Method and device for evaluating vascular reactivity, electronic device and storage medium

Abstract

Embodiments of the present application disclose a kind of vascular reactivity evaluation method, device, electronic equipment and storage medium, wherein the method comprises: obtaining the first magnetic susceptibility weighted imaging of brain region of target object in free breathing state and the second magnetic susceptibility weighted imaging in breath-holding state;Determine the vascular distribution map of brain region;According to the first magnetic susceptibility weighted imaging and vascular distribution map, determine the first oxygen uptake fraction of target blood vessel in free breathing state;According to the second magnetic susceptibility weighted imaging and vascular distribution map, determine the second oxygen uptake fraction of target blood vessel in breath-holding state;According to the first oxygen uptake fraction and the second oxygen uptake fraction of target blood vessel, determine the evaluation index of vascular reactivity of target blood vessel, and evaluate the vascular reactivity of target blood vessel based on evaluation index.It can achieve the effect of simply, quickly and accurately evaluating vascular reactivity through oxygen uptake fraction in free breathing state and breath-holding state.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of biomedical technology, and in particular to a method, apparatus, electronic device and storage medium for evaluating vascular reactivity. Background Technology

[0002] Oxygen extraction fraction (OEF) is a parameter reflecting the brain's demand for and utilization of oxygen. Under physiological conditions, OEF is relatively uniformly distributed throughout the brain, while under pathological conditions, OEF increases or decreases to varying degrees. Current research mainly focuses on quantitatively estimating OEF across the entire brain and visualizing its distribution through imaging.

[0003] Currently, methods for estimating oxygen uptake fraction using magnetic resonance imaging (MRI) are mainly based on the inversion of information regarding the different magnetic susceptibility of hemoglobin under different oxygenation states. Compared to oxyhemoglobin, deoxyhemoglobin is a strongly paramagnetic substance, and its T2* relaxation signal is significantly shortened under a magnetic field. Although MRI-based methods for estimating oxygen uptake fraction can achieve non-invasive quantitative measurement, the MRI acquisition time is too long (2-10 minutes), and it cannot obtain information on vascular autoregulation during the body's simple oxygen supply and consumption processes. While methods using the inhalation of gases such as carbon dioxide in different proportions can simulate vascular responses under different hypoxic conditions, they are currently only used in experimental studies and have many limitations in terms of clinical applicability. Summary of the Invention

[0004] This invention provides a method, apparatus, electronic device, and storage medium for evaluating vascular reactivity, enabling the estimation of magnetic resonance oxygen uptake fraction and the determination of vascular reactivity within a short time.

[0005] In a first aspect, embodiments of the present invention provide a method for evaluating vascular reactivity, the method comprising:

[0006] Acquire a first magnetic susceptibility-weighted image of the brain region of the target object under free breathing and a second magnetic susceptibility-weighted image of the target object under breath-holding;

[0007] Determine the vascular distribution map of the brain region;

[0008] The first oxygen uptake fraction of the target blood vessel in the brain region under free breathing state is determined based on the first magnetic susceptibility-weighted imaging and the blood vessel distribution map.

[0009] The second oxygen uptake fraction of the target blood vessels in the brain region under breath-holding state was determined based on the second magnetic susceptibility-weighted imaging and vascular distribution map.

[0010] The evaluation index of vascular reactivity of the target blood vessel is determined based on the first oxygen uptake fraction and the second oxygen uptake fraction of the target blood vessel, and the vascular reactivity of the target blood vessel is evaluated based on the evaluation index.

[0011] Secondly, embodiments of the present invention also provide a device for evaluating vascular reactivity, the device comprising:

[0012] A magnetic susceptibility-weighted imaging acquisition module is used to acquire a first magnetic susceptibility-weighted image of the brain region of the target object in a free breathing state and a second magnetic susceptibility-weighted image of the target object in a breath-holding state.

[0013] A vascular distribution atlas determination module is used to determine the vascular distribution atlas of the brain region;

[0014] The first oxygen uptake fraction determination module is used to determine the first oxygen uptake fraction of the target blood vessels in the brain region under free breathing conditions based on the first magnetic susceptibility-weighted imaging and the blood vessel distribution map.

[0015] The second oxygen uptake fraction determination module is used to determine the second oxygen uptake fraction of the target blood vessels in the brain region under breath-holding state based on the second magnetic susceptibility-weighted imaging and vascular distribution map.

[0016] The vascular reactivity evaluation module is used to determine the evaluation index of the vascular reactivity of the target blood vessel based on the first oxygen uptake fraction and the second oxygen uptake fraction of the target blood vessel, and to evaluate the vascular reactivity of the target blood vessel based on the evaluation index.

[0017] Thirdly, embodiments of the present invention also provide an electronic device, the electronic device comprising:

[0018] One or more processors;

[0019] Storage device for storing one or more programs.

[0020] When the one or more programs are executed by the one or more processors, the one or more processors implement the method for evaluating vascular reactivity provided in any embodiment of the present invention.

[0021] Fourthly, embodiments of the present invention also provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for evaluating vascular reactivity provided in any embodiment of the present invention.

[0022] The technical solution of this embodiment acquires a first magnetic susceptibility-weighted image of the brain region of a target subject under free breathing conditions and a second magnetic susceptibility-weighted image of the target subject under breath-holding conditions. This enables the determination of cerebral vascular imaging under different oxygen metabolism environments. Furthermore, the acquired first and second magnetic susceptibility-weighted images can be used to further determine the corresponding first and second quantitative magnetic susceptibility maps. The vascular distribution map of the brain region is determined. Based on the first magnetic susceptibility-weighted image and the vascular distribution map, the first oxygen uptake fraction of the target blood vessels in the brain region under free breathing conditions is determined. Based on the second magnetic susceptibility-weighted image and the vascular distribution map, the second oxygen uptake fraction of the target blood vessels in the brain region under breath-holding conditions is determined. This is used to determine the parameters of oxygen demand and utilization rate of the target blood vessels in the brain region of the target subject under free breathing conditions and breath-holding conditions. Finally, based on the first and second oxygen uptake fractions of the target blood vessels, an evaluation index of the vascular reactivity of the target blood vessels is determined, and the vascular reactivity of the target blood vessels is evaluated based on the evaluation index. This method is used to determine the vascular reactivity of a target blood vessel based on the first and second oxygen uptake fractions. It solves the problem of the current lack of an effective method for evaluating vascular reactivity, achieving a simple, rapid, and accurate evaluation of vascular reactivity using oxygen uptake fractions under both free and breath-holding conditions, and is applicable to clinical applications. Attached Figure Description

[0023] To more clearly illustrate the technical solutions of exemplary embodiments of the present invention, the accompanying drawings used in describing the embodiments are briefly introduced below. Obviously, the accompanying drawings described are only a portion of the drawings of the embodiments to be described in this invention, and not all of the drawings. For those skilled in the art, other drawings can be obtained from these drawings without any creative effort.

[0024] Figure 1 This is a schematic flowchart of a method for evaluating vascular reactivity provided in Embodiment 1 of the present invention;

[0025] Figure 2 This is a schematic diagram of a method for evaluating vascular reactivity provided in Embodiment 2 of the present invention;

[0026] Figure 3 This is a schematic diagram of the experimental process of a method for evaluating vascular reactivity provided in Embodiment 2 of the present invention;

[0027] Figure 4 This is a graph showing the result of vascular reactive oxygen uptake fraction in a method for evaluating vascular reactivity provided in Embodiment 2 of the present invention;

[0028] Figure 5 This is a schematic diagram of the structure of a vascular reactivity evaluation device provided in Embodiment 3 of the present invention;

[0029] Figure 6 This is a schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention. Detailed Implementation

[0030] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the invention. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present invention and not the entire structure.

