Methods and devices for processing MRI data on regional brain function and blood perfusion changes

Abstract

A method and apparatus for processing MRI data on changes in local brain function and blood perfusion, the method comprising: (1) collecting T1-weighted imaging, T2-weighted imaging, diffusion-weighted imaging, high-resolution T1-weighted imaging, resting-state fMRI, and 3D-pCASL sequence imaging for each subject on an MRI scanner; (2) processing the resting-state fMRI to obtain the following indicators: local consistency ReHo, low-frequency amplitude ALFF, and low-frequency amplitude fraction fALFF; (3) processing the 3D-pCASL sequence imaging to obtain perfusion indicators in each brain region, including mean cerebral blood flow mCBF, arterial transit time ATT, and arterial cerebral blood volume aCBV; (4) performing statistical analysis between patients and healthy controls on the data obtained in steps (2) and (3), and using correlation analysis to determine the correlation between statistically significant indicators and scale scores.

Description

Technical Field

[0001] This invention relates to the field of medical image processing technology, and more particularly to a method for processing MRI data of local brain function and blood perfusion changes, as well as an apparatus for processing MRI data of local brain function and blood perfusion changes. Background Technology

[0002] Magnetic resonance imaging (MRI) technology, after decades of development, has become an important research tool in neuroimaging for assessing structural, functional, and metabolic changes in the nervous system. Blood oxygen level dependent-functional magnetic resonance imaging (BOLD fMRI) utilizes changes in blood oxygen levels and hemodynamics before and after neuronal activation to reveal spontaneous activity of neurons in specific brain regions. BOLD-fMRI imaging of amblyopic patients in a resting state provides an indirect characterization of localized spontaneous neuronal physiological activity in the brain, thereby assessing the impact of developmental disorders involving visual input and processing abnormalities on the central nervous system from a functional perspective. The widely used BOLD-fMRI signal can reflect the response of dynamically changing cerebral blood flow (CBF), cerebral oxygen metabolism rate, and arterial cerebral blood volume (CBV) to changes in neural activity. Generally, changes in BOLD signal are positively correlated with changes in CBF, but are also influenced by changes in other coupling factors. Arterial spin labling (ASL) is a brain perfusion magnetic resonance imaging technique that labels and tracks hydrogen protons in arterial blood without the need for exogenous tracers, thus obtaining images of blood flow perfusion. Therefore, ASL has advantages such as being non-invasive, repeatable, and having high resolution. Among these techniques, quasi-continuous arterial spin labling (pCASL) with multiple post-label delays (PLD) has a high signal-to-noise ratio and can more accurately assess changes in cerebral blood flow. rs-fMRI and ASL imaging techniques have unique advantages in revealing changes in regional brain function and blood perfusion in patients. Summary of the Invention

[0003] To overcome the shortcomings of the prior art, the technical problem to be solved by the present invention is to provide an MRI data processing method for local brain function and blood perfusion changes. This method can accurately process magnetic resonance images of local brain function and blood perfusion changes to obtain imaging indicators of local brain functional activity and blood perfusion changes, thereby understanding the physiological mechanisms of spontaneous neuronal activity and blood supply changes in the brain.

[0004] The technical solution of this invention is: a method for processing MRI data of local brain function and blood perfusion changes, which includes the following steps:

[0005] (1) T1-weighted imaging, T2-weighted imaging, diffusion-weighted imaging, high-resolution T1-weighted imaging, resting-state fMRI, and 3D-pCASL sequence imaging were collected for each subject on a magnetic resonance scanner.

[0006] (2) Process the resting fMRI to obtain local consistency ReHo, low frequency amplitude ALFF, and low frequency amplitude fraction fALFF;

[0007] (3) Process the 3D-pCASL sequence imaging to obtain perfusion indicators such as mean cerebral blood flow mCBF, arterial transit time ATT and arterial cerebral blood volume aCBV in each region;

[0008] (4) Perform statistical analysis on the data obtained in steps (2) and (3), and use correlation analysis to determine the correlation between statistically significant indicators and scale scores.

