CN117911360A - Quantitative index extraction method and related device for cortical myelin based on T1w/T2w map - Google Patents
Quantitative index extraction method and related device for cortical myelin based on T1w/T2w map Download PDFInfo
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Abstract
The invention discloses a quantitative index extraction method and a relevant device for cortical myelin based on a T1w/T2w map, belonging to the technical field of medical imaging; preprocessing the T1w image and the T2w image; calculating a T1w/T2w map of the gray matter region through the preprocessed T1w image and the preprocessed T2w image; and finally covering the gray matter partition template on a T1w/T2w map of the gray matter region, and extracting myelin quantification indexes under each partition in the gray matter partition template. The invention normalizes the MRI data processing flow based on the T1w/T2w map; developing a quantitative index extraction method of myelin in gray matter region based on ROI; the invention lays a technical foundation for the accurate and rapid diagnosis of myelin lesions and related diseases in the follow-up clinical quantification by the universality of the software environment of the invention and the operation thereof.
Description
Technical Field
The invention belongs to the technical field of medical imaging, and relates to a quantitative index extraction method and a related device for cortical myelin based on a T1w/T2w map.
Background
Non-invasively mapping the layout of human cortical areas is a continuing challenge of neuroscience. Myelin is a lipid-rich tissue that encapsulates neuronal axons. It is an important component of the human brain due to its role in accelerating nerve signaling and promoting synchronization. Myelin thickness is proportional to the diameter of axons, which change during development and aging. Myelin abnormalities are central to a variety of developmental and neurodegenerative diseases, and myelin reduction by demyelination during normal aging is also thought to underlie decreased cognitive ability by interfering with the synchronicity of neuronal circuits and reducing processing rates, a process particularly important for modulating neural plasticity by participating in cortical inhibitory neuronal activity. While most research in human brain myelin has focused on white matter, the importance of gray matter myelin throughout the development and aging process is increasingly recognized.
There are studies indicating new methods of cortical mapping based on myelin content shown by T1 weighted (T1 w) and T2 weighted (T2 w) MRI. The correlation between the content of cortical myelin and the T1w image is strong through histological evaluation, and the T2w image also proves to be in negative correlation with the content of cortical myelin, because the contrast of myelin is enhanced, and the contrast of myelin can be enhanced by utilizing the ratio of the intensity of the T1w/T2w image to eliminate the related image intensity deviation in the magnetic resonance imaging process. Currently, T1w/T2w quantitative analysis techniques may be an effective tool to support non-invasive localization of the brain medullary sheath. Therefore, the technology may find important application in research of brain development, aging and diseases.
Although it has been proposed in recent years to include: MRI imaging sequences with stronger biological interpretability, such as magnetization transfer (magnetization transfer, MT) imaging, myelin water fraction (MYELIN WATER fraction, MWT) imaging, and the like, but the sequences are more concentrated in white matter areas for myelin imaging, the application in cortical areas is less, the comprehensive popularity in clinical diagnosis in China is lower, and the technology is still in a scientific research driving stage. Whereas, since T1w and T2w images are typically part of a conventional brain MRI examination, high resolution images can be obtained in a relatively short time, and mapping of the myelin content within the skin using T1w/T2w technology in humans has recently been applied to clinical studies of a variety of central nervous system diseases.
In the clinical imaging diagnosis of the stage, imaging diagnosis of myelin lesions is usually performed using MRI sequences such as T1w, T2w, and FLAIR (fluid attenuation inversion recovery, fluid attenuated inversion recovery) or by combining CT; the imaging diagnosis depending on multiple imaging sequences or modes is often carried out by an expert on naked eyes for observing the image data, the method has strong horizontal dependence on the observed expert, the obtained result has strong subjectivity, long consumption time and lower efficiency, and the qualitative conclusion is obtained, so that the difference cannot be quantitatively embodied.
The existing technology based on myelin quantitative index analysis comprises the following steps: quantitative analysis technology of myelin based on cortex surface and quantitative analysis of myelin based on voxels. In quantitative analysis of myelin based on cortical surfaces, data from each subject needs to be mapped to the cortical surface and aligned between individuals using surface-based registration. The group mean myelin map provides an observable spatial gradient of sharp transitions in independently measured myelin content at the surface, i.e., the presumed cortical region boundaries, ultimately forming a myelin map in the units of cortical vertices. In quantitative analysis of myelin based on voxels, clustering is performed by voxel level calculation, and finally, a region with significant difference in image signals is obtained. The method needs limiting parameters such as the minimum clustering block mass, and the like, and the setting of the parameters is relatively high in subjectivity and is easy to filter lesions in a micro-area.