[0031] It should also be noted that, for ease of description, the accompanying drawings show only the parts relevant to the invention and not all of them. Before discussing exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe the operations (or steps) as sequential processes, many of the operations can be performed in parallel, concurrently, or simultaneously. Furthermore, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but it may also have additional steps not included in the drawings. The process may correspond to a method, function, procedure, subroutine, subprogram, etc.

[0032] Example 1

[0033] Figure 1 This is a flowchart illustrating a method for evaluating vascular reactivity provided in Embodiment 1 of the present invention. This embodiment is applicable to situations involving the determination of vascular reactivity. The method can be executed by a vascular reactivity evaluation device, which can be implemented by software and / or hardware and can be configured in a terminal and / or server to implement the vascular reactivity evaluation method in this embodiment of the present invention.

[0034] like Figure 1 As shown, the method in this embodiment may specifically include:

[0035] S110. Obtain a first magnetic susceptibility-weighted image of the brain region of the target object in a free breathing state and a second magnetic susceptibility-weighted image of the target object in a breath-holding state.

[0036] Susceptibility-weighted imaging (SWI) is a novel imaging technique that uses the differences in magnetic susceptibility among different tissues to generate image comparisons.

[0037] The target object can be understood as the object whose brain region will be imaged using magnetic resonance imaging (MRI) with magnetic susceptibility weighting. The brain region can be understood as the entire brain region of the target object.

[0038] In this embodiment of the invention, the first magnetic susceptibility-weighted imaging can be understood as magnetic susceptibility-weighted imaging of the target object under free breathing (FB) conditions, and can be represented as SWI1. The second magnetic susceptibility-weighted imaging can be understood as magnetic susceptibility-weighted imaging of the target object under breath-holding (BH) conditions, and can be represented as SWI2.

[0039] Specifically, to avoid the influence of the instrument on the classification results, all subjects in the study underwent resting-state head scans using the same type of magnetic resonance imaging (MRI) instrument and the same scanning sequence. Then, with the subjects breathing freely, the first magnetic susceptibility-weighted imaging data (SWI1) of the brain regions was acquired. With the subjects holding their breath, the second magnetic susceptibility-weighted imaging data (SWI2) of the brain regions was acquired.

[0040] Vascular reactivity can be understood as the ability of blood vessels to contract or dilate under the influence of various factors, which can effectively reflect the vascular regulatory capacity.

[0041] Optionally, brain data of the target subject acquired based on SWI1 data can be used as reference data for the magnetic susceptibility of brain regions with vascular reactivity. Optionally, brain region data of the target subject acquired based on SWI2 data can be used as magnetic susceptibility data for brain regions with vascular reactivity.

[0042] Optionally, the time difference between the acquisition time of the first magnetic susceptibility-weighted imaging and the acquisition time of the second magnetic susceptibility-weighted imaging is within a preset difference range, and the parameters of the scanning sequence used in the first magnetic susceptibility-weighted imaging and the second magnetic susceptibility-weighted imaging are the same.

[0043] Specifically, the time difference between the acquisition time of the first magnetic susceptibility-weighted imaging and the acquisition time of the second magnetic susceptibility-weighted imaging is within a preset range. In other words, the smaller the time difference between the acquisition time of the first magnetic susceptibility-weighted imaging and the acquisition time of the second magnetic susceptibility-weighted imaging, the better.

[0044] Specifically, the first magnetic susceptibility-weighted imaging acquisition time is relatively short. Considering the differences in breath-holding time of the target object, the average maximum breath-holding time of the target object is used as the setting time for the first and second magnetic susceptibility-weighted imaging. In this embodiment of the invention, to ensure the accuracy of data under free breathing conditions and to prevent it from being affected by breath-holding, magnetic susceptibility-weighted imaging under free breathing conditions can be acquired first, followed by magnetic susceptibility-weighted imaging under breath-holding conditions. The advantage of this setting is that it allows for accurate acquisition of vascular data with a short acquisition interval. Since magnetic susceptibility-weighted imaging under free breathing conditions is acquired first, the acquisition time of the first magnetic susceptibility-weighted imaging can be set first, for example, the time under free breathing conditions of the target object can be set within 30 seconds. Then, the acquisition time of the second magnetic susceptibility-weighted imaging under breath-holding conditions can be controlled to be approximately the same as the acquisition time of the first magnetic susceptibility-weighted imaging, for example, the preset difference range can be set within ±2 seconds.

[0045] The first magnetic susceptibility-weighted imaging and the second magnetic susceptibility-weighted imaging use the same scanning sequence parameters. Therefore, the impact of differences in acquisition equipment or acquisition parameters during the magnetic susceptibility-weighted imaging acquisition process can be minimized.

[0046] S120. Determine the vascular distribution map of the brain region.

[0047] A vascular atlas can be understood as a map showing the location and shape of blood vessels in brain regions. This map clearly shows the condition of the blood vessels, such as their thickness, branches, location, and connections. Various methods can be used to determine the vascular atlas of brain regions, including deep learning algorithms, multimodal fusion algorithms, image segmentation, and morphological processing.

[0048] Specifically, taking the determination of blood vessel distribution in brain regions based on deep learning algorithms as an example, we can first perform magnetic resonance angiography (MRI) on the brain region, then preprocess the grayscale values ​​of the obtained MRI angiography, determine the region of interest (ROI) according to a preset threshold, and then extract the blood vessel regions in the brain region based on the ROI. The blood vessel region is divided into multiple local images. Using the 3DUNet network in the deep learning algorithm, a fixed blood vessel region is selected for annotation, and using this region as a base point, multiple local regions are randomly selected to obtain local blood vessel segmentation results. Finally, all local regions are stitched together to obtain the overall blood vessel distribution map.

[0049] For example, image segmentation can also be used to determine the vascular distribution map. Key points of blood vessels in magnetic resonance angiography are marked to determine the geometric feature points of blood vessels in the brain region. Then, matching feature point pairs are found. The brain region image is serialized into a subtraction image based on the relationship between the matching feature point pairs. Then, a set of feature points in the serialized subtraction image is extracted. The feature points of the blood vessel edges in the subtraction image are locally repositioned. Using gray values, the feature points of the blood vessel edges are moved into the blood vessels. Then, image segmentation is performed based on region growing and adaptive thresholding to obtain the vascular distribution map of the brain region.

[0050] There are various methods for determining the vascular distribution atlas of brain regions, and no particular method is limited; the method can be determined based on actual needs.

[0051] Optionally, determining the vascular distribution map of the brain region includes: acquiring a third magnetic susceptibility-weighted image of the brain region of the target object under free breathing conditions; determining a third quantitative magnetic susceptibility map corresponding to the third magnetic susceptibility-weighted image; and determining the vascular distribution map of the brain region based on the prior knowledge template of the brain region, the third magnetic susceptibility-weighted image, and the third quantitative magnetic susceptibility map.

[0052] The acquisition time of the third magnetic susceptibility-weighted imaging is longer than that of the first magnetic susceptibility-weighted imaging.

[0053] The prior knowledge template can be understood as knowledge information that can be obtained based on existing knowledge. In this embodiment of the invention, each voxel in the brain region has a probability of having blood vessels. The prior knowledge template can represent the probability template of each voxel being a vein in magnetic susceptibility-weighted imaging.

