Magnetic resonance-based vascular structure analysis method and apparatus, computer device, and storage medium
By combining SE and GE sequences in magnetic resonance imaging, the average radius of blood vessels and microvascular density are calculated, solving the problem that existing MRI techniques cannot provide quantitative indicators, and realizing non-invasive, high-precision early diagnosis of tumors and monitoring of treatment effects.
Patent Information
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- SHENZHEN INST OF ADVANCED TECH
- Filing Date
- 2024-12-24
- Publication Date
- 2026-07-02
AI Technical Summary
Existing MRI imaging techniques cannot provide accurate quantitative indicators of blood vessel size and microvessel density, which affects early diagnosis of tumors and monitoring of treatment effectiveness. Furthermore, they rely on invasive examinations and cannot provide detailed data on the status of tumor microvessels.
By acquiring the first T2 relaxation time and the second T2 relaxation time, and combining MRI with SE and GE sequences, the average radius of blood vessels and microvessel density in the lesion tissue were calculated, and medical analysis was performed using a convolutional neural network.
It provides quantitative analysis of blood vessels within diseased tissue, enabling the assessment of vascular conditions and changes in the surrounding area, improving the accuracy of early tumor diagnosis, reducing trauma to patients, and achieving more comprehensive monitoring of treatment outcomes.
Smart Images
Figure CN2024141663_02072026_PF_FP_ABST
Abstract
Description
Methods, devices, computer equipment and storage media for magnetic resonance vascular structure analysis Technical Field
[0001] This invention relates to the fields of magnetic resonance and medical technology, and in particular to a method, apparatus, computer equipment and storage medium for magnetic resonance vascular structure analysis. Background Technology
[0002] Angiogenesis is a crucial stage in tumor development and progression. Rapidly growing tumors exhibit increased vascular density and larger vessel diameters compared to normal tissues. Tumor angiogenesis, associated with rapid tumor growth, is characterized by increased vascular density and larger vessel diameters in certain areas of the tumor compared to normal tissue. Microvascular density is a major factor predicting tumor invasiveness and prognosis in patients with different tumor types. Routine examinations, due to the small size of biopsy specimens, may not extract samples from the most aggressive or typical parts of the tumor. Furthermore, the invasiveness of immunohistochemistry prevents its use for post-treatment follow-up. Among all in vivo microvascular imaging methods, MRI can provide information on brain perfusion.
[0003] Currently, MRI-based vascular imaging technology has made some progress, with commonly used imaging methods including contrast-based imaging and functional MRI (fMRI). Some existing techniques improve tumor visualization by using specific contrast agents, such as dynamic contrast-enhanced MRI (DCE-MRI) and vascular imaging (MRA). However, most of these techniques cannot provide accurate quantitative indicators such as vessel size and microvessel density, affecting the diagnosis of early-stage tumors and the monitoring of treatment outcomes. Traditional MRI imaging methods rely on invasive procedures (such as biopsies) to obtain tumor tissue samples. Furthermore, many techniques cannot provide detailed data on tumor microvascular status or accurately monitor changes after tumor treatment. Summary of the Invention
[0004] Based on this, it is necessary to address the technical problem of poor vascular structure analysis results in existing technologies by proposing a magnetic resonance vascular structure analysis method, device, computer equipment, and storage medium.
[0005] In a first aspect, a magnetic resonance imaging (MRI) method for analyzing vascular structures is provided, the method comprising:
[0006] The first T2 relaxation time and the second T2 relaxation time are obtained, wherein the first T2 relaxation time is the T2 relaxation time obtained by performing magnetic resonance imaging on the lesion tissue of the target living organism using the SE sequence, and the second T2 relaxation time is the T2 relaxation time obtained by performing magnetic resonance imaging on the lesion tissue using the GE sequence.
[0007] The average radius of blood vessels and the density of microvessels in the diseased tissue were determined by calculation based on the first T2 relaxation time and the second T2 relaxation time.
[0008] Medical analysis is performed based on the average radius of the blood vessels and the microvessel density.
