Magnetic resonance data analysis method and device, computer equipment and storage medium
Through the magnetization transfer imaging method without contrast agent and qMT MRI technology, combined with the dual-cell model for quantitative analysis, the problems of low signal-to-noise ratio and poor resolution of breast tumor data analysis in the prior art were solved, and the accurate evaluation of the microvascular changes and tissue characteristics of breast tumors was achieved.
Patent Information
- Application Number
- CN202510017181.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Priority Date
- 2024-12-27
- Filing Date
- 2025-01-06
- Publication Date
- 2025-04-18
AI Technical Summary
The existing breast tumor data analysis technology has defects such as low signal-to-noise ratio, poor imaging resolution, and inability to provide detailed tissue structure information, making it difficult to accurately evaluate the microvascular changes and tissue characteristics of the tumor.
The magnetization transfer imaging method without contrast agent was used to combine qMT MRI technology, and quantitative analysis was performed through a dual-cell model to calculate parameters such as PSR, krf and R1f to obtain the qMT parameter map of breast tumors, including data such as the exchange rate between water molecules and macromolecules and microvascular density.
Accurate quantitative analysis of breast tumors is achieved, the accuracy and reliability of data analysis is improved, more comprehensive tumor monitoring is provided, and the potential risks of contrast agents are avoided.
Smart Images
Figure CN119846529A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the technical field of magnetic resonance imaging, and in particular to a magnetic resonance data analysis method and device. Background Art
[0002] Magnetization transfer (MT) imaging is very sensitive to changes in macromolecular content in tissues and, therefore, has the potential to be used as a non-invasive method to explore the complex tumor environment of cancer. qMT MRI describes the process of free water proton saturation at different offset frequencies by modeling the exchange rate of free water and macromolecular protons, while taking into account the effects of the power of the MT saturation pulse and the T1 relaxation rate. To improve the specificity of MT MRI measurements, the qMT MRI method was adopted, using a two-pool model to describe the bound and free water populations in tissues. qMT MRI has been widely used in neurological imaging studies, but its application in breast tumor data analysis has not been fully explored to reveal tumor characteristics such as angiogenesis and cellular activity. Existing breast tumor data analysis technologies, such as traditional MRI imaging, have defects such as low signal-to-noise ratio, poor imaging resolution, and inability to provide detailed tissue structure information.
[0003] In order to overcome these defects, the present application proposes a magnetic resonance data analysis method, apparatus, computer equipment and storage medium. Summary of the invention
[0004] The purpose of this application is to provide a magnetic resonance data analysis method, device, computer equipment and storage medium to solve the above-mentioned problems.
[0005] To achieve the above objectives, this application provides the following technical solutions:
[0006] In a first aspect, the present application provides a magnetic resonance data analysis method, comprising:
[0007] Acquiring disease information of the patient, wherein the disease information includes: a region of interest and a qMT parameter;
[0008] Analyzing the region of interest and the qMT parameters to obtain quantitative data;
[0009] A quantitative analysis report is generated according to the quantitative data.
[0010] In a second aspect, the present application provides a magnetic resonance data analysis device, comprising:
[0011] Acquisition module: acquiring disease information of the patient, the disease information including: region of interest, qMT parameters;
[0012] Analysis module: analyzing the region of interest and the qMT parameters to obtain quantitative data;
[0013] Report generation module: generates a quantitative analysis report based on the quantitative data.
[0014] In a third aspect, the present application provides a computer device, comprising a processor and a memory coupled to the processor, wherein the memory stores program instructions for implementing a magnetic resonance data analysis method; and the processor is used to execute the program instructions stored in the memory to implement magnetic resonance data analysis.
[0015] In a fourth aspect, the present application provides a storage medium storing program instructions executable by a processor, wherein the program instructions are used to execute a magnetic resonance data analysis method.
[0016] The present application provides a magnetic resonance data analysis method, device, computer equipment and storage medium, which have the following beneficial effects:
[0017] (1) The use of contrast-free magnetization transfer imaging avoids the potential risks of contrast agents, which is especially safer for patients who are allergic to contrast agents or have renal insufficiency. At the same time, qMT imaging technology is used to obtain qMT parameter maps of breast tumors, including data such as the exchange rate between water molecules and macromolecules and microvascular density, to accurately evaluate microvascular changes and tissue characteristics of breast tumors.
