represents the pipe diameter at xi ;
  • the curve between the first entry point and the first exit point is the initially determined stenosis position, that is, the first stenotic lesion interval.
  • the misjudged stenosis area is removed from the first stenotic lesion interval to obtain a second stenotic lesion interval, including:
  • A represents the stenosis degree of the blood vessel
  • D min represents the minimum diameter of the blood vessel between the first entry point and the first exit point
  • D in and D out represent the vessel diameter of the first entry point and the first exit point, respectively vascular diameter.
  • the misjudged stenosis area is removed from the first stenotic lesion interval, and the second stenotic lesion interval is obtained, including:
  • the stenotic area obtained again after removing the misjudged area is the second stenotic lesion interval.
  • a method for accurately obtaining a narrow lesion interval provided by the present application further includes:
  • the present application provides a computer storage medium, and when the computer program is executed by a processor, the above-mentioned method for accurately acquiring a narrow lesion interval can be implemented.
  • aspects of the present invention may be embodied as a system, method or computer program product. Accordingly, various aspects of the present invention may be embodied in the form of an entirely hardware implementation, an entirely software implementation (including firmware, resident software, microcode, etc.), or a combination of hardware and software aspects, It may be collectively referred to herein as a "circuit,” "module,” or “system.” Furthermore, in some embodiments, various aspects of the present invention may also be implemented in the form of a computer program product on one or more computer-readable media having computer-readable program code embodied thereon. Implementation of the method and/or system of embodiments of the invention may involve performing or completing selected tasks manually, automatically, or a combination thereof.
  • a data processor such as a computing platform for executing a plurality of instructions.
  • the data processor includes volatile storage for storing instructions and/or data and/or non-volatile storage for storing instructions and/or data, such as a magnetic hard disk and/or a Move media.
  • a network connection is also provided.
  • a display and/or user input device such as a keyboard or mouse, is optionally also provided.
  • the computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium.
  • the computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus or device, or a combination of any of the above. More specific examples (non-exhaustive list) of computer-readable storage media would include the following:
  • a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.
  • a computer-readable signal medium may include a propagated data signal in baseband or as part of a carrier wave, with computer-readable program code embodied thereon. Such propagated data signals may take a variety of forms including, but not limited to, electromagnetic signals, optical signals, or any suitable combination of the foregoing.
  • a computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device .
  • Program code embodied on a computer-readable medium may be transmitted using any suitable medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
  • computer program code for performing operations for various aspects of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages such as Java, Smalltalk, C++, and conventional procedural programming languages, such as The "C" programming language or similar programming language.
  • the program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer, or entirely on the remote computer or server.
  • the remote computer may be connected to the user's computer through any kind of network - including a local area network (LAN) or wide area network (WAN) - or may be connected to an external computer (eg using an Internet service provider via Internet connection).
  • LAN local area network
  • WAN wide area network
  • These computer program instructions can also be stored on a computer readable medium, the instructions cause a computer, other programmable data processing apparatus, or other device to operate in a particular manner, whereby the instructions stored on the computer readable medium produce the An article of manufacture of instructions implementing the functions/acts specified in one or more blocks of the flowcharts and/or block diagrams.
  • Computer program instructions can also be loaded on a computer (eg, a coronary artery analysis system) or other programmable data processing device to cause a series of operational steps to be performed on the computer, other programmable data processing device or other device to produce a computer-implemented process , such that instructions executing on a computer, other programmable apparatus, or other device provide a process for implementing the functions/acts specified in the flowchart and/or one or more block diagram blocks.
  • a computer eg, a coronary artery analysis system
  • other programmable data processing device to produce a computer-implemented process , such that instructions executing on a computer, other programmable apparatus, or other device provide a process for implementing the functions/acts specified in the flowchart and/or one or more block diagram blocks.