[0009] This invention collects T1-weighted imaging, T2-weighted imaging, diffusion-weighted imaging, high-resolution T1-weighted imaging, resting-state fMRI, and 3D-pCASL sequence imaging for each subject on a magnetic resonance imaging scanner; processes the resting-state fMRI to obtain local consistency ReHo, low-frequency amplitude ALFF, and low-frequency amplitude fraction fALFF; processes the 3D-pCASL sequence imaging to obtain perfusion indicators such as mean cerebral blood flow mCBF, arterial transit time ATT, and arterial cerebral blood volume aCBV in each brain region; statistically analyzes the data obtained in steps (2) and (3), and uses correlation analysis to determine the correlation between statistically significant indicators and scale scores. Therefore, it can accurately process magnetic resonance images with changes in blood perfusion to obtain imaging indicators of local brain functional activity and changes in blood perfusion, thereby understanding the physiological mechanisms of spontaneous neuronal activity and changes in blood supply in the brain.

[0010] A device for processing MRI data on local brain function and blood perfusion changes is also provided, comprising:

[0011] The image acquisition module is configured to collect T1-weighted imaging, T2-weighted imaging, diffusion-weighted imaging, high-resolution T1-weighted imaging, resting-state fMRI, and 3D-pCASL sequence imaging for each subject on a magnetic resonance scanner.

[0012] The image processing module is configured to process resting-state fMRI to obtain local consistency ReHo, low-frequency amplitude ALFF, and low-frequency amplitude fraction fALFF.

[0013] The sequence imaging processing module is configured to process 3D-pCASL sequence imaging to obtain perfusion parameters such as mean cerebral blood flow (mCBF), arterial transit time (ATT), and arterial cerebral blood volume (aCBV) in each region.

[0014] The data analysis module is configured to perform statistical analysis on the data obtained from the image processing module and the sequence imaging processing module, and to use correlation analysis methods to determine the correlation between statistically significant indicators and scale scores. Attached Figure Description

[0015] Figure 1 A flowchart is shown for a method of processing MRI data on changes in local brain function and blood perfusion according to the present invention. Detailed Implementation

[0016] like Figure 1 As shown, this method for processing MRI data on localized changes in brain function and blood perfusion includes the following steps:

[0017] (1) T1-weighted imaging, T2-weighted imaging, diffusion-weighted imaging, high-resolution T1-weighted imaging, resting-state fMRI, and 3D-pCASL sequence imaging were collected for each subject on a magnetic resonance scanner.

[0018] (2) Process the resting fMRI to obtain local consistency ReHo, low frequency amplitude ALFF, and low frequency amplitude fraction fALFF;

[0019] (3) Process the 3D-pCASL sequence imaging to obtain perfusion indicators such as mean cerebral blood flow mCBF, arterial transit time ATT and arterial cerebral blood volume aCBV in each region;

[0020] (4) Perform statistical analysis on the data obtained in steps (2) and (3), and use correlation analysis to determine the correlation between statistically significant indicators and scale scores.

[0021] This invention collects T1-weighted imaging, T2-weighted imaging, diffusion-weighted imaging, high-resolution T1-weighted imaging, resting-state fMRI, and 3D-pCASL sequence imaging for each subject on a magnetic resonance scanner; processes the resting-state fMRI to obtain local consistency ReHo, low-frequency signal energy ALFF, and low-frequency amplitude fraction fALFF; processes the 3D-pCASL sequence imaging to obtain perfusion indicators such as mean cerebral blood flow mCBF, arterial transit time ATT, and arterial cerebral blood volume aCBV in each region; statistically analyzes the data obtained in steps (2) and (3), and uses correlation analysis to determine the correlation between statistically significant indicators and scale scores. Therefore, it can accurately process magnetic resonance images with changes in blood perfusion to obtain imaging indicators of local brain functional activity and changes in blood perfusion, thereby understanding the physiological mechanisms of spontaneous neuronal activity and changes in blood supply in the brain.

[0022] Preferably, in step (1), 3D-T1WI uses sagittal imaging, while the rest are axial imaging. The axial scanning baseline is the anterior-posterior commissure line, and the sagittal scanning baseline is the midline of the brain. During the scan, the subject lies supine with their head first, and a sponge pad is placed on both sides of the head to reduce head movement. The subject wears an internal earplug and an external earmuff.