[0054] Specifically, based on prior knowledge templates of brain regions, the probability that each voxel in the brain tissue is a blood vessel can be determined. Third-magnetic susceptibility-weighted imaging of the target subject under free breathing conditions allows for the acquisition of whole-brain venous segmentation based on the high-resolution data of this imaging. Then, processing of the third-magnetic susceptibility-weighted imaging yields a third-quantitative magnetic susceptibility map. Further, based on this map, the vascular distribution map of the target subject's brain regions can be determined, resulting in the whole-brain vascular network distribution. Therefore, by applying Gaussian mixture weighted summation to the prior knowledge templates of brain regions, third-magnetic susceptibility-weighted imaging, and the third-quantitative magnetic susceptibility map, a venous distribution map of the brain regions can be obtained. This allows for a more accurate assessment of the distribution of venous vessels in the brain regions and facilitates more complete venous segmentation.

[0055] Optionally, determining the third quantitative magnetic susceptibility map corresponding to the third magnetic susceptibility-weighted imaging includes: generating a brain mask image based on the original amplitude image of the third magnetic susceptibility-weighted imaging; determining the intracranial magnetic susceptibility-weighted imaging corresponding to the intracranial region in the brain region of the third magnetic susceptibility-weighted imaging; performing dephase processing and background field removal processing on the original phase image of the intracranial magnetic susceptibility-weighted imaging to obtain a target phase image; and calculating the magnetic susceptibility distribution of each voxel in the intracranial region based on the amplitude prior information of the brain mask image, the target phase image, and the least squares method to reconstruct the third quantitative magnetic susceptibility map.

[0056] In this invention, a mask image can be understood as an image filtering template, typically constructed using morphological methods to extract regions of interest (ROIs) within the brain of a target object. Magnetization susceptibility-weighted imaging (MSI) can be understood as acquiring data based on gradient echo sequences, followed by specialized data processing and image reconstruction to form a magnetic resonance imaging technique sensitive to the magnetic susceptibility of matter. In this embodiment, intracranial MSI can be understood as data obtained by performing MSI-weighted imaging on the brain region of a target object. The original phase image can be understood as a magnetic resonance image obtained by scanning the brain region of a target object using MSI, showing the phase data differences of different protons, which can be used to reflect the original phase information of different protons during relaxation. The phase deconvolution method can be linear or nonlinear; for example, a least squares phase deconvolution method or a weighted least squares phase deconvolution method can be used.

[0057] Specifically, in quantitative susceptibility imaging (QSEM), the acquired data includes information from both internal and external brain regions. The internal brain regions need to be retained as regions of interest (ROIs), and these ROIs are ultimately presented in the QSEM results. Therefore, non-ROIs need to be filtered out during QSEM. There are various methods for determining the ROIs of the target brain region, such as image segmentation based on grayscale histogram thresholding, region dilation morphology methods, amplitude-based image segmentation, edge-based image segmentation, wavelet transform-based image segmentation, region growing-based image segmentation, and image segmentation based on specific theories. These image segmentation methods can be used to delineate the ROIs in the image. When determining the ROIs, a brain mask image can be generated from the original amplitude image of the target subject under free breathing conditions using third-susceptibility-weighted imaging. This yields intracranial susceptibility-weighted imaging of the brain regions, filtering out non-ROIs, such as the skull, and providing brain boundary information for subsequent steps to obtain better quality image data.

[0058] Based on the constructed brain mask image, the brain magnetic susceptibility weighted imaging corresponding to the brain region can be determined. The original phase image of the brain magnetic susceptibility weighted imaging is subjected to dephase processing and background field removal processing to obtain the target phase image. Finally, the prior probability of magnetic susceptibility and the least squares method are combined to solve the quantitative magnetic susceptibility of the brain image information and reconstruct the third quantitative magnetic susceptibility map.

[0059] Similarly, when the target is breathing freely, the same operation is performed based on the third magnetic susceptibility weighted image to reconstruct the third quantitative magnetic susceptibility map; when the target is holding its breath, the same operation is performed based on the second magnetic susceptibility weighted image to reconstruct the second quantitative magnetic susceptibility map.

[0060] Optionally, the step of performing phase dephase processing on the original phase image of the brain magnetic susceptibility-weighted imaging includes: performing regional phase entanglement estimation based on the phase information of multiple voxels and the scanning time of the original phase image of the brain magnetic susceptibility-weighted imaging; and performing inverse solution of the aliasing phase based on the estimation result to obtain the true phase information of the brain magnetic susceptibility-weighted imaging.

[0061] Specifically, due to the long scanning time of MRI scans of brain regions, phase images obtained from susceptibility-weighted imaging exhibit phase aliasing. Therefore, dephase processing is required to resolve the image into temporal and spatial information. Then, by combining the phase information of multiple voxels and the scanning time, regional phase entanglement estimation is performed, and the aliased phase is solved inversely to obtain the true phase information. Optionally, during dephase processing, the process begins with regions of less phase aliasing in the susceptibility-weighted imaging phase image and gradually progresses to regions with more aliasing.

[0062] S130. Determine the first oxygen uptake fraction of the target blood vessel in the brain region under free breathing state based on the first magnetic susceptibility-weighted imaging and the blood vessel distribution map.

[0063] The target blood vessel can be understood as the venous blood vessels in the brain region of the target subject. Methods for acquiring the target blood vessel include, but are not limited to, image segmentation methods, erosion dilation algorithms, seed growth methods, region filling methods, mathematical morphology methods, watershed methods, or pattern recognition methods. The first oxygen uptake fraction can be understood as a parameter representing the oxygen demand and utilization rate of the target blood vessel in the brain region of the target subject under free breathing conditions. There are various ways to determine the oxygen uptake fraction. For example, it can be measured non-invasively using asymmetric spin echo rapid imaging technology; it can be quantitatively measured using T2 relaxation spin labeling imaging technology; or it can simulate a gas-free task vascular reactivity measurement method, measuring the ratio of oxygenated hemoglobin to deoxygenated hemoglobin in the target blood vessel through intermittent breath-holding and free breathing states, and then calculating the oxygen uptake fraction during the breath-holding and free breathing states by combining the time of the state change process.

[0064] Specifically, third-weighted magnetic susceptibility imaging of the brain region of the target subject under free breathing conditions can be acquired to determine the third quantitative magnetic susceptibility spectrum corresponding to the third-weighted imaging. For both third-weighted and first-weighted magnetic susceptibility imaging, the same type of MRI scanner and the same scanning sequence are used to scan the target subject's brain region. The number of scans is unlimited; it can be a single scan or multiple scans. To ensure the validity of the acquired data and the accuracy of the oxygen uptake fraction calculation, the acquisition time for third-weighted imaging can be longer than that for first-weighted imaging. Compared to the acquisition time of first-weighted imaging, the acquisition time for third-weighted imaging is longer; for example, the acquisition time can be set to 2-10 minutes.

[0065] Under free breathing conditions, resting brain regions of the target subjects were scanned using magnetic resonance imaging (MRI). Utilizing the differences in magnetic susceptibility between different tissues, a 3D gradient echo sequence was employed to scan the brain regions. Based on this, the MRI images underwent special data processing and image reconstruction to obtain first and third susceptibility-weighted imaging. Based on the first susceptibility-weighted imaging, vascular distribution maps, and the corresponding tissue magnetic susceptibility characteristics of different tissues, the first oxygen uptake fraction of the target blood vessels under free breathing conditions was determined.

[0066] S140. Determine the second oxygen uptake fraction of the target blood vessel in the brain region under breath-holding state based on the second magnetic susceptibility-weighted imaging and vascular distribution map.