[0009] Secondly, a magnetic resonance vascular structure analysis device is provided, the device comprising:
[0010] The acquisition module is used to acquire a first T2 relaxation time and a second T2 relaxation time. The first T2 relaxation time is the T2 relaxation time obtained by performing magnetic resonance imaging on the lesion tissue of the target living organism using the SE sequence, and the second T2 relaxation time is the T2 relaxation time obtained by performing magnetic resonance imaging on the lesion tissue using the GE sequence.
[0011] The calculation module is used to calculate based on the first T2 relaxation time and the second T2 relaxation time to determine the average radius of blood vessels and microvessel density in the diseased tissue.
[0012] An analysis module is used for medical analysis based on the average radius of the blood vessels and the microvessel density.
[0013] Thirdly, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described magnetic resonance vascular structure analysis method.
[0014] Fourthly, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the above-described magnetic resonance vascular structure analysis method.
[0015] The magnetic resonance vascular structure analysis method proposed in this invention obtains a first T2 relaxation time and a second T2 relaxation time. The first T2 relaxation time is obtained by performing MRI on the lesion tissue of the target living organism using an SE sequence, and the second T2 relaxation time is obtained by performing MRI on the lesion tissue using a GE sequence. Then, based on the first and second T2 relaxation times, the average radius and microvessel density of blood vessels within the lesion tissue are calculated. Finally, medical analysis is performed based on the average radius and microvessel density of blood vessels within the lesion tissue. This method can provide the average radius and microvessel density of blood vessels within the lesion tissue, and the analysis can not only assess the vascular condition of the lesion tissue, but also quantitatively analyze the vascular changes in the surrounding area of the lesion tissue, which helps to achieve a more comprehensive treatment effect and improves the accuracy of early tumor diagnosis. Attached Figure Description
[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0017] in:
[0018] Figure 1 shows the application environment of the magnetic resonance vascular structure analysis method in one embodiment;
[0019] Figure 2 is a flowchart of a magnetic resonance vascular structure analysis method in one embodiment;
[0020] Figure 3 is a schematic diagram of vascular structure imaging parameters of a magnetic resonance vascular structure analysis method in one embodiment;
[0021] Figure 4 shows a 9.4T magnetic resonance imaging (MRI) and pathological images of the magnetic resonance vascular structure analysis method in one embodiment;
[0022] Figure 5 is a structural block diagram of a magnetic resonance vascular structure analysis device in one embodiment;
[0023] Figure 6 is a structural block diagram of a computer device in one embodiment;
[0024] Figure 7 is a structural block diagram of a computer device in another embodiment. Detailed Implementation
[0025] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein in the specification of the application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "comprising" and "having," and any variations thereof, in the specification, claims, and foregoing drawings of this application, are intended to cover non-exclusive inclusion. The terms "first," "second," etc., in the specification, claims, or foregoing drawings of this application are used to distinguish different objects, not to describe a particular order.
[0026] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.
[0027] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0028] The magnetic resonance vascular structure analysis method provided in this embodiment of the invention can be applied in the application environment shown in Figure 1. In this environment, the client 110 communicates with the server 120 via a network. The server 120 can receive a first T2 relaxation time and a second T2 relaxation time from the client 110. The first T2 relaxation time is obtained by performing magnetic resonance imaging (MRI) on the lesion tissue of the target living organism using an SE sequence, and the second T2 relaxation time is obtained by performing MRI on the lesion tissue using a GE sequence. Based on the first and second T2 relaxation times, the average radius and microvascular density of blood vessels within the lesion tissue are calculated. Finally, medical analysis is performed based on the average radius and microvascular density of the blood vessels. This provides the average radius and microvascular density of blood vessels within the lesion tissue, and the analysis not only assesses the vascular condition of the lesion tissue but also quantitatively analyzes vascular changes in the surrounding area, contributing to a more comprehensive treatment effect and improving the accuracy of early tumor diagnosis. The client 110 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices. The server 120 can be implemented using a standalone server or a server cluster consisting of multiple servers. The invention will now be described in detail through specific embodiments.
[0029] Please refer to Figure 2, which is a flowchart illustrating a magnetic resonance vascular structure analysis method according to an embodiment of the present invention, including the following steps:
[0030] Step S101: Obtain the first T2 relaxation time and the second T2 relaxation time, wherein the first T2 relaxation time is the T2 relaxation time obtained by performing magnetic resonance imaging on the lesion tissue of the target living organism using the SE sequence, and the second T2 relaxation time is the T2 relaxation time obtained by performing magnetic resonance imaging on the lesion tissue using the GE sequence.