[0018] (2) Quantitative analysis of qMT parameters was performed using the dual-pool model to calculate parameter maps such as PSR, krf, and R1f; compared with the qualitative analysis of existing technologies, it provides more accurate quantitative data, such as microvascular density and vessel size, and improves the accuracy and reliability of data analysis;
[0019] (3) The analysis of the region of interest includes the lesion tissue and the ipsilateral and contralateral fibroglandular tissues. The average values of PSR, krf, and R1f in breast lesions and FGT are compared. Not only the vascular characteristics inside the tumor are analyzed, but also the microvascular status of the area around the tumor is evaluated, providing more comprehensive tumor monitoring. BRIEF DESCRIPTION OF THE DRAWINGS
[0020] Figure 1 Schematic diagram of the process of the magnetic resonance data analysis method of Example 1 of the present application;
[0021] Figure 2 This is a schematic diagram of the dual-pool model of Example 1 of the present application;
[0022] Figure 3 The qMT image of the patient in Example 1 of the present application and its corresponding parameter map;
[0023] Figure 4 This is a schematic structural diagram of a magnetic resonance data analysis device according to Example 2 of the present application;
[0024] Figure 5 This is a schematic diagram of the computer device structure of Example 3 of the present application;
[0025] Figure 6 This is a schematic diagram of the storage medium structure of Example 4 of the present application. DETAILED DESCRIPTION
[0026] It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.
[0027] The following is an analysis of the solutions in the prior art in combination with related technologies.
[0028] DCE-MRI (dynamic contrast-enhanced MRI): It detects tumor areas by enhancing the image signal through contrast agent injection, but there are risks in contrast agent use and it cannot directly provide quantitative information on blood vessels or microvessels. Traditional MRI technology: Although it can be used to detect breast tumors, it cannot accurately evaluate the microenvironment and microvascular conditions of the tumor due to insufficient signal contrast between tissues.
[0029] Existing technologies have the following disadvantages: (1) Contrast agent dependence: DCE-MRI and other technologies require injection of contrast agents, which may pose risks to patients with allergies or renal insufficiency. (2) Insufficient signal strength: Traditional MRI cannot accurately distinguish between tumors and surrounding healthy tissues, especially in the early stages of tumors, when signal contrast is low. (3) Lack of microvascular analysis capabilities: Existing technologies are generally unable to penetrate into the microvascular level and cannot comprehensively evaluate microvascular changes in tumors and surrounding tissues.
[0030] The present application proposes a magnetic resonance data analysis method, apparatus, computer equipment and storage medium, which provide accurate analysis of tumors and their surrounding microvascular environment in a non-invasive manner.
[0031] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.
[0032] Example 1
[0033] See also Figure 1 , is a flow chart of the magnetic resonance data analysis method of Example 1 of the present application; the steps include:
[0034] S1: Obtaining disease information of a patient, wherein the disease information includes: a region of interest and qMT parameters.
[0035] In this embodiment, a 1.5T or 3T MRI system is used to obtain the qMT parameters of the patient's region of interest, ipsilateral and contralateral breast fibroglandular bodies by qMT imaging technology. Compared with the ipsilateral and contralateral breast fibroglandular bodies of breast cancer patients, the absolute values of the pool size ratio, the longitudinal magnetization rate from the restricted pool to the free pool, and the longitudinal relaxation rate of the free pool in the tumor are significantly reduced. This application shows that qMT has potential clinical value by calculating the qMT difference between the lesion tissue and the ipsilateral and contralateral breast fibroglandular bodies.
[0036] S2: Analyze the region of interest and the qMT parameters to obtain quantitative data.
[0037] In this embodiment, analyzing the region of interest includes: selecting the breast tumor region and the ipsilateral and contralateral breast fibroglandular bodies as the region of interest, comparing the qMT parameters of the tumor tissue and the normal tissue, and performing statistical analysis.
[0038] Quantitative analysis of qMT parameters includes: magnetization transfer (MT) imaging is sensitive to changes in the content of macromolecules in tissues. qMT MRI characterizes the exchange rate between free water and macromolecular protons by modeling the saturation of free water protons at a series of offset frequencies, while considering the power of the MT saturation pulse and the contribution of the apparent relaxation rate. In order to improve the specificity of MT MRI measurements, a quantitative MT (qMT) MRI method is proposed. Specifically:
[0039] The qMT parameters were quantitatively analyzed using a dual-pool model. The dual-pool model was used to describe the populations of bound water and free water in tissues and to quantitatively analyze the qMT parameters. Based on the dual-pool model, the pool size ratio PSR and the basic rate constant k of the exchange of saturated spins between the two pools were calculated. rf and k fr and the longitudinal relaxation rate R of the free pool 1f .