[0067] The image acquisition parameters for the second magnetic susceptibility-weighted imaging are the same as those for the first magnetic susceptibility-weighted imaging, using the same type of MRI instrument, the same scanning sequence, and the same scanning parameters. Unlike the first magnetic susceptibility-weighted imaging, the second magnetic susceptibility-weighted imaging involves scanning the brain regions of the target subject while they are holding their breath. The second oxygen uptake fraction can be understood as a parameter representing the target subject's oxygen demand and utilization rate while holding their breath.

[0068] Specifically, by performing a resting scan of the target subject's brain region using a magnetic resonance imaging (MRI) instrument while the target subject is holding their breath, and utilizing the differences in magnetic susceptibility between different tissues, a 3D gradient echo sequence is used to scan the target subject's brain region. Based on this, special data processing and image reconstruction are performed on the MRI scan images to obtain a second magnetic susceptibility-weighted imaging. Then, based on the second magnetic susceptibility-weighted imaging and vascular distribution atlas, the second oxygen uptake fraction of the target blood vessels in the brain region under the breath-holding state is determined.

[0069] S150. Determine the evaluation index of vascular reactivity of the target blood vessel based on the first oxygen uptake fraction and the second oxygen uptake fraction of the target blood vessel, and evaluate the vascular reactivity of the target blood vessel based on the evaluation index.

[0070] Vascular reactivity can be understood as the ability of blood vessels to constrict or dilate under the influence of various vascular factors, effectively reflecting vascular regulatory capacity. Evaluation indicators of vascular reactivity can include the intake of carbon dioxide by the target blood vessel in both free breathing and breath-holding states. The oxygen uptake fraction of the target blood vessel under different states is tested, and the differences are used as evaluation indicators of vascular reactivity. The vascular reactivity of the target blood vessel is then evaluated based on these indicators.

[0071] For example, after a target subject inhales carbon dioxide during free breathing, the blood flow velocity in the target blood vessel increases significantly. During hyperventilation, the average blood flow velocity in the target blood vessel decreases significantly, and after 20-30 seconds of hyperventilation, the blood flow velocity gradually stabilizes without significant change. During breath-holding, the blood flow velocity in the target blood vessel increases significantly with increasing breath-holding time, and after more than 30 seconds of breath-holding, the blood flow velocity gradually stabilizes. Therefore, the rate of increase in blood flow velocity or the breath-holding index under these three states can be used as an indicator of vascular reactivity. Among these, using the target blood vessel response during breath-holding as an indicator of vascular reactivity in brain regions is the most convenient.

[0072] Specifically, the first oxygen uptake fraction of the target blood vessel in the brain region under free breathing conditions is determined based on first and third magnetic susceptibility-weighted imaging. The second oxygen uptake fraction of the target blood vessel in the brain region under breath-holding conditions is determined based on second and third magnetic susceptibility-weighted imaging. An evaluation index for the vascular reactivity of the target blood vessel is determined based on the first and second oxygen uptake fractions, and the vascular reactivity of the target blood vessel is evaluated based on the evaluation index.

[0073] Optionally, determining the evaluation index of vascular reactivity of the target blood vessel based on the first oxygen uptake fraction and the second oxygen uptake fraction of the target blood vessel includes: calculating the fraction difference between the first oxygen uptake fraction and the second oxygen uptake fraction for each voxel of the target blood vessel, and determining the evaluation index of vascular reactivity of the target blood vessel based on the fraction difference.

[0074] Among them, a voxel in a blood vessel can be understood as a three-dimensional unit of the human body represented by a pixel in an image, or as the smallest geometric unit that can be distinguished in magnetic resonance imaging. A voxel contains at least one blood cell.

[0075] Specifically, the first oxygen uptake fraction and the second oxygen uptake fraction can be calculated for each voxel in the target blood vessel in the magnetic resonance image. Then, the difference between the two oxygen uptake fractions for each voxel can be calculated, and the vascular reactivity evaluation index of the target blood vessel can be determined based on the difference in fractions for each voxel. For example, the difference in fractions for the first and second oxygen uptake fractions of multiple voxels in the target blood vessel can be calculated separately, and then a weighted average of the fraction differences among the multiple voxels can be taken as the evaluation index of the vascular reactivity of the target blood vessel. Alternatively, the first oxygen uptake fraction of multiple voxels in the target blood vessel can be weighted, summed, and averaged to obtain the mean first oxygen uptake fraction. The second oxygen uptake fraction of multiple voxels in the target blood vessel can be weighted, summed, and averaged to obtain the mean second oxygen uptake fraction. The difference between the mean first oxygen uptake fraction and the mean second oxygen uptake fraction can then be taken as the evaluation index of the vascular reactivity of the target blood vessel.

[0076] Optionally, the first magnetic susceptibility-weighted imaging, the second magnetic susceptibility-weighted imaging, and the third magnetic susceptibility-weighted imaging are registered.

[0077] Specifically, registration can be understood as registering the first magnetic susceptibility-weighted imaging, the second magnetic susceptibility-weighted imaging, and the third magnetic susceptibility-weighted imaging to correct pixels representing the same tissue in the three sets of data to the same position to meet the needs of data analysis. For example, it can be obtained by rotating the target angle in the magnetic susceptibility-weighted imaging.

[0078] For example, using SWI2 as a reference, standard feature statistics and linear fitting are performed on SWI1 and SWI2 to correct the two sets of data to the same position. Using SWI2 as a reference, the mutual information entropy of gray values ​​between SWI3 and SWI2 is constrained to correct the two sets of data to the same position.

[0079] The technical solution of this embodiment acquires a first magnetic susceptibility-weighted image of the brain region of a target subject under free breathing conditions and a second magnetic susceptibility-weighted image of the target subject under breath-holding conditions. The acquired first and second magnetic susceptibility-weighted images can further determine corresponding first and second quantitative magnetic susceptibility maps. A vascular distribution map of the brain region is determined. Based on the first magnetic susceptibility-weighted image and the vascular distribution map, a first oxygen uptake fraction of the target blood vessels in the brain region under free breathing conditions is determined; and based on the second magnetic susceptibility-weighted image and the vascular distribution map, a second oxygen uptake fraction of the target blood vessels in the brain region under breath-holding conditions is determined. This is used to determine the parameters of oxygen demand and utilization rate of the target blood vessels in the target subject's brain region under free breathing conditions and breath-holding conditions, respectively. Finally, an evaluation index of the vascular reactivity of the target blood vessels is determined based on the first and second oxygen uptake fractions, and the vascular reactivity of the target blood vessels is evaluated based on the evaluation index. This is used to determine the vascular reactivity capacity of the target blood vessels based on the first and second oxygen uptake fractions. This invention solves the problem of the lack of effective methods for evaluating vascular reactivity, and achieves the technical effect of simply, quickly and accurately evaluating vascular reactivity by measuring oxygen uptake fractions under free breathing and breath-holding conditions, which is applicable to clinical applications.

[0080] Example 2

[0081] Figure 2 This is a flowchart illustrating the method for evaluating vascular reactivity provided in Embodiment 2 of the present invention. Optionally, based on any optional technical solution in the embodiments of the present invention, determining the first oxygen uptake fraction of the brain region under free breathing conditions according to the first magnetic susceptibility-weighted imaging and the vascular distribution map includes: determining the first quantitative magnetic susceptibility map corresponding to the first magnetic susceptibility-weighted imaging; and for each voxel of the target blood vessel in the vascular distribution map, calculating the first oxygen uptake fraction of each voxel in the target blood vessel based on the quantitative magnetic susceptibility of each voxel in the first quantitative magnetic susceptibility map and the pre-established relationship between the quantitative magnetic susceptibility and the oxygen uptake fraction.