[0023] Preferably, in step (1), the scanning parameters are:

[0024] T1WI: TR = 3322.65ms, TE = 30.84ms, matrix = 512x512, flip angle = 110°, slice thickness = 5.0mm, slice interval = 6mm, acquisition time is 1min 7s;

[0025] T2WI: TR = 7240.64ms, TE = 93.0ms, matrix: 512x512, flip angle = 142°, layer thickness: 5.0mm, layer spacing: 6mm, acquisition time: 51s;

[0026] DWI: TR=3000ms, TE=67.7ms, matrix: 256x256, flip angle=90°, slice thickness: 5.0mm, slice interval: 6mm, acquisition time: 24s;

[0027] 3D-T1WI: Field of view = 256×256mm, Matrix = 256×256, Slice thickness = 1.0mm, Echo time = MIN, Repetition time = 6.7ms, Flip angle = 12°, Number of slices = 192, Scan time 4min41s;

[0028] rs-fMRI: Field of view = 224×224mm, Matrix = 64×64, Slice thickness = 3.5mm, Echo time = 30ms, Repetition time = 2000ms, Flip angle = 90°, Number of slices = 33, Slice interval = 0.7mm, Number of excitations (NEX) = 1, Scan time 8min;

[0029] 3D-pCASL: Field of view = 240×240mm, slice thickness = 4.0mm, echo time = 14.6ms, repetition times = 4817, 5029, 5512ms respectively, flip angle = 111°, number of slices = 36, NEX = 3, PLD = 1525, 2025, 2525ms respectively, scan time = 6min54s, 7min13s, 7min54s respectively.

[0030] Preferably, step (2) includes the following sub-steps:

[0031] (2.1) Convert the raw DICOM data to NIFTI format, remove the first 10 time points, exclude those with head translation > 2mm and / or rotation > 2°, normalize the data and 3D-T1 structural images, and resample the voxels to 3×3×3mm. 3 Based on the MNI standard brain template, functional images and individual structural images were registered; covariate noise and linear drift, including physiological noise, global noise and gray and white matter noise, were removed.

[0032] (2.2) After filtering with a bandpass filter range of 0.01 to 0.10 Hz, the local consistency ReHo of the resting spontaneous neural activity in the original subject's brain regions was calculated. A Gaussian smoothing kernel with a full width at half maximum (FWHM) of 4 mm was used for spatial smoothing to improve the signal-to-noise ratio. When calculating the low-frequency amplitude, spatial smoothing was performed first, followed by bandpass filtering. The energy ALFF of the calculated low-frequency signal was divided by the power of the entire frequency band to obtain the low-frequency amplitude fraction fALFF.

[0033] (2.3) The ReHo, ALFF and fALFF values ​​were standardized by Z score to ensure that the data conformed to a normal distribution, which would facilitate the subsequent comparison between patients and healthy controls using independent samples t test.

[0034] Preferably, step (3) includes the following sub-steps:

[0035] (3.1) Convert the raw ASL data and CBF data into brain perfusion parameter maps, including mean cerebral blood flow mCBF, arterial transit time ATT and arterial cerebral blood volume aCBV;

[0036] (3.2) Standardization to MNI standard spatial brain template;

[0037] (3.3) Covering the Brainnetom map;

[0038] (3.4) Obtain the perfusion indicators of each zone: mean cerebral blood flow mCBF, arterial transit time ATT, and arterial cerebral blood volume aCBV.

[0039] Preferably, in step (4), the gender difference between groups is determined by the chi-square test. The mean ± standard deviation is used to describe continuous variables that conform to a normal distribution, while the median and the first and third quartiles are used to describe those that do not conform to a normal distribution. The comparison between groups of the former is conducted using an independent samples t-test, while the latter is conducted using a non-parametric test.

[0040] Preferably, in step (4), the perfusion indicators CBF, ATT, aCBV and the values ​​of ReHo, ALFF and fALFF of local brain spontaneous neural activity are compared between adult amblyopic patients and healthy control groups, and multiple comparison corrections are performed.

[0041] Those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium. When executed, the program includes the steps of the methods of the above embodiments. The storage medium can be ROM / RAM, magnetic disk, optical disk, memory card, etc. Therefore, corresponding to the method of the present invention, the present invention also includes an MRI data processing device for local brain function and blood perfusion changes. This device is typically represented in the form of functional modules corresponding to the steps of the method. The device includes:

[0042] The image acquisition module is configured to collect T1-weighted imaging, T2-weighted imaging, diffusion-weighted imaging, high-resolution T1-weighted imaging, resting-state fMRI, and 3D-pCASL sequence imaging for each subject on a magnetic resonance scanner.