[0040] The longitudinal relaxation rate R of the free pool 1f =1 / T 1f , the longitudinal relaxation rate R of the confined pool 1r =1 / T 1r ; where T is the reciprocal of R.
[0041] The pool size ratio is PSR=k fr / k rf =M 0r / M 0f , where k fr The longitudinal magnetization rate from the free pool to the confined pool, M 0r 、M 0f is the longitudinal magnetization at equilibrium.
[0042] In the dual-pool model, the characteristic information of breast tumors is quantified by analyzing the exchange rate between water molecules and macromolecules; the formula is expressed as:
[0043]
[0044] Among them, M x,f and M y,f are the transverse magnetization of the free pool in the x and y directions, respectively; M z,f and M z,r are the longitudinal magnetization intensities of the free pool and the confined pool, respectively; the constant k fr and k rf are the longitudinal magnetization rates from the free pool to the confined pool and from the confined pool to the free pool, respectively; Im is the imaginary part; Re is the real part.
[0045] See also Figure 2 , which is a schematic diagram of the dual-pool model of Example 1 of the present application. The dual-pool model of MT exchange without radio frequency, in which the longitudinal relaxation rates of the free pool and the restricted pool are R and R, respectively. 1f and R 1r . M z,f and M z,r are the longitudinal magnetization of the free pool and the confined pool at time t, respectively, M 0,f and M 0,r represents the longitudinal magnetization at equilibrium. The basic rate constant for saturation spin exchange between the two pools is defined as k fr and k rf , depending on the direction.
[0046] See also Figure 3 , which are the qMT images and corresponding parameter diagrams of the patient in Example 1 of the present application. From top to bottom are the qMT images and their corresponding pool size ratio PSR, the longitudinal magnetization rate krf from the restricted pool to the free pool, and the longitudinal relaxation rate R1f of the free pool.
[0047] S3: Generate a quantitative analysis report based on the quantitative data.
[0048] In this embodiment, quantitative data is extracted according to the automated software to generate a quantitative analysis report, which includes but is not limited to: qMT parameter values of breast tumor regions, comparison results of tumor tissue and normal tissue, and tumor type.
[0049] In summary, Example 1 of the present application provides more accurate data analysis through quantitative magnetization transfer (qMT) imaging technology. First, an MRI scan is performed on the patient to obtain qMT parameter maps of the region of interest and the ipsilateral and contralateral fibroglandular tissues, which include data such as the exchange rate between water molecules and macromolecules and microvascular density. By comparing the qMT parameters of tumor tissue and normal tissue, statistical analysis is performed; in the quantitative analysis, a dual-pool model is used to describe the populations of bound water and free water in the tissue, and parameter maps such as the pool size ratio, the longitudinal magnetization rate from the restricted pool to the free pool, and the longitudinal relaxation rate of the free pool are calculated to characterize the exchange rate between free water and macromolecular protons; finally, data is extracted and a quantitative analysis report is generated through automated software, including the qMT parameter values of the tumor area, the comparison results with normal tissues, and the tumor type, etc.; the present application not only avoids the risk of using contrast agents, but also provides accurate quantitative analysis reports.
[0050] Example 2
[0051] See also Figure 4 , is a schematic diagram of the structure of the magnetic resonance data analysis device of Example 2 of the present application; the specific contents include:
[0052] Acquisition module: acquiring disease information of the patient, the disease information including: region of interest, qMT parameters;
[0053] Analysis module: analyzing the region of interest and the qMT parameters to obtain quantitative data;
[0054] Report generation module: generates a quantitative analysis report based on the quantitative data.
[0055] Example 3
[0056] See also Figure 5 , is a schematic diagram of the computer device structure of Example 3 of the present application. The computer device 50 includes a processor 51 and a memory 52 coupled to the processor 51 .
[0057] The memory 52 stores program instructions for implementing the above-mentioned magnetic resonance data analysis method.
[0058] The processor 51 is used to execute program instructions stored in the memory 52 to implement magnetic resonance data analysis.
[0059] The processor 51 may also be referred to as a CPU (Central Processing Unit).
[0060] The processor 51 may be an integrated circuit chip with signal processing capabilities. The processor 51 may also 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, discrete hardware components. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.