[0082] Specifically, the method of this embodiment may include:

[0083] S210. Obtain a first magnetic susceptibility-weighted image of the brain region of the target object in a free breathing state and a second magnetic susceptibility-weighted image of the target object in a breath-holding state.

[0084] S220. Determine the vascular distribution map of the brain region.

[0085] S230. Determine the first quantitative magnetic susceptibility spectrum corresponding to the first magnetic susceptibility weighted imaging.

[0086] Quantitative magnetic susceptibility mapping can be understood as a map reconstructed through magnetic susceptibility inversion technology. Quantitative magnetic susceptibility imaging is a technique in magnetic resonance imaging used to quantitatively measure the magnetic susceptibility characteristics of tissues, enabling effective quantitative analysis of the magnetic susceptibility caused by changes in blood oxygen saturation within tissues. The first quantitative magnetic susceptibility map can be understood as the first quantitative magnetic susceptibility map corresponding to the first magnetic susceptibility-weighted imaging of the target object under free breathing conditions, acquired through quantitative magnetic imaging technology.

[0087] Specifically, the first quantitative magnetic susceptibility is calculated in the brain region of the target subject under free breathing conditions, and the first quantitative magnetic susceptibility spectrum corresponding to the first magnetic susceptibility weighted imaging is obtained.

[0088] Optionally, the dephase processing and background field removal processing of the original phase image of the brain magnetic susceptibility-weighted imaging includes: removing the background field of the original phase image of the brain magnetic susceptibility-weighted imaging based on the feature that the orthogonal product of the unit dipole field of the brain region and the unit dipole field of any background field is less than or equal to a preset threshold.

[0089] In other words, a preset threshold can be used to determine whether the orthogonal product of the unit dipole field within the brain region and the unit dipole field of any background field is less than or equal to the preset threshold. For example, the preset threshold can be 0 or a value close to 0. The background field can be understood as being caused by the inhomogeneity of the magnetization source and the main magnetic field outside the region of interest, and the presence of the background field will affect the calculation of the magnetic susceptibility of the region of interest. Therefore, the background field component needs to be filtered out before calculating the magnetic susceptibility.

[0090] Specifically, in this embodiment of the invention, a dipole field projection method is used to remove the background field. This method utilizes the characteristic that the orthogonal product of the dipole background field in the non-interest region and the local dipole field in the interest region is close to 0 to remove the background field, thereby reducing its influence on the interest region. The determination of whether the product is close to 0 can be made by checking whether the orthogonal product of the dipole background field in the non-interest region and the local dipole field in the interest region is within a preset error range. In other words, the difference between this orthogonal product and 0 is within the preset error range.

[0091] S240. For each voxel of the target blood vessel in the blood vessel distribution map, calculate the first oxygen uptake fraction of each voxel in the target blood vessel based on the quantitative magnetic susceptibility of each voxel in the first quantitative magnetic susceptibility map and the pre-established relationship between the quantitative magnetic susceptibility and the oxygen uptake fraction.

[0092] Specifically, after determining the vascular distribution map based on the prior knowledge template of the brain region, the third magnetic susceptibility weighted imaging, and the third quantitative magnetic susceptibility map, for each voxel in the vascular distribution map, the first oxygen uptake fraction of each voxel in the target blood vessel is calculated based on the quantitative magnetic susceptibility of each voxel in the quantitative magnetic susceptibility map and the pre-established relationship between the quantitative magnetic susceptibility and the oxygen uptake fraction.

[0093] Optionally, the relationship between the quantitative magnetic susceptibility and the oxygen uptake fraction is determined based on the following formula:

[0094]

[0095] Wherein, OEF is the oxygen uptake fraction of the voxel; Δχ vein-CSF =χ vein -χ CSF , χ vein χ represents the quantitative magnetic susceptibility of venous vessels in the quantitative magnetic susceptibility spectrum. CSF Δχ represents the quantitative magnetization of cerebrospinal fluid in the anterior region of the lateral ventricle. vein-CSF Indicates the difference in magnetic susceptibility between veins and cerebrospinal fluid; Δχ deoxy The difference in magnetic susceptibility per unit hematocrit between oxygenated and deoxygenated erythrocytes; Δχ oxy-CSF =χ oxy -χ CSF , Δχ oxy-CSF The difference in magnetic susceptibility between oxygenated red blood cells and cerebrospinal fluid; χ oxy is the magnetization of oxygenated red blood cells; Hct is the hematocrit of red blood cells; pv is the correction parameter for the volume effect of the voxel acquisition portion.

[0096] It should be noted that when calculating the first oxygen uptake fraction, χ² vein The first quantitative magnetic susceptibility spectrum shows the quantitative magnetic susceptibility of venous vessels; when calculating the second oxygen uptake fraction, χ² vein The second quantitative magnetic susceptibility spectrum shows the quantitative magnetic susceptibility of venous vessels.

[0097] S250. Determine the second oxygen uptake fraction of the target blood vessel in the brain region under breath-holding state based on the second magnetic susceptibility-weighted imaging and vascular distribution map.

[0098] Similarly, the second quantitative magnetic susceptibility map corresponding to the second magnetic susceptibility weighted imaging can be determined first, and then for each voxel of the target blood vessel in the blood vessel distribution map, the second oxygen uptake fraction of each voxel in the target blood vessel can be calculated based on the quantitative magnetic susceptibility of each voxel in the second quantitative magnetic susceptibility map and the pre-established relationship between quantitative magnetic susceptibility and oxygen uptake fraction.

[0099] Specifically, the second quantitative magnetic susceptibility can be calculated in the brain region of the target subject when the subject is holding their breath, and the second quantitative magnetic susceptibility spectrum corresponding to the second magnetic susceptibility weighted imaging can be obtained.

[0100] The specific method for determining the second quantitative magnetic susceptibility spectrum corresponding to the second magnetic susceptibility-weighted imaging can be the same as the method for determining the first quantitative magnetic susceptibility spectrum. The relationship between the quantitative magnetic susceptibility and the oxygen uptake fraction can be determined based on the aforementioned formula, and will not be elaborated here.

[0101] S260. Determine the evaluation index of vascular reactivity of the target blood vessel based on the first oxygen uptake fraction and the second oxygen uptake fraction of the target blood vessel, and evaluate the vascular reactivity of the target blood vessel based on the evaluation index.

[0102] By way of example, Embodiment 2 of the present invention provides an experimental method for determining vascular reactivity. The specific experimental steps and results are as follows:

[0103] 1. Magnetic Resonance Imaging Acquisition

[0104] (1) Collect MRI data of the target subject's head. The target subject must not be carrying any metal and must not have claustrophobia;

[0105] (2) Data acquisition: A Siemens 3.0T magnetic resonance imaging system and a 32-channel phased array head coil were used to acquire three magnetic susceptibility-weighted imaging (SWI) data of two healthy target subjects. The data were: the third magnetic susceptibility-weighted imaging (SWI3) of the target subject under free breathing, the first magnetic susceptibility-weighted imaging (SWI1) of the target subject under free breathing, and the second magnetic susceptibility-weighted imaging (SWI2) of the target subject under breath-holding. The experiment was repeated once.

[0106] like Figure 3 As shown, Figure 3 This is a schematic diagram of the experimental process of an evaluation method for vascular reactivity provided in Embodiment 2 of the present invention.