Both the above two techniques need to perform spatial transformation or clustering calculation at voxel level, and have the disadvantages of complex data processing flow, large calculated amount, long time consumption, high operation difficulty and inconvenient registration of software running environment, so that most of the techniques are used in scientific research driving tasks and have limited application in clinical imaging diagnosis.
Disclosure of Invention
The invention aims to solve the technical problems of complex data processing flow, large calculated amount, long time consumption and high operation difficulty of myelin quantitative index analysis in the prior art, and provides a method and a related device for extracting cortical myelin quantitative indexes based on a T1w/T2w map.
In order to achieve the purpose, the invention is realized by adopting the following technical scheme:
in a first aspect, the invention provides a quantitative index extraction method for cortical myelin based on a T1w/T2w map, which comprises the following steps:
Preprocessing the T1w image and the T2w image;
Calculating a T1w/T2w map of the gray matter region through the preprocessed T1w image and the preprocessed T2w image;
Covering the gray matter partition template onto the T1w/T2w map of the gray matter region, and extracting myelin quantification indexes under each partition in the gray matter partition template.
In a second aspect, the invention provides a quantitative index extraction system for cortical myelin based on a T1w/T2w map, comprising:
The preprocessing module is used for preprocessing the T1w image and the T2w image;
the image calculation module is used for calculating a T1w/T2w map of the gray matter region through the preprocessed T1w image and the preprocessed T2w image;
the index extraction module is used for covering the gray matter partition template on the T1w/T2w map of the gray matter region and extracting myelin quantification indexes under each partition in the gray matter partition template.
In a third aspect, the present invention provides a computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the processor implementing the steps of the method as described above when executing the computer program.
In a fourth aspect, the present invention provides a computer readable storage medium storing a computer program which when executed by a processor performs the steps of a method as described above.
Compared with the prior art, the invention has the following beneficial effects:
The invention discloses a quantitative index extraction method and a related device for cortical myelin based on a T1w/T2w map; based on the high correlation of the T1w/T2w map to the myelin content representation, a cortical myelin quantification index extraction method based on a region of interest (Region of interest, ROI) is provided, which normalizes the MRI data processing flow based on the T1w/T2w map, and normalizes and removes signal noise and space factors which possibly influence the subsequent quantification analysis in the high-resolution T1w and T2 w; the quantitative index of myelin in each refined cortical region is extracted based on the extraction of the ROI features of the cortical region, the cortical region with abnormal myelin can be directly positioned, the abnormal degree of the myelin index can be quantitatively represented, and different gray matter partition templates can be flexibly replaced according to clinical requirements; the invention has higher calculation efficiency, and the running software is environment-friendly and is easy to popularize in clinical imaging diagnosis.
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For a clearer description of the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments will be briefly described below, it being understood that the following drawings only illustrate some embodiments of the present invention and should not be considered as limiting the scope, and other related drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a schematic diagram of the system of the present invention;
FIG. 3 is a schematic diagram of a method according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a computer device according to the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. The components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the invention, as presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures.
In the description of the embodiments of the present invention, it should be noted that, if the terms "upper," "lower," "horizontal," "inner," and the like indicate an azimuth or a positional relationship based on the azimuth or the positional relationship shown in the drawings, or the azimuth or the positional relationship in which the inventive product is conventionally put in use, it is merely for convenience of describing the present invention and simplifying the description, and does not indicate or imply that the apparatus or element to be referred to must have a specific azimuth, be configured and operated in a specific azimuth, and thus should not be construed as limiting the present invention. Furthermore, the terms "first," "second," and the like, are used merely to distinguish between descriptions and should not be construed as indicating or implying relative importance.
Furthermore, the term "horizontal" if present does not mean that the component is required to be absolutely horizontal, but may be slightly inclined. As "horizontal" merely means that its direction is more horizontal than "vertical", and does not mean that the structure must be perfectly horizontal, but may be slightly inclined.
In the description of the embodiments of the present invention, it should also be noted that, unless explicitly specified and limited otherwise, the terms "disposed," "mounted," "connected," and "connected" should be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention can be understood by those of ordinary skill in the art according to the specific circumstances.