[0043] The image processing module is configured to process resting-state fMRI to obtain local consistency ReHo, low-frequency amplitude ALFF, and low-frequency amplitude fraction fALFF.

[0044] The sequence imaging processing module is configured to process 3D-pCASL sequence imaging to obtain perfusion parameters such as mean cerebral blood flow (mCBF), arterial transit time (ATT), and arterial cerebral blood volume (aCBV) in each region.

[0045] The data analysis module is configured to perform statistical analysis on the data obtained from the image processing module and the sequence imaging processing module, and to use correlation analysis methods to determine the correlation between statistically significant indicators and scale scores.

[0046] This study primarily used resting-state functional magnetic resonance imaging (fMRI) and three-delay quasi-continuous arterial spin labeling imaging to compare adult amblyopia patients with age-, sex-, and education-matched healthy controls. It assessed changes in ReHo, ALFF, and fALFF in different brain regions, compared blood flow perfusion parameters CBF, ATT, and aCBV in each brain region, and investigated the correlation between these parameters and anxiety, depression, and quality of life scores in amblyopia patients.

[0047] 1. Changes in localized low-frequency amplitude (fraction) in adults with amblyopia

[0048] fMRI results showed no statistically significant differences in low-frequency amplitude ALFF (alpha-femoral free velocity) in brain regions compared to healthy controls in adult amblyopia patients. However, differences were observed in low-frequency amplitude fALFF values. Analysis revealed that the right frontal pole and right superior temporal gyrus fALFF were lower in the patient group than in healthy controls, while the right angular gyrus fALFF was higher. In unilateral amblyopia patients, those with left-sided amblyopia had significantly higher fALFF in the bilateral fusiform gyrus and left calcarine sulcus cortex than healthy controls, while those with right-sided amblyopia had decreased fALFF in the right superior temporal gyrus and increased fALFF in the right middle frontal gyrus. Previous studies have shown that in strabismic amblyopia patients, the ALFF value in the middle frontal gyrus is decreased, while the ALFF value in the superior frontal gyrus is increased. This seems inconsistent with the results of this study. However, studies using functional connectivity in amblyopia patients have found that the effective connectivity between the visual cortex and the left middle frontal gyrus and superior temporal gyrus is significantly lower in amblyopia patients than in normal controls. This may be because ALFF values ​​are easily affected by physiological noise (such as breathing and heartbeat) at higher frequencies. The fALFF value, expressed as the ratio of ALFF to the root mean square of the power spectrum across all frequencies, has higher sensitivity and specificity in detecting spontaneous brain activity. The decreased effective functional connectivity mentioned above may also stem from reduced spontaneous activity in these brain regions. The angular gyrus, located at the junction of the occipital, temporal, and parietal lobes, plays a crucial role in processing reading and semantic comprehension after visual input. Activation of the angular gyrus is more pronounced in amblyopia patients under task-oriented fMRI imaging. Current research generally recognizes the crucial role of the fusiform gyrus in facial and body shape recognition, as well as lexical and semantic processing. Damage to the fusiform gyrus is closely associated with prosopagnosia and facial recognition impairment. In response to attractive facial or shape-perceived stimuli, the BOLD response in the fusiform gyrus region is activated, evoking a wide distribution of neural networks involved in perception, decision-making, and reward pathways. Although the prediction of task-oriented brain region activation / deactivation based on resting-state spontaneous brain activity is still under investigation, existing research suggests that elevated fALFF in the bilateral fusiform gyrus and left calcarine fissure of left-sided amblyopia patients may reflect compensatory mechanisms for facial and shape recognition in daily life, as well as lateral activation of primary visual cortical regions due to the brain's dependence on the unaffected eye.

[0049] 2. Changes in local consistency in adults with amblyopia

[0050] Compared to the HC group, adult amblyopic patients showed elevated ReHo values ​​in the right fusiform gyrus and lingual gyrus of the occipital lobe. For unilateral amblyopic patients, left-sided amblyopic patients exhibited elevated ReHo values ​​in both fusiform gyruses. This is consistent with previous studies showing elevated ReHo values ​​in certain brain regions (including the lingual gyrus and supraoccipital / middle gyrus) of the V2 area of ​​the occipital visual cortex in strabismic amblyopic patients. The lingual gyrus and fusiform gyrus both belong to the medial occipital lobe and, as part of the visual network, are primarily involved in primary visual processing, logical analysis, and higher-level visual memory. Elevated ReHo values ​​indicate increased synchronicity of spontaneous neuronal activity in these regions, potentially suggesting compensatory changes in visual impairment. Furthermore, analysis of changes in interhemispheric functional connectivity in anisometropic amblyopic patients using voxel mirror homotopy connectivity (VMHC) revealed that the VMHC value in the lingual gyrus is associated with stereopsis, while the VMHC value in the fusiform gyrus is associated with the amount of anisometropia.