[0107] The main imaging parameters for the third susceptibility-weighted imaging (SWI3) of the target subject under free breathing conditions were TR / TE1 (60 / 6.8 ms, ΔTE = 6.8 ms, 7 echoes, FA = 15°, matrix = 320 × 240, and voxel size of 0.75 mm × 0.75 mm × 2 mm), with an acquisition time of 4 min. The main imaging parameters for the first susceptibility-weighted imaging (SWI1) of the target subject under free breathing conditions were TR / TE (18 / 12 ms, FA = 15°). The main imaging parameters for the second susceptibility-weighted imaging (SWI2) of the target subject under breath-holding conditions were the same as those for the first susceptibility-weighted imaging (TR / TE) (18 / 12 ms, FA = 15°, matrix = 192 × 144, and voxel size of 1.2 mm × 1.2 mm × 5 mm). The acquisition time for both the first and second susceptibility-weighted imaging was 18 s.

[0108] Where TR represents the repetition time, i.e., the time required for the pulse sequence to be executed once; TE represents the echo time, i.e., the time required from the first radio frequency pulse to the generation of the echo signal; FA represents the flip angle; and matrix represents the size of a matrix, which in this case can represent the number of pixels in each voxel in magnetic susceptibility-weighted imaging.

[0109] 2. Data Processing

[0110] Phase maps from susceptibility-weighted imaging (SWI) data were used to reconstruct quantitative susceptibility mapping (QSM) using a Bayesian regularization algorithm. Based on prior templates and individual data, venous networks in the target subject's brain regions were extracted using SWI and QSM. The mathematical relationship between quantitative susceptibility galaxies and vascular reactivity (OEF) in the QSM map was then utilized to calculate changes in OEF.

[0111] The formula for calculating OEF is as follows:

[0112]

[0113] Wherein, OEF is the oxygen uptake fraction of the voxel; Δχ vein-CSF =χ vein -χ CSF , χ vein χ represents the quantitative magnetic susceptibility of venous vessels in the quantitative magnetic susceptibility spectrum. CSF Δχ represents the quantitative magnetization of cerebrospinal fluid in the anterior region of the lateral ventricle. vein-CSF Indicates the difference in magnetic susceptibility between veins and cerebrospinal fluid; Δχdeoxy The difference in magnetic susceptibility per unit hematocrit between oxygenated and deoxygenated erythrocytes; Δχ oxy-CSF =χ oxy -χ CSF , Δχ oxy-CSF The difference in magnetic susceptibility between oxygenated red blood cells and cerebrospinal fluid; χ oxy is the magnetization of oxygenated red blood cells; Hct is the hematocrit of red blood cells; pv is the correction parameter for the volume effect of the voxel acquisition portion.

[0114] like Figure 4 As shown, Figure 4 This is a graph showing the results of vascular reactive oxygen uptake fraction (OEF) in a method for evaluating vascular reactivity provided in Embodiment 2 of the present invention. The graph uses a paired t-test to evaluate the difference in OEF between the free breathing (FB) and breath-hold (BH) groups. The p-value between the two OEF groups was <0.05, and the average OEF of vascular reactivity during breath-holding was 8.9% higher than that of the resting OEF.

[0115] The above experiments confirmed the feasibility of measuring vascular reactive oxygen uptake fraction.

[0116] It is understood that the terms "first," "second," or "third" in the embodiments of the present invention are only used to distinguish different magnetic susceptibility-weighted imaging or oxygen uptake fractions, and are not intended to limit the order or magnitude of magnetic susceptibility-weighted imaging or oxygen uptake fractions.

[0117] The technical solution of this embodiment acquires a first magnetic susceptibility-weighted image of the brain region of a target subject under free breathing conditions and a second magnetic susceptibility-weighted image of the target subject under breath-holding conditions. This enables the determination of cerebral vascular imaging under different oxygen metabolism environments. Furthermore, the acquired first and second magnetic susceptibility-weighted images can be used to further determine the corresponding first and second quantitative magnetic susceptibility maps. The vascular distribution map of the brain region is determined. Based on the first magnetic susceptibility-weighted image and the vascular distribution map, the first oxygen uptake fraction of the target blood vessels in the brain region under free breathing conditions is determined. Based on the second magnetic susceptibility-weighted image and the vascular distribution map, the second oxygen uptake fraction of the target blood vessels in the brain region under breath-holding conditions is determined. This is used to determine the parameters of oxygen demand and utilization rate of the target blood vessels in the brain region of the target subject under free breathing conditions and breath-holding conditions. Finally, based on the first and second oxygen uptake fractions of the target blood vessels, an evaluation index of the vascular reactivity of the target blood vessels is determined, and the vascular reactivity of the target blood vessels is evaluated based on the evaluation index. This method is used to determine the vascular reactivity of a target blood vessel based on the first and second oxygen uptake fractions. It solves the problem of the current lack of an effective method for evaluating vascular reactivity, achieving a simple, rapid, and accurate evaluation of vascular reactivity using oxygen uptake fractions under both free and breath-holding conditions, and is applicable to clinical applications.

[0118] Example 3

[0119] Figure 5 This is a schematic diagram of the vascular reactivity evaluation device provided in Embodiment 3 of the present invention. The vascular reactivity evaluation device provided in this embodiment can be implemented by software and / or hardware, and can be configured in a terminal and / or server to implement the vascular reactivity evaluation method in the embodiments of the present invention. The device may specifically include: a magnetic susceptibility weighted imaging acquisition module 510, a vascular distribution map determination module 520, a first oxygen uptake fraction determination module 530, a vascular reactivity evaluation module 540, and a vascular reactivity evaluation module 550.

[0120] The magnetic susceptibility-weighted imaging acquisition module 510 is used to acquire a first magnetic susceptibility-weighted image of the brain region of the target object in a free breathing state and a second magnetic susceptibility-weighted image of the target object in a breath-holding state.

[0121] The vascular distribution map determination module 520 is used to determine the vascular distribution map of the brain region;

[0122] The first oxygen uptake fraction determination module 530 is used to determine the first oxygen uptake fraction of the target blood vessels in the brain region under free breathing state based on the first magnetic susceptibility-weighted imaging and the blood vessel distribution map.

[0123] The second oxygen uptake fraction determination module 540 is used to determine the second oxygen uptake fraction of the target blood vessels in the brain region under breath-holding state based on the second magnetic susceptibility-weighted imaging and vascular distribution map.

[0124] The vascular reactivity evaluation module 550 is used to determine the evaluation index of the vascular reactivity of the target blood vessel based on the first oxygen uptake fraction and the second oxygen uptake fraction of the target blood vessel, and to evaluate the vascular reactivity of the target blood vessel based on the evaluation index.

[0125] The technical solution of this embodiment acquires a first magnetic susceptibility-weighted image of the brain region of a target subject under free breathing conditions and a second magnetic susceptibility-weighted image of the target subject under breath-holding conditions. This enables the determination of cerebral vascular imaging under different oxygen metabolism environments. Furthermore, the acquired first and second magnetic susceptibility-weighted images can be used to further determine the corresponding first and second quantitative magnetic susceptibility maps. The vascular distribution map of the brain region is determined. Based on the first magnetic susceptibility-weighted image and the vascular distribution map, the first oxygen uptake fraction of the target blood vessels in the brain region under free breathing conditions is determined. Based on the second magnetic susceptibility-weighted image and the vascular distribution map, the second oxygen uptake fraction of the target blood vessels in the brain region under breath-holding conditions is determined. This is used to determine the parameters of oxygen demand and utilization rate of the target blood vessels in the brain region of the target subject under free breathing conditions and breath-holding conditions. Finally, based on the first and second oxygen uptake fractions of the target blood vessels, an evaluation index of the vascular reactivity of the target blood vessels is determined, and the vascular reactivity of the target blood vessels is evaluated based on the evaluation index. This method is used to determine the vascular reactivity of a target blood vessel based on the first and second oxygen uptake fractions. It solves the problem of the current lack of an effective method for evaluating vascular reactivity, achieving a simple, rapid, and accurate evaluation of vascular reactivity using oxygen uptake fractions under both free and breath-holding conditions, and is applicable to clinical applications.