[0031] The target living body can be a human, an animal, or something similar.
[0032] Gradient echo (GE) sequences are sequences that generate echoes based on changes in gradient magnetic fields. Compared to spin echo sequences, GE sequences are faster and more sensitive to fluids (such as blood). Their characteristics are as follows: Vascular Imaging: GE sequences are highly sensitive to blood flow, especially in images of rapidly moving fluids (such as blood) and arteries, providing dynamic information about blood flow. Therefore, they provide good representation of vascular contours, blood flow velocity, and direction, particularly when displaying vascular morphology and blood flow changes (such as aneurysms and vascular malformations). Signal Characteristics: Due to the characteristics of gradient echo sequences, flowing blood in vessels produces a strong signal during imaging, while stationary tissue shows a lower signal. Therefore, GE sequences are particularly suitable for observing vascular structure and blood flow dynamics, especially when examining lesions with vascular activity.
[0033] Spin echo (SE) sequences, based on the principle of spin echo, generate imaging signals using 90° and 180° radiofrequency pulses, suitable for providing high tissue contrast. Their characteristics are as follows: Vascular Imaging: SE sequences are primarily used to emphasize the transverse relaxation time (T2) of tissues and provide high tissue contrast. Because the composition of the vessel wall differs from the surrounding tissue, SE sequences can more clearly display the vessel wall, the surrounding tissue, and the contrast between the vessel and surrounding structures. This is important for detecting changes in the vessel wall (such as arteriosclerosis or intimal thickening). Signal Characteristics: SE sequences are particularly adept at capturing details within tissues, revealing the structural features of blood vessels, especially when the contrast between the vessel wall and surrounding tissue is high. In some cases, SE sequences can be used to visualize blood flow within the vessel lumen, although slightly inferior to GE sequences, it still reveals more detail in the vessel wall.
[0034] Combining GE and SE signals using SAGE (spin and gradient echo) sequences provides more comprehensive vascular imaging by leveraging the advantages of both: Dynamics and detail complement each other: GE sequences provide dynamic information about blood flow, helping to depict vascular morphology and blood flow velocity, especially valuable in assessing vascular function (such as flow obstruction, aneurysms, etc.). SE sequences provide higher tissue contrast, particularly in displaying the vessel wall and surrounding tissue structures. It helps to clearly present the details of the vessel wall and pathological features of the tissue. Enhanced vascular clarity and diagnostic information: Combining GE and SE sequences yields more comprehensive vascular imaging. For example, in assessing cerebrovascular diseases, aneurysms, vascular malformations, or cardiovascular diseases, GE sequences help to visualize blood flow, while SE sequences emphasize the details of vascular structures. GE signals emphasize blood flow information and rapid dynamic changes, while SE signals emphasize the clarity of static structures. In some complex vascular lesions, such as those with thickened vessel walls, thrombosis, or arterial stenosis, combining these two sequences can provide a more comprehensive diagnostic basis.
[0035] Dual-sequence imaging: In practice, physicians often choose to perform GE and SE sequences simultaneously. For example, in an MRI scan, a GE sequence might be performed first to capture blood flow-related information, followed by an SE sequence to emphasize structural details of the vessel wall or lesion area. By comparing the images from the two sequences, lesions or abnormalities within the blood vessels can be identified more accurately, such as vascular occlusion, aneurysms, thickening or irregularity of the vessel wall, etc.
[0036] It should be noted that the GE sequence provides highly sensitive blood flow information, suitable for observing the morphology of blood vessels, blood flow dynamics, and their changes. The SE sequence provides high-contrast tissue imaging, suitable for observing the structure of the vessel wall and surrounding tissues, revealing details. Combined use: By combining the advantages of GE and SE, a more comprehensive vascular image can be obtained, capturing both dynamic changes in blood flow and clearly displaying the details of the vessel wall and surrounding tissues, enhancing the diagnostic capability for vascular abnormalities (such as thrombosis, aneurysm, etc.).