[0051] 3. Changes in cerebral blood flow in adults with amblyopia

[0052] Using ASL (Amblyopia Subtraction Alveolar Surgery) to non-invasively observe blood perfusion in adult patients with amblyopia, elevated CBF (circulatory flow factor) values ​​were observed in the caudate nucleus and nucleus accumbens of the basal ganglia. Simultaneously, the aCBV (asymptotic circulatory flow value) of the caudate nucleus was also statistically significant. The caudate nucleus contains numerous fiber projections to the prefrontal, parietal, occipital, and temporal lobes, participating in the cortical-striatal-globus pallidus-thalamic emotion regulation circuit, and thus participating in the regulation of emotion and cognition. Studies on Parkinson's disease patients with depression have shown enhanced functional connectivity between the caudate nucleus and visual-related brain regions (including the cuneus, lingual gyrus, and middle occipital gyrus). Although adult patients with amblyopia in this study did not exhibit significant anxiety or depression, the potential link between abnormal functional connectivity of the caudate nucleus and the visual processing network may also exist in amblyopia patients. Previously, the insular cortex was simply considered the area of ​​visceral sensation and motor function; however, recent studies have found that the insula is involved in or dominates vestibular, somatosensory, somatomotor, motor association, limbic integration, and language functions. Among the brain regions exhibiting ATT differences, besides the insula, the anterior cingulate cortex also participates in the formation of the emotional network and has strong functional connections with the limbic system, including the nucleus accumbens. Simultaneously, the insula is also an important component of the default-mode network (DMN). ATT represents the time it takes for arterial blood to travel from the labeled location to the imaging plane, and in cerebrovascular diseases, it is affected by the degree of vascular occlusion or the formation of collateral circulation. Decreased ATT in these brain regions, including the middle occipital gyrus and suboccipital gyrus, reflects a decrease in the corresponding blood flow velocity, which may predict impaired neural activity in the corresponding visual, default-mode, and emotional network functional areas.

[0053] This study found a statistically significant correlation between disease duration and scores on the first dimension of the LVQOL scale (distance visual acuity, motion perception, and light perception). Patients' assessments of their need for distance visual acuity, motion perception, and light perception increased with disease duration. In adult amblyopic patients, the ATT value in the V5 / MT+ area of ​​the left occipital lobe higher visual cortex correlated with the third part of the LVQOL scale; that is, as the ATT value increased, the patient's score on the accommodative ability component of the LVQOL scale increased. This may be because amblyopia develops during early childhood visual development, and adult amblyopic patients often experience a prolonged disease course. Although the blood flow time in the areas responsible for visual-motor perception is prolonged, patients who subjectively rely more on the healthy eye do not experience a weakening of their accommodative adaptation to daily life. While studies have shown that visual impairment can easily induce various psychological disorders and negative emotions, this study did not find significant anxiety or depression in adult amblyopic patients. This may be because the SAS and SDS scales are subjective self-assessment scales and require combination with objective physician assessment or the use of more sensitive scales.

[0054] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Any simple modifications, equivalent changes, and alterations made to the above embodiments based on the technical essence of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A method for processing MRI data showing changes in local brain function and blood perfusion, comprising the following steps: (1) T1-weighted imaging, T2-weighted imaging, diffusion-weighted imaging, high-resolution T1-weighted imaging, resting-state fMRI, and 3D-pCASL sequence imaging were collected for each subject on a magnetic resonance scanner. (2) Process the resting fMRI to obtain local consistency ReHo, low frequency amplitude ALFF, and low frequency amplitude fraction fALFF; (3) Process the 3D-pCASL sequence imaging to obtain the perfusion indicators of average cerebral blood flow mCBF, arterial transit time ATT and arterial cerebral blood volume aCBV in each region; (4) Perform statistical analysis on the data obtained in steps (2) and (3), and use correlation analysis to determine the correlation between statistically significant indicators and scale scores; in step (4), compare whether there are differences in perfusion indicators CBF, ATT, aCBV and brain local spontaneous neural activity ReHo, ALFF and fALFF values ​​between adult amblyopic patients and healthy control groups, and perform multiple comparison corrections.