The invention is described in further detail below with reference to the attached drawing figures:
Referring to fig. 1 and 3, the embodiment of the invention discloses a method for extracting quantitative indexes of cortical myelin based on a T1w/T2w map, which comprises the following steps:
S1, preprocessing a T1w image and a T2w image;
s2, calculating a T1w/T2w map of the gray matter region through the preprocessed T1w image and the preprocessed T2w image;
s3, covering the gray matter partition template on a T1w/T2w map of the gray matter region, and extracting myelin quantification indexes under each partition in the gray matter partition template.
The MRI data processing flow based on the T1w/T2w map is standardized, and signal noise and space factors which possibly influence subsequent quantitative analysis in the high-resolution T1w and T2w are removed; extracting quantitative indexes of myelin from each refined cortical region based on the ROI features of the cortical region, and directly positioning the cortical region with abnormal myelin, wherein the quantitative indexes represent the abnormal degree of the myelin indexes; the invention lays a technical foundation for the accurate and rapid diagnosis of myelin lesions and related diseases in the follow-up clinical quantification by the universality of the software environment of the invention.
In a possible embodiment of the present invention, before preprocessing the T1w image and the T2w image, the T1w image and the T2w image need to be input, the original DICOM (DIGITAL IMAGING AND Communications IN MEDICINE) format data needs to be converted into Nifit format, so as to facilitate subsequent image processing and calculation, and an gray matter partition template needs to be input, so as to complete subsequent extraction of quantitative indexes of cortical myelin based on ROI.
The preprocessing of the T1w image and the T2w image specifically comprises the following steps:
S101, carrying out origin correction on a T1w image and a T2w image, wherein the origin correction comprises the steps of adjusting left and right brains of a sagittal plane coronal plane to be symmetrical, and adjusting AC-PC connection in the images; stereotactic brain mapping was based on the lines of previous association-postassociation (anterior commissure, AC, posterior commissure PC, AC-PC), as studies have shown that AC-PC of different human brains have no significant differences. Therefore, to reduce the impact of patient head motion during nuclear magnetic scan on subsequent image processing, manual origin correction of the T1w, T2w images is required.
S102, registering the corrected T2w image to the corrected individual T1w image; t1w is often used as a high-resolution structure standard image in MRI image processing, and other sequence images need to be registered under an individual anatomical space formed by T1 w; before the calculation of the T1w/T2w map, the T2w image needs to be unified under the anatomical space of the T1w image, so that the accuracy of the subsequent image calculation is ensured.
S103, offset field correction is carried out on the registered T1w image and the registered T2w image; the deviation regularization parameter in the bias field correction is set to be 0.0001, and the full width half maximum parameter is set to be 60mm; factors such as patient position in the scanner, the scanner itself, and many unknown problems can cause intensity differences across the image, i.e., the intensity values can vary within the same tissue. This is called the bias field. This is a poor signal noise with low frequency smoothing that can affect subsequent quantitative analysis. A pre-processing step is therefore required to correct for the effects of the bias field before subsequent image calculations can be performed.
S104, performing intensity normalization on the T1w image and the T2w image after offset field correction.
In a possible embodiment of the present invention, the intensity normalization of the T1w image and the T2w image after the bias field correction includes: according to the head MRI scanned image, using the intensity values of the external voxels of the brain tissues of the eyeball and the temporo cheek as a reference, carrying out intensity normalization on the T1w image and the T2w image, wherein the specific formula is as follows:
wherein, X S represents the intensity distribution peak value of the input image in the corresponding region of the ICBM152 eyeball binarization mask; y S represents the intensity distribution peak of the input image in the region corresponding to the ICBM152 temporal cheek binarization mask; x R represents the distribution peak of eyeball mask intensity in the ICBM152 template; y R represents the peak distribution of temporal cheek mask intensities in the ICBM152 template; i represents the voxel value before intensity normalization; i c represents the intensity normalized voxel value.
In a possible embodiment of the present invention, the T1w/T2w map of the gray matter region is calculated by using the preprocessed T1w image and the preprocessed T2w image, and specifically includes:
S201, dividing the normalized T1w image and the normalized T2w image to obtain a T1w/T2w map in the individual space; the intensity values of the pixels in the map reflect the level of myelin content in the region where the pixels are located.