[0037] Step S102: Calculate based on the first T2 relaxation time and the second T2 relaxation time to determine the average radius of blood vessels and microvessel density in the lesion tissue;
[0038] The first T2 relaxation time is expressed as follows:
[0039] Where, ΔR 2se This refers to the first T2 relaxation time. T2 relaxation time is expressed as the time after contrast agent is injected into the target living organism during MRI imaging of the target living organism using SE sequence. T2 relaxation time is expressed as the time before contrast agent is injected into the target living organism during MRI imaging of lesion tissue using an SE sequence. TE refers to the echo time. post S represents the image signal intensity of the SE sequence after injection of contrast agent into the target living organism. pre This indicates the signal intensity corresponding to the SE sequence obtained before the contrast agent was injected.
[0040] The second T2 relaxation time is expressed as follows:
[0041] Where, ΔR 2ge This is the second T2 relaxation time. This represents the T2 relaxation time after contrast agent is injected into the target living organism during MRI imaging of the target living organism's lesion tissue using the GE sequence. T2 relaxation time is expressed as the time before contrast agent is injected into the target living organism during MRI imaging of lesion tissue using a GE sequence. TE refers to the echo time. This indicates the image signal intensity corresponding to the GE sequence after the contrast agent is injected into the target living organism. This indicates the signal intensity corresponding to the GE sequence obtained before the contrast agent was injected.
[0042] The average radius of blood vessels within the diseased tissue is expressed as follows:
[0043] R refers to the average radius of blood vessels within the diseased tissue, γ is the gyromagnetic ratio, and B... o Let ΔR be the static magnetic field strength. 2se This refers to the first T2 relaxation time, ΔR 2ge It is the second T2 relaxation time, D refers to the diffusion coefficient, and ΔX refers to the additional sensitivity difference between the blood vessel and the surrounding tissue.
[0044] Microvessel density is represented as follows:
[0045] Q refers to microvascular density.
[0046] Step S103: Perform medical analysis based on the average radius of the blood vessels and the microvessel density.
[0047] In one embodiment, medical analysis is performed based on the average radius of the blood vessels, the microvessel density, the past average radius of blood vessels in the target living organism, and the past microvessel density.
[0048] Specifically, an analysis report is generated based on the average radius of the blood vessels, the microvascular density, the past average radius of blood vessels in the target living organism, the past microvascular density, and the trained analysis model, wherein the analysis model is obtained by training a model based on a convolutional neural network.
[0049] As an example, the lesion tissue can be a tumor region in the human body. Indicators such as microvascular density and vessel size (e.g., average vessel radius) inside and outside the tumor are crucial for tumor grading, monitoring tumor growth, evaluating treatment response, and monitoring treatment efficacy. Quantitative analysis can provide doctors with a more scientific basis for treatment decisions, especially in monitoring the effects of anti-angiogenic therapy, effectively assessing changes in tumor microcirculation.
[0050] As an example, images obtained from MRI of lesions in a living target using SE sequences and MRI of lesions in a living target using GE sequences can also be analyzed and visualized. By establishing a quantitative expression model, the images are analyzed to provide visualized images and digital reports, including vascular features and microvascular density in the tumor region. This technology can rapidly generate high-precision imaging results through computer-aided analysis, improving the efficiency and accuracy of tumor diagnosis.
[0051] As an example, this invention is applicable to the early diagnosis of tumors and can also help monitor the process and effectiveness of tumor treatment. By comparing changes in vascular characteristics before and after treatment (such as changes in vessel radius and microvascular density), the effectiveness of treatment can be effectively assessed. Especially in anti-angiogenic therapy, this invention can reflect the contraction of tumor vessels and the improvement of microcirculation.
[0052] The technical solution of this invention can provide multi-dimensional quantitative assessment, not only analyzing the vascular structure of the tumor itself, but also quantitatively assessing the vascular status of the surrounding area, providing data support for accurate tumor staging and treatment planning. It offers a more scientific, non-invasive, and efficient technical means for the early diagnosis, treatment efficacy monitoring, and treatment effectiveness evaluation of brain tumors, improving the accuracy of tumor treatment and reducing patient risks.