[0061] Example 4
[0062] See also Figure 6 , which is a schematic diagram of the structure of the storage medium of Example 4 of the present application. The storage medium of the embodiment of the present application stores a program file 61 that can implement all the above methods, wherein the program file 61 can be stored in the above storage medium in the form of a software product, including a number of instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) or a processor (processor) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes, or computers, servers, mobile phones, tablets and other devices.
[0063] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other identical elements in the process, device, article or method including the element.
[0064] The above description is only a preferred embodiment of the present application, and does not limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly used in other related technical fields, are also included in the patent protection scope of the present application.
[0065] Although the embodiments of the present application have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present application, and that the scope of the present application is defined by the appended claims and their equivalents.
[0066] Of course, the present invention may have many other implementations. Based on this implementation, other implementations obtained by ordinary technicians in this field without any creative work are all within the scope of protection of the present invention.
Claims
1. A method for analyzing magnetic resonance data, characterized in that: include: Acquiring disease information of the patient, wherein the disease information includes: a region of interest and a qMT parameter; Analyzing the region of interest and the qMT parameters to obtain quantitative data; A quantitative analysis report is generated according to the quantitative data.
2. The magnetic resonance data analysis method according to claim 1, characterized in that: In the step of obtaining the disease information of the patient, the disease information including: the region of interest and the qMT parameter, the following steps are specifically included: The qMT parameters of the patient's region of interest, ipsilateral and contralateral breast fibroglandular tissues were obtained using qMT imaging technology.
3. The magnetic resonance data analysis method according to claim 1, characterized in that: The step of analyzing the region of interest and the qMT parameters to obtain quantitative data specifically includes the following steps: The breast tumor area and the ipsilateral and contralateral breast fibroglandular tissues were selected as regions of interest, and the qMT parameters of tumor tissue and normal tissue were compared and statistically analyzed. The qMT parameters were quantitatively analyzed using a two-pool model.
4. The magnetic resonance data analysis method according to claim 3, characterized in that: The step of quantitatively analyzing the qMT parameters by the dual-pool model specifically includes the following steps: The two-pool model was used to describe the populations of bound water and free water in tissues and to perform quantitative analysis of qMT parameters; Based on the two-pool model, the pool size ratio PSR and the basic rate constant k of the exchange of saturated spins between the two pools were calculated. rf and k fr and the longitudinal relaxation rate R of the free pool 1f ; The longitudinal relaxation rate R of the free pool 1f =1 / T 1f , the longitudinal relaxation rate R of the confined pool 1r =1 / T 1r ; Where T is the reciprocal of R; The pool size ratio is PSR=k fr / k rf =M 0r / M 0f , where k fr The longitudinal magnetization rate from the free pool to the confined pool, M 0r 、M 0f is the longitudinal magnetization at equilibrium.
5. The magnetic resonance data analysis method according to claim 4, characterized in that: In the dual-pool model, the characteristic information of breast tumors is quantified by analyzing the exchange rate between water molecules and macromolecules; the formula is expressed as: Among them, M x,f and M y,f are the transverse magnetization of the free pool in the x and y directions, respectively; M z,f and M z,r are the longitudinal magnetizations of the free pool and the confined pool, respectively; the constant k fr and k rf are the longitudinal magnetization rates from the free pool to the confined pool and from the confined pool to the free pool, respectively; Im is the imaginary part; Re is the real part.
6. The magnetic resonance data analysis method according to claim 1, characterized in that: The step of generating a quantitative analysis report according to the quantitative data specifically includes the following steps: Extract quantitative data based on automated software and generate quantitative analysis reports; The quantitative analysis report includes but is not limited to: qMT parameter value of breast tumor area, comparison results between tumor tissue and normal tissue, and tumor type.
7. A device for the magnetic resonance data analysis method according to claim 1, characterized in that: include: Acquisition module: acquiring disease information of the patient, the disease information including: region of interest, qMT parameters; Analysis module: analyzing the region of interest and the qMT parameters to obtain quantitative data; Report generation module: generates a quantitative analysis report based on the quantitative data.
8. A computer device, characterized in that: The computer device includes a processor and a memory coupled to the processor, wherein the memory stores program instructions for implementing the magnetic resonance data analysis method described in any one of claims 1-6; and the processor is used to execute the program instructions stored in the memory to implement magnetic resonance data analysis.
9. A storage medium, characterized in that: Program instructions executable by a processor are stored, and the program instructions are used to execute the magnetic resonance data analysis method according to any one of claims 1 to 6.