S202, obtaining an individual tissue probability map by means of T1w image segmentation calculation; the tissue probability map of the individual comprises a gray matter probability map, a white matter probability map and a cerebrospinal fluid probability map; the voxel values of the probability map here refer to: the probability that a voxel corresponding to a location voxel belongs to a corresponding tissue element in the individual spatial map. The data for each subject is divided into a number of different tissue types. Tissue types are defined in terms of tissue probability maps, which define the prior probability of finding a tissue type at a particular location.
S203, selecting a probability threshold for the gray probability map, and binarizing the gray probability map to obtain a gray binarization mask.
In a possible embodiment of the present invention, the process of calculating the gray matter binarization mask in S203 specifically includes:
BGM(x,y,z)＝PGM(x,y,z)≥threshold
Wherein x, y and z are three coordinate directions respectively; b GM is a gray matter binary mask; p GM is a tissue probability map; threshold is a probability threshold that is expressed as the probability that the pixel location belongs to gray matter.
In a possible embodiment of the present invention, the probability threshold in S203 is selected to be 0.5-0.8.
In one possible embodiment of the present invention, the method of covering the gray matter partition template onto the T1w/T2w map of the gray matter region, and extracting myelin quantification indexes under each partition in the gray matter partition template specifically includes:
S301, performing product operation on the T1w/T2w map in S201 and the gray matter binarization mask in S203 to obtain a gray matter region T1w/T2w map in the individual space; to remove the effect of areas other than ash on subsequent analysis.
S302, normalizing gray matter partition templates to individual anatomical spaces under T1w images of each patient by adopting an interpolation method; the interpolation method adopts the nearest neighbor interpolation method to ensure the physiological significance of the voxel value representing the anatomical position in the template after standardization.
S303, covering the gray area T1w/T2w map of the standardized gray area in S302 to extract myelin quantification indexes based on gray ROI levels, and calculating the pixel intensity mean value of each ROI in the tissue template in the gray area T1w/T2w map to obtain the T1w/T2w intensity mean value of each gray area template ROI under the individual T1w/T2w gray map; the specific calculation process is as follows:
Wherein i represents the partition number in the gray matter partition template; myelin i represents the calculated myelin quantification index in the corresponding partition; r i represents the voxel intensity value of the gray matter region T1w/T2w map obtained in S301 in the corresponding partition; n i represents the total number of voxels contained in the corresponding partition; x, y, z represent three coordinate directions, respectively.
Referring to fig. 2, the embodiment of the invention discloses a quantitative index extraction system for cortical myelin based on a T1w/T2w map, comprising:
The preprocessing module is used for preprocessing the T1w image and the T2w image;
the image calculation module is used for calculating a T1w/T2w map of the gray matter region through the preprocessed T1w image and the preprocessed T2w image;
the index extraction module is used for covering the gray matter partition template on the T1w/T2w map of the gray matter region and extracting myelin quantification indexes under each partition in the gray matter partition template.
Referring to fig. 4, an embodiment of the present invention discloses a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the method for extracting quantitative index of cortical myelin based on T1w/T2w map as described above when executing the computer program.
The embodiment of the invention discloses a computer readable storage medium, which stores a computer program, wherein the computer program realizes the steps of the quantitative index extraction method of cortical myelin based on a T1w/T2w map when being executed by a processor.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical aspects of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the above embodiments, it should be understood by those of ordinary skill in the art that: modifications and equivalents may be made to the specific embodiments of the invention without departing from the spirit and scope of the invention, which is intended to be covered by the claims.
Claims (10)
1. A quantitative index extraction method for cortical myelin based on a T1w/T2w map is characterized by comprising the following steps:
Preprocessing the T1w image and the T2w image;
Calculating a T1w/T2w map of the gray matter region through the preprocessed T1w image and the preprocessed T2w image;
Covering the gray matter partition template onto the T1w/T2w map of the gray matter region, and extracting myelin quantification indexes under each partition in the gray matter partition template.