[0053] This invention offers the following advantages: 1. High-precision quantitative analysis: It provides quantitative data on vascular structure and microvascular density, improving the accuracy of early tumor diagnosis. Existing MRI techniques typically rely on qualitative assessment of images, i.e., making judgments by visually observing changes in the tumor and its vascular structure. However, this method is easily affected by human factors and experience, potentially leading to missed or misdiagnosed early tumors. 2. Multidimensional assessment: It can not only assess the vascular condition within the tumor but also quantitatively analyze vascular changes in the surrounding area, facilitating more comprehensive monitoring of treatment effectiveness. While existing contrast-based MRI imaging techniques can assess tumor angiogenesis, they often focus on vascular information within the tumor area, lacking a comprehensive assessment of the microvascular environment surrounding the tumor. Tumor growth and spread depend not only on the vascular network within the tumor but also on the microvascular environment surrounding it, which plays a crucial role in tumor spread and metastasis. 3. Non-invasive: This invention is a non-invasive imaging technique that reduces physical harm to the patient. The invasiveness of traditional immunohistochemical examinations prevents their use for post-treatment follow-up. Furthermore, because biopsy specimens are small, they may not be taken from the most aggressive or typical parts of the tumor.
[0054] Referring to Figure 3, Figure 3 shows that the microvascular structural characteristics of different tumors differ under 3T imaging, improving the accuracy of tumor assessment. Based on the spin and gradient echo (SAGE) sequences and T2 sequences in Figure (right), relevant parameters for vascular structure imaging were calculated through quantitative analysis. Figure (left) shows the calculated parameters: vessel diameter (VSI), blood volume (CBV), vessel density (Q), slope of the long axis of the vascular structure, slope length of the vascular structure vortex curve, and slope axis of the vascular structure vortex curve.
[0055] Referring to Figure 4, 9.4T magnetic resonance imaging (MRI) and pathological images were obtained from the tumor region and healthy tissue in a C6 glioma model. Sections showing similar tumor locations are presented in T2-weighted, gradient echo, and spin echo images on SAGE sequences, along with corresponding pathological samples. In this study, regions of interest (ROIs) were superimposed on T2-weighted and SAGE images.
[0056] Please refer to Figure 5. In one embodiment, a magnetic resonance vascular structure analysis device is provided. The device includes: an acquisition module 10, used to acquire a first T2 relaxation time and a second T2 relaxation time, wherein the first T2 relaxation time is the T2 relaxation time obtained by performing magnetic resonance imaging on the lesion tissue of the target living organism using an SE sequence, and the second T2 relaxation time is the T2 relaxation time obtained by performing magnetic resonance imaging on the lesion tissue using a GE sequence.
[0057] The calculation module 20 is used to perform calculations based on the first T2 relaxation time and the second T2 relaxation time to determine the average radius of blood vessels and microvessel density in the diseased tissue.
[0058] Analysis module 30 is used for medical analysis based on the average radius of the blood vessels and the microvessel density.
[0059] The first T2 relaxation time is expressed as follows:
[0060] Where, ΔR 2se This refers to the first T2 relaxation time. T2 relaxation time is expressed as the time after contrast agent is injected into the target living organism during MRI imaging of the target living organism using SE sequence. T2 relaxation time is expressed as the time before contrast agent is injected into the target living organism during MRI imaging of lesion tissue using an SE sequence. TE refers to the echo time. post S represents the image signal intensity of the SE sequence after injection of contrast agent into the target living organism. pre This indicates the signal intensity corresponding to the SE sequence obtained before the contrast agent was injected.
[0061] The second T2 relaxation time is expressed as follows:
[0062] Where, ΔR 2ge This is the second T2 relaxation time. This represents the T2 relaxation time after contrast agent is injected into the target living organism during MRI imaging of the target living organism's lesion tissue using the GE sequence. T2 relaxation time is expressed as the time before contrast agent is injected into the target living organism during MRI imaging of lesion tissue using a GE sequence. TE refers to the echo time. This indicates the image signal intensity corresponding to the GE sequence after the contrast agent is injected into the target living organism. This indicates the signal intensity corresponding to the GE sequence obtained before the contrast agent was injected.