[0126] Based on any optional technical solution in the embodiments of the present invention, the vascular distribution map determination module may optionally include:

[0127] The third magnetic susceptibility-weighted imaging acquisition submodule is used to acquire the third magnetic susceptibility-weighted imaging of the brain region of the target object in a free breathing state, wherein the acquisition time of the third magnetic susceptibility-weighted imaging is longer than the acquisition time of the first magnetic susceptibility-weighted imaging.

[0128] The third quantitative magnetic susceptibility map determination submodule is used to determine the third quantitative magnetic susceptibility map corresponding to the third magnetic susceptibility weighted imaging.

[0129] The vascular distribution map determination submodule is used to determine the vascular distribution map of the brain region based on the prior knowledge template of the brain region, the third magnetic susceptibility-weighted imaging, and the third quantitative magnetic susceptibility map.

[0130] Based on any optional technical solution in the embodiments of the present invention, the first oxygen uptake fraction determination module may optionally include: a quantitative magnetic susceptibility map determination submodule, a vascular distribution map determination submodule, and an oxygen uptake fraction calculation submodule.

[0131] The first quantitative magnetic susceptibility map determination submodule is used to determine the first quantitative magnetic susceptibility map corresponding to the first magnetic susceptibility weighted imaging.

[0132] The oxygen uptake fraction calculation submodule is used to calculate the first oxygen uptake fraction of each voxel in the target blood vessel for each voxel in the target blood vessel distribution map, based on the quantitative magnetic susceptibility of each voxel in the second quantitative magnetic susceptibility map and the pre-established relationship between the quantitative magnetic susceptibility and the oxygen uptake fraction.

[0133] Based on any optional technical solution in the embodiments of the present invention, the third quantitative magnetic susceptibility spectrum determination submodule may specifically include: a mask image generation unit, a magnetic susceptibility weighted imaging determination unit, a target phase image acquisition unit, and a quantitative magnetic susceptibility spectrum reconstruction unit.

[0134] The mask image generation unit is used to generate a brain mask image based on the original amplitude image of the third magnetic susceptibility-weighted imaging.

[0135] A magnetic susceptibility-weighted imaging determination unit is used to determine the intracranial magnetic susceptibility-weighted imaging corresponding to the intracranial region in the brain region of the third magnetic susceptibility-weighted imaging.

[0136] The target phase image acquisition unit is used to perform dephase processing and background field removal processing on the original phase image of the brain magnetic susceptibility-weighted imaging to obtain the target phase image;

[0137] The quantitative magnetic susceptibility map reconstruction unit is used to calculate the magnetic susceptibility distribution of each voxel in the brain region based on the amplitude prior information of the brain mask image, the target phase image, and the least squares method, and reconstruct the first quantitative magnetic susceptibility map.

[0138] Based on any optional technical solution in the embodiments of the present invention, the quantitative magnetic susceptibility map reconstruction unit is optionally used to perform regional phase entanglement estimation based on the phase information of multiple voxels of the original phase image of the brain magnetic susceptibility weighted imaging and the scanning time, and to perform inverse solution of the aliased phase based on the estimation result to obtain the true phase information of the brain magnetic susceptibility weighted imaging.

[0139] Based on any optional technical solution in the embodiments of the present invention, the quantitative magnetic susceptibility map reconstruction unit is optionally used to remove the background field of the original phase image of the brain magnetic susceptibility weighted imaging based on the feature that the orthogonal product of the unit dipole field of the brain region and the unit dipole field of any background field is less than a preset threshold.

[0140] Based on any optional technical solution in the embodiments of the present invention, the relationship between the quantitative magnetic susceptibility and the oxygen uptake fraction is optionally determined based on the following formula:

[0141]

[0142] Wherein, OEF is the oxygen uptake fraction of the voxel; Δχ vein-CSF =χ vein -χ CSF , χ vein χ represents the quantitative magnetic susceptibility of venous vessels in the quantitative magnetic susceptibility spectrum. CSF Δχ represents the quantitative magnetization of cerebrospinal fluid in the anterior region of the lateral ventricle. vein-CSF Indicates the difference in magnetic susceptibility between veins and cerebrospinal fluid; Δχ deoxy The difference in magnetic susceptibility per unit hematocrit between oxygenated and deoxygenated erythrocytes; Δχ oxy-CSF =χ oxy -χ CSF , Δχ oxy-CSF The difference in magnetic susceptibility between oxygenated red blood cells and cerebrospinal fluid; χ oxy is the magnetization of oxygenated red blood cells; Hct is the hematocrit of red blood cells; pv is the correction parameter for the volume effect of the voxel acquisition portion.

[0143] Based on any optional technical solution in the embodiments of the present invention, optionally, the vascular reactivity evaluation module is used for:

[0144] For each voxel of the target blood vessel, the difference between the first oxygen uptake fraction and the second oxygen uptake fraction is calculated, and an evaluation index of the vascular reactivity of the target blood vessel is determined based on the difference in fractions.

[0145] Based on any optional technical solution in the embodiments of the present invention, optionally, the acquisition time of the third magnetic susceptibility-weighted imaging is greater than the acquisition time of the first magnetic susceptibility-weighted imaging, the time difference between the acquisition time of the first magnetic susceptibility-weighted imaging and the acquisition time of the second magnetic susceptibility-weighted imaging is within a preset difference range, and the parameters of the scanning sequence used by the first magnetic susceptibility-weighted imaging and the second magnetic susceptibility-weighted imaging are the same.

[0146] The above-mentioned vascular reactivity evaluation device can execute the vascular reactivity evaluation method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the vascular reactivity evaluation method.

[0147] Example 4

[0148] Figure 6 This is a schematic diagram of the structure of an electronic device provided in Embodiment 4 of the present invention. Figure 6 A block diagram is shown of an exemplary electronic device 12 suitable for implementing embodiments of the present invention. Figure 6 The electronic device 12 shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of the present invention.

[0149] like Figure 6 As shown, the electronic device 12 is represented in the form of a general-purpose computing device. The components of the electronic device 12 may include, but are not limited to: one or more processors or processing units 16, system memory 28, and bus 18 connecting different system components (including system memory 28 and processing unit 16).

[0150] Bus 18 represents one or more of several bus architectures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus using any of the various bus architectures. For example, these architectures include, but are not limited to, the Industry Standard Architecture (ISA) bus, the Micro Channel Architecture (MAC) bus, the Enhanced ISA bus, the Video Electronics Standards Association (VESA) local bus, and the Peripheral Component Interconnect (PCI) bus.

[0151] Electronic device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by electronic device 12, including volatile and non-volatile media, removable and non-removable media.

[0152] System memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. Electronic device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, storage system 34 may be used to read and write non-removable, non-volatile magnetic media (… Figure 6 Not shown; usually referred to as a "hard drive"). Although Figure 6 Not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk") and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 via one or more data media interfaces. System memory 28 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the embodiments of the present invention.

[0153] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in system memory 28. Such program modules 42 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. Program modules 42 typically perform the functions and / or methods described in the embodiments of the present invention.