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Health & Medical Sciences (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Radiology & Medical Imaging (AREA)
  • Medical Informatics (AREA)
  • General Health & Medical Sciences (AREA)
  • Geometry (AREA)
  • Quality & Reliability (AREA)
  • Computer Graphics (AREA)
  • Software Systems (AREA)
  • Epidemiology (AREA)
  • Primary Health Care (AREA)
  • Public Health (AREA)
  • Apparatus For Radiation Diagnosis (AREA)

Abstract

L'invention concerne un procédé et un support de stockage pour l'acquisition précise d'une gamme de lésions sténosées, comprenant: la réalisation d'une modélisation tridimensionnelle selon un diamètre Dt de vaisseau en temps réel, une longueur de ligne médiane de vaisseau L, et une gamme de sténoses pour former un modèle mathématique ayant une gamme de lésions étroite (S100); la détermination préliminaire pour obtenir une première gamme de lésions sténosées (S200); l'élimination de régions sténosées déterminées par erreur depuis la première gamme de lésions sténosées pour obtenir une seconde gamme de lésions sténosées (S300). Dans le procédé et le support de stockage pour l'acquisition précise d'une gamme de lésions sténosées, au moyen d'une modélisation d'une paroi vasculaire en trois dimensions après réajustement, et une correction supplémentaire pour une sténose vasculaire de précision grossière, la précision d'une gamme de lésions étroite étant assurée.
PCT/CN2020/131703 2020-11-25 2020-11-26 Procédé et support de stockage pour l'acquisition précise d'une gamme de lésions sténosées Ceased WO2022109907A1 (fr)

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CN202011342207.9 2020-11-25
CN202011342207.9A CN112419280B (zh) 2020-11-25 2020-11-25 精确获取狭窄病变区间的方法及存储介质

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Cited By (7)

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CN115619979A (zh) * 2022-11-22 2023-01-17 广州中望龙腾软件股份有限公司 半狭长面清理方法、终端以及存储介质
US12138027B2 (en) 2016-05-16 2024-11-12 Cath Works Ltd. System for vascular assessment
US12315076B1 (en) 2021-09-22 2025-05-27 Cathworks Ltd. Four-dimensional motion analysis of a patient's coronary arteries and myocardial wall
US12354755B2 (en) 2012-10-24 2025-07-08 Cathworks Ltd Creating a vascular tree model
US12387325B2 (en) 2022-02-10 2025-08-12 Cath Works Ltd. System and method for machine-learning based sensor analysis and vascular tree segmentation
US12446965B2 (en) 2023-08-09 2025-10-21 Cathworks Ltd. Enhanced user interface and crosstalk analysis for vascular index measurement
US12499646B1 (en) 2025-01-17 2025-12-16 Cathworks Ltd. Three-dimensional sizing tool for cardiac assessment

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CN110889896A (zh) * 2019-11-11 2020-03-17 苏州润迈德医疗科技有限公司 获取血管狭窄病变区间及三维合成方法、装置和系统

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CN110584639A (zh) * 2019-09-04 2019-12-20 北京工业大学 一种对cta冠状动脉图像进行数据处理预测ffr的方法

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US20150087956A1 (en) * 2012-09-25 2015-03-26 Toshiba Medical Systems Corporation X-ray diagnostic apparatus and medical image processing apparatus
CN108038848A (zh) * 2017-12-07 2018-05-15 上海交通大学 基于医学影像序列斑块稳定性指标的快速计算方法及系统
CN110367965A (zh) * 2018-09-19 2019-10-25 苏州润迈德医疗科技有限公司 便捷测量冠状动脉血管评定参数的方法、装置及系统
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CN110889896A (zh) * 2019-11-11 2020-03-17 苏州润迈德医疗科技有限公司 获取血管狭窄病变区间及三维合成方法、装置和系统

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US12354755B2 (en) 2012-10-24 2025-07-08 Cathworks Ltd Creating a vascular tree model
US12138027B2 (en) 2016-05-16 2024-11-12 Cath Works Ltd. System for vascular assessment
US12315076B1 (en) 2021-09-22 2025-05-27 Cathworks Ltd. Four-dimensional motion analysis of a patient's coronary arteries and myocardial wall
US12387325B2 (en) 2022-02-10 2025-08-12 Cath Works Ltd. System and method for machine-learning based sensor analysis and vascular tree segmentation
US12423813B2 (en) 2022-02-10 2025-09-23 Cathworks Ltd. System and method for machine-learning based sensor analysis and vascular tree segmentation
CN115619979A (zh) * 2022-11-22 2023-01-17 广州中望龙腾软件股份有限公司 半狭长面清理方法、终端以及存储介质
CN115619979B (zh) * 2022-11-22 2023-06-02 广州中望龙腾软件股份有限公司 半狭长面清理方法、终端以及存储介质
US12446965B2 (en) 2023-08-09 2025-10-21 Cathworks Ltd. Enhanced user interface and crosstalk analysis for vascular index measurement
US12499646B1 (en) 2025-01-17 2025-12-16 Cathworks Ltd. Three-dimensional sizing tool for cardiac assessment

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