[0063] The average radius of blood vessels within the diseased tissue is expressed as follows:
[0064] R refers to the average radius of blood vessels within the diseased tissue, γ is the gyromagnetic ratio, and B... o Let ΔR be the static magnetic field strength. 2se This refers to the first T2 relaxation time, ΔR 2ge It is the second T2 relaxation time, D refers to the diffusion coefficient, and ΔX refers to the additional sensitivity difference between the blood vessel and the surrounding tissue.
[0065] Microvessel density is represented as follows:
[0066] Q refers to microvascular density.
[0067] Analysis module 30 is used to perform medical analysis based on the average radius of the blood vessels, the microvessel density, and the past average radius of blood vessels and past microvessel density of the target living organism.
[0068] Analysis module 30 is used to generate an analysis report based on the average radius of the blood vessels, the microvascular density, the past average radius of blood vessels in the target living organism, the past microvascular density, and a trained analysis model, wherein the analysis model is obtained by training a model based on a convolutional neural network.
[0069] In one embodiment, a computer device is provided, which can be a server, and its internal structure diagram is shown in Figure 6. The computer device includes a processor, memory, a network interface, and a database connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile and / or volatile storage media and internal memory. The non-volatile storage media stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface is used to communicate with external clients via a network connection. When the computer program is executed by the processor, it implements the functions or steps of a magnetic resonance vascular structure analysis method on the server side.
[0070] In one embodiment, a computer device is provided, which can be a client, and its internal structure diagram is shown in Figure 7. The computer device includes a processor, memory, network interface, display screen, and input device connected via a system bus. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external server via a network connection. When the computer program is executed by the processor, it implements the functions or steps of a magnetic resonance vascular structure analysis method on the client side.
[0071] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, performs the following steps:
[0072] The first T2 relaxation time and the second T2 relaxation time are obtained, wherein the first T2 relaxation time is the T2 relaxation time obtained by performing magnetic resonance imaging on the lesion tissue of the target living organism using the SE sequence, and the second T2 relaxation time is the T2 relaxation time obtained by performing magnetic resonance imaging on the lesion tissue using the GE sequence.
[0073] The average radius of blood vessels and the density of microvessels in the diseased tissue were determined by calculation based on the first T2 relaxation time and the second T2 relaxation time.
[0074] Medical analysis is performed based on the average radius of the blood vessels and the microvessel density.
[0075] This invention can provide the average radius of blood vessels and microvessel density within diseased tissue, and then analyze them. This not only assesses the vascular condition of the diseased tissue, but also quantitatively analyzes the vascular changes in the area surrounding the diseased tissue, which helps to achieve a more comprehensive treatment effect and improves the accuracy of early tumor diagnosis.
[0076] In one embodiment, a computer-readable storage medium is provided that stores a computer program, which, when executed by a processor, performs the following steps:
[0077] The first T2 relaxation time and the second T2 relaxation time are obtained, wherein the first T2 relaxation time is the T2 relaxation time obtained by performing magnetic resonance imaging on the lesion tissue of the target living organism using the SE sequence, and the second T2 relaxation time is the T2 relaxation time obtained by performing magnetic resonance imaging on the lesion tissue using the GE sequence.
[0078] The average radius of blood vessels and the density of microvessels in the diseased tissue were determined by calculation based on the first T2 relaxation time and the second T2 relaxation time.
[0079] Medical analysis is performed based on the average radius of the blood vessels and the microvessel density.
[0080] This invention can provide the average radius of blood vessels and microvessel density within diseased tissue, and then analyze them. This not only assesses the vascular condition of the diseased tissue, but also quantitatively analyzes the vascular changes in the area surrounding the diseased tissue, which helps to achieve a more comprehensive treatment effect and improves the accuracy of early tumor diagnosis.
[0081] It should be noted that the functions or steps that can be implemented by the computer-readable storage medium or computer device described above can be referred to the relevant descriptions on the server side and client side in the foregoing method embodiments. To avoid repetition, they will not be described one by one here.
[0082] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.
[0083] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.
[0084] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.