2. The method for extracting quantitative index of cortical myelin based on T1w/T2w map according to claim 1, wherein the preprocessing of T1w image and T2w image specifically comprises:
s101, carrying out origin correction on a T1w image and a T2w image, wherein the origin correction comprises the steps of adjusting left and right brains of a sagittal plane coronal plane to be symmetrical, and adjusting AC-PC connection in the images;
S102, registering the corrected T2w image to the corrected individual T1w image;
S103, offset field correction is carried out on the registered T1w image and the registered T2w image; the deviation regularization parameter in the bias field correction is set to be 0.0001, and the full width half maximum parameter is set to be 60mm;
s104, performing intensity normalization on the T1w image and the T2w image after offset field correction.
3. The method for extracting quantitative index of cortical myelin based on T1w/T2w map according to claim 2, wherein the intensity normalizing of the T1w image and the T2w image after bias field correction comprises: according to the head MRI scanned image, using the intensity values of the external voxels of the brain tissues of the eyeball and the temporo cheek as a reference, carrying out intensity normalization on the T1w image and the T2w image, wherein the specific formula is as follows:
wherein, X S represents the intensity distribution peak value of the input image in the corresponding region of the ICBM152 eyeball binarization mask; y S represents the intensity distribution peak of the input image in the region corresponding to the ICBM152 temporal cheek binarization mask; x R represents the distribution peak of eyeball mask intensity in the ICBM152 template; y R represents the peak distribution of temporal cheek mask intensities in the ICBM152 template; i represents the voxel value before intensity normalization; i c represents the intensity normalized voxel value.
4. The method for extracting quantitative index of cortical myelin based on T1w/T2w map according to claim 1, wherein the T1w/T2w map of gray matter region is calculated from the preprocessed T1w image and T2w image, specifically comprising:
s201, dividing the normalized T1w image and the normalized T2w image to obtain a T1w/T2w map in the individual space;
S202, obtaining an individual tissue probability map by means of T1w image segmentation calculation; the tissue probability map of the individual comprises a gray matter probability map, a white matter probability map and a cerebrospinal fluid probability map;
s203, selecting a probability threshold for the gray probability map, and binarizing the gray probability map to obtain a gray binarization mask.
5. The method for extracting quantitative index of cortical myelin based on T1w/T2w map of claim 4, wherein the calculation process of gray matter binarization mask in S203 specifically comprises:
BGM(x,y,z)＝PGM(x,y,z)≥threshold
wherein x, y and z are three coordinate directions respectively; b GM is a gray matter binary mask; p GM is a tissue probability map; threshold is a probability threshold that is expressed as the probability that the pixel location belongs to gray matter.
6. The method for extracting quantitative index of cortical myelin based on T1w/T2w map according to claim 4, wherein the probability threshold in S203 is selected to be 0.5-0.8.
7. The method for extracting quantitative indexes of cortical myelin based on a T1w/T2w map according to claim 4, wherein the method for extracting quantitative indexes of myelin under each partition in the gray matter partition template by covering the gray matter partition template onto the T1w/T2w map of the gray matter region is specifically as follows:
S301, performing product operation on the T1w/T2w map in S201 and the gray matter binarization mask in S203 to obtain a gray matter region T1w/T2w map in the individual space;
s302, normalizing gray matter partition templates to individual anatomical spaces under T1w images of each patient by adopting an interpolation method; the interpolation method adopts a nearest neighbor interpolation method;
S303, covering the gray area T1w/T2w map of the standardized gray area in S302 to extract myelin quantification indexes based on gray ROI levels, and calculating the pixel intensity mean value of each ROI in the tissue template in the gray area T1w/T2w map to obtain the T1w/T2w intensity mean value of each gray area template ROI under the individual T1w/T2w gray map; the specific calculation process is as follows:
Wherein i represents the partition number in the gray matter partition template; myelin i represents the calculated myelin quantification index in the corresponding partition; r i represents the voxel intensity value of the gray matter region T1w/T2w map obtained in S301 in the corresponding partition; n i represents the total number of voxels contained in the corresponding partition; x, y, z represent three coordinate directions, respectively.
8. A cortical myelin quantitative index extraction system based on a T1w/T2w profile, comprising:
The preprocessing module is used for preprocessing the T1w image and the T2w image;
the image calculation module is used for calculating a T1w/T2w map of the gray matter region through the preprocessed T1w image and the preprocessed T2w image;
the index extraction module is used for covering the gray matter partition template on the T1w/T2w map of the gray matter region and extracting myelin quantification indexes under each partition in the gray matter partition template.
9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any of claims 1-7 when the computer program is executed.
10. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the method according to any one of claims 1-7.
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