[0154] Electronic device 12 can also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), and with one or more devices that enable a user to interact with the electronic device 12, and / or with any device that enables the electronic device 12 to communicate with one or more other computing devices (e.g., network card, modem, etc.). This communication can be performed through input / output (I / O) interface 22. Furthermore, electronic device 12 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 20. Figure 6 As shown, network adapter 20 communicates with other modules of electronic device 12 via bus 18. It should be understood that, although... Figure 6 As not shown, other hardware and / or software modules may be used in conjunction with electronic device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0155] The processing unit 16 executes various functional applications and data processing by running programs stored in the system memory 28, such as implementing a method for evaluating vascular reactivity provided in this embodiment.

[0156] Example 5

[0157] Embodiment 5 of the present invention also provides a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to perform a method for evaluating vascular reactivity. The method includes: acquiring a first magnetic susceptibility-weighted image of a brain region of a target subject under free breathing conditions and a second magnetic susceptibility-weighted image of the target subject under breath-holding conditions; determining a vascular distribution map of the brain region; determining a first oxygen uptake fraction of a target blood vessel in the brain region under free breathing conditions based on the first magnetic susceptibility-weighted image and the vascular distribution map; determining a second oxygen uptake fraction of the target blood vessel in the brain region under breath-holding conditions based on the second magnetic susceptibility-weighted image and the vascular distribution map; determining an evaluation index of the vascular reactivity of the target blood vessel based on the first oxygen uptake fraction and the second oxygen uptake fraction of the target blood vessel; and evaluating the vascular reactivity of the target blood vessel based on the evaluation index.

[0158] The computer storage medium of this invention can be any combination of one or more computer-readable media. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. A 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 any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, 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.

[0159] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of sending, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0160] Program code contained on a computer-readable medium may be transmitted using any suitable medium, including—but not limited to—wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0161] Computer program code for performing the operations of embodiments of the present invention can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0162] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A method for evaluating vascular reactivity, characterized by, The method comprises the following steps: obtaining first magnetic susceptibility weighted imaging of a brain region of a target object in a free breathing state and second magnetic susceptibility weighted imaging of the target object in a breath-holding state; determining a blood vessel distribution map of the brain region; determining a first oxygen uptake fraction of a target blood vessel of the brain region in the free breathing state according to the first magnetic susceptibility weighted imaging and the blood vessel distribution map; determining a second oxygen uptake fraction of the target blood vessel of the brain region in the breath-holding state according to the second magnetic susceptibility weighted imaging and the blood vessel distribution map; calculating a fractional difference value of the first oxygen uptake fraction and the second oxygen uptake fraction for each voxel of the target blood vessel, determining an evaluation index of blood vessel reactivity of the target blood vessel according to the fractional difference value, and evaluating the blood vessel reactivity of the target blood vessel based on the evaluation index. The method further comprises the following steps:

2. The method of claim 1, wherein, determining a first quantitative magnetic susceptibility map corresponding to the first magnetic susceptibility weighted imaging; and calculating the first oxygen uptake fraction of each voxel in the target blood vessel according to the quantitative magnetic susceptibility of each voxel in the first quantitative magnetic susceptibility map and a pre-established relationship between the quantitative magnetic susceptibility and the oxygen uptake fraction. The method further comprises the following steps: obtaining third magnetic susceptibility weighted imaging of the brain region of the target object in the free breathing state, wherein the acquisition time of the third magnetic susceptibility weighted imaging is greater than that of the first magnetic susceptibility weighted imaging; determining a third quantitative magnetic susceptibility map corresponding to the third magnetic susceptibility weighted imaging; and 3. The method of claim 2, wherein, determining the blood vessel distribution map of the brain region according to a prior knowledge template of the brain region, the third magnetic susceptibility weighted imaging and the third quantitative magnetic susceptibility map. The method further comprises the following steps: generating a brain mask image based on a raw amplitude image of the third magnetic susceptibility weighted imaging; determining intracerebral magnetic susceptibility weighted imaging corresponding to an intracerebral region in the brain region of the third magnetic susceptibility weighted imaging; performing dephasing processing and background field removal processing on a raw phase image of the intracerebral magnetic susceptibility weighted imaging to obtain a target phase image; 4. The method of claim 3, wherein, calculating the magnetic susceptibility distribution of each voxel in the intracerebral region according to amplitude prior information of the brain mask image, the target phase image and a least square method, and reconstructing the third quantitative magnetic susceptibility map. The method further comprises the following steps:

5. The method of claim 4, wherein, performing regional phase wrapping estimation according to phase information and scanning time of a plurality of voxels of the raw phase image of the intracerebral magnetic susceptibility weighted imaging, and inversely solving the aliasing phase based on the estimation result to obtain real phase information of the intracerebral magnetic susceptibility weighted imaging. The method further comprises the following steps: performing dephasing processing and background field removal processing on a raw phase image of the intracerebral magnetic susceptibility weighted imaging to obtain a target phase image; The background field of the original phase image of the brain susceptibility weighted imaging is removed based on a feature that an inner brain region unit dipole field of the brain region and an arbitrary background field unit dipole field are orthogonal and the product is less than a preset threshold.

6. The method of claim 2, wherein, The relationship between the quantitative susceptibility and the oxygen extraction fraction is determined based on the following formula: ， wherein, is the oxygen extraction fraction of the voxel; , is the quantitative susceptibility of venous vessels in the quantitative susceptibility map, is the quantitative susceptibility of cerebrospinal fluid in the anterior lateral ventricle region; represents the difference in susceptibility between venous vessels and cerebrospinal fluid; is the difference in susceptibility between unit oxygenated and deoxygenated red blood cells; , is the difference in susceptibility between oxygenated red blood cells and cerebrospinal fluid; is the susceptibility of oxygenated red blood cells; is the red blood cell hematocrit; is a correction parameter for partial volume effects of the acquisition voxel.

7. The method of claim 1, wherein, A time difference between a collection time of the first susceptibility weighted imaging and a collection time of the second susceptibility weighted imaging is within a preset difference range, and parameters of a scanning sequence used by the first susceptibility weighted imaging and the second susceptibility weighted imaging are the same.

8. A device for evaluating vascular reactivity, characterized in that, The method comprises the following steps: A susceptibility weighted imaging acquisition module is configured to acquire first susceptibility weighted imaging of a brain region of a target object in a free breathing state and second susceptibility weighted imaging of the target object in a breath-hold state; A blood vessel distribution map determination module is configured to determine a blood vessel distribution map of the brain region; A first oxygen extraction fraction determination module is configured to determine a first oxygen extraction fraction of a target blood vessel of the brain region in the free breathing state according to the first susceptibility weighted imaging and the blood vessel distribution map; A second oxygen extraction fraction determination module is configured to determine a second oxygen extraction fraction of the target blood vessel of the brain region in the breath-hold state according to the second susceptibility weighted imaging and the blood vessel distribution map; A blood vessel reactivity evaluation module is configured to calculate a fraction difference value of the first oxygen extraction fraction and the second oxygen extraction fraction for each voxel of the target blood vessel, determine an evaluation index of blood vessel reactivity of the target blood vessel according to the fraction difference value, and evaluate the blood vessel reactivity of the target blood vessel based on the evaluation index. A first quantitative susceptibility map determination sub-module is configured to determine a first quantitative susceptibility map corresponding to the first susceptibility weighted imaging, and an oxygen extraction fraction calculation sub-module is configured to calculate a first oxygen extraction fraction of each voxel in the target blood vessel according to a quantitative susceptibility of each voxel in the first quantitative susceptibility map and a previously established relationship between the quantitative susceptibility and the oxygen extraction fraction for each voxel of the target blood vessel in the blood vessel distribution map.

Images