Claims
1. A method for magnetic resonance vascular structure analysis, characterized in that, The magnetic resonance vascular structure analysis method includes: The first T2 relaxation time and the second T2 relaxation time are obtained, wherein the first T2 relaxation time is the T2 relaxation time obtained by performing magnetic resonance imaging on the lesion tissue of the target living organism using the SE sequence, and the second T2 relaxation time is the T2 relaxation time obtained by performing magnetic resonance imaging on the lesion tissue using the GE sequence. The average radius of blood vessels and the density of microvessels in the diseased tissue were determined by calculation based on the first T2 relaxation time and the second T2 relaxation time. Medical analysis is performed based on the average radius of the blood vessels and the microvessel density.
2. The magnetic resonance vascular structure analysis method according to claim 1, characterized in that, The first T2 relaxation time is expressed as follows: Where, ΔR 2se This refers to the first T2 relaxation time. T2 relaxation time is expressed as the time after contrast agent is injected into the target living organism during MRI imaging of the target living organism using SE sequence. T2 relaxation time is expressed as the time before contrast agent is injected into the target living organism during MRI imaging of lesion tissue using an SE sequence. TE refers to the echo time. post S represents the image signal intensity of the SE sequence after injection of contrast agent into the target living organism. pre This indicates the signal intensity corresponding to the SE sequence obtained before the contrast agent was injected.
3. The magnetic resonance vascular structure analysis method according to claim 2, characterized in that, The second T2 relaxation time is expressed as follows: Where, ΔR 2ge This is the second T2 relaxation time. This represents the T2 relaxation time after contrast agent is injected into the target living organism during MRI imaging of the target living organism's lesion tissue using the GE sequence. T2 relaxation time is expressed as the time before contrast agent is injected into the target living organism during MRI imaging of lesion tissue using a GE sequence. TE refers to the echo time. This indicates the image signal intensity corresponding to the GE sequence after the contrast agent is injected into the target living organism. This indicates the signal intensity corresponding to the GE sequence obtained before the contrast agent was injected.
4. The magnetic resonance vascular structure analysis method according to claim 3, characterized in that, The average radius of blood vessels within the diseased tissue is expressed as follows: R refers to the average radius of blood vessels within the diseased tissue, γ is the gyromagnetic ratio, and B... o Let ΔR be the static magnetic field strength. 2se This refers to the first T2 relaxation time, ΔR 2ge It is the second T2 relaxation time, D refers to the diffusion coefficient, and ΔX refers to the additional sensitivity difference between the blood vessel and the surrounding tissue.
5. The magnetic resonance vascular structure analysis method according to claim 3, characterized in that, Microvessel density is represented as follows: Q refers to microvascular density.
6. The magnetic resonance vascular structure analysis method according to any one of claims 1 to 5, characterized in that, The steps of performing medical analysis based on the average radius of blood vessels and the microvessel density include: Medical analysis is performed based on the average radius of the blood vessels, the microvessel density, and the past average radius of blood vessels and past microvessel density of the target living organism.
7. The magnetic resonance vascular structure analysis method according to claim 6, characterized in that, The steps for medical analysis based on the average radius of the blood vessels, the microvessel density, and the past average radius of blood vessels and past microvessel density of the target living organism include: An analysis report is generated based on the average radius of the blood vessels, the microvessel density, the past average radius of blood vessels in the target living organism, the past microvessel density, and the trained analysis model, wherein the analysis model is obtained by training a convolutional neural network.
8. A magnetic resonance vascular structure analysis device, characterized in that, The magnetic resonance vascular structure analysis device includes: The acquisition module is used to acquire a first T2 relaxation time and a second T2 relaxation time. The first T2 relaxation time is the T2 relaxation time obtained by performing magnetic resonance imaging on the lesion tissue of the target living organism using the SE sequence, and the second T2 relaxation time is the T2 relaxation time obtained by performing magnetic resonance imaging on the lesion tissue using the GE sequence. The calculation module is used to calculate based on the first T2 relaxation time and the second T2 relaxation time to determine the average radius of blood vessels and microvessel density in the diseased tissue. An analysis module is used for medical analysis based on the average radius of the blood vessels and the microvessel density.
9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the magnetic resonance vascular structure analysis method as described in any one of claims 1 to 7.
10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the magnetic resonance vascular structure analysis method as described in any one of claims 1 to 7.