2. The MRI data processing method for local brain function and blood perfusion changes according to claim 1, characterized in that: In step (1), 3D-T1WI uses sagittal imaging, while the rest are axial imaging. The axial scanning baseline is the anterior-posterior commissure line, and the sagittal scanning baseline is the midline of the brain. During the scan, the subject lies supine with their head first, and a sponge pad is placed on both sides of the head to reduce head movement. The subject wears an internal earplug and an external earmuff.

3. The MRI data processing method for local brain function and blood perfusion changes according to claim 2, characterized in that: In step (1), the scanning parameters are: T1WI: TR=3322.65ms, TE=30.84ms, matrix=512x512, flip angle=110°, slice thickness=5.0mm, slice interval=6mm, acquisition time is 1min 7s; T2WI: TR=7240.64ms, TE=93.0ms, matrix: 512x512, flip angle=142°, layer thickness: 5.0mm, layer spacing: 6mm, acquisition time: 51s; DWI: TR=3000ms, TE=67.7ms, matrix: 256x256, flip angle=90°, slice thickness: 5.0mm, slice interval: 6mm, acquisition time: 24s; 3D-T1WI: Field of view = 256×256mm, Matrix = 256×256, Slice thickness = 1.0mm, Echo time = MIN, Repetition time = 6.7ms, Flip angle = 12°, Number of slices = 192, Scan time 4min41s; rs-fMRI: Field of view = 224×224mm, Matrix = 64×64, Slice thickness = 3.5mm, Echo time = 30ms, Repetition time = 2000ms, Flip angle = 90°, Number of slices = 33, Slice interval = 0.7mm, Number of excitations (NEX) = 1, Scan time 8min; 3D-pCASL: Field of view = 240×240mm, slice thickness = 4.0mm, echo time = 14.6ms, repetition times = 4817, 5029, 5512ms respectively, flip angle = 111°, number of slices = 36, NEX = 3, PLD = 1525, 2025, 2525ms respectively, scan time = 6min54s, 7min13s, 7min54s respectively.

4. The MRI data processing method for local brain function and blood perfusion changes according to claim 3, characterized in that: Step (2) includes the following sub-steps: (2.1) Convert the original DICOM data format to NIFTI format, remove the first 10 time points, exclude those with head translation > 2 mm and / or rotation > 2°, normalize the data and 3D-T1 structural images, and resample the voxels to 3×3×3 mm. 3 Based on the MNI standard brain template, functional images and individual structural images were registered; covariate noise and linear drift, including physiological noise, global noise and gray and white matter noise, were removed. (2.2) After filtering with a bandpass filter range of 0.01~0.10Hz, the local consistency ReHo of the resting spontaneous neural activity in the brain regions of the original subjects was calculated. A Gaussian smoothing kernel with a full width at half height of 4mm was used for spatial smoothing to improve the signal-to-noise ratio. When calculating the low-frequency amplitude ALFF, spatial smoothing was performed first, and then bandpass filtering was performed after the calculation. The calculated low-frequency amplitude ALFF was divided by the power of the entire frequency band to obtain the low-frequency amplitude fraction fALFF. (2.3) The ReHo, ALFF and fALFF values ​​were standardized by Z score to ensure that the data conformed to a normal distribution, which would facilitate the subsequent comparison between patients and healthy controls using independent samples t test.

5. The MRI data processing method for local brain function and blood perfusion changes according to claim 4, characterized in that: Step (3) includes the following sub-steps: (3.1) Convert the raw ASL data and CBF data into a brain perfusion parameter map, including mean cerebral blood flow mCBF, arterial transit time ATT and arterial cerebral blood volume aCBV; (3.2) Standardization to MNI standard spatial brain template; (3.3) Covering the Brainnetom map; (3.4) Obtain the perfusion parameters of each zone: mean cerebral blood flow mCBF, arterial transit time ATT, and arterial cerebral blood volume aCBV.

6. The MRI data processing method for regional brain function and blood perfusion changes according to claim 5, characterized in that: In step (4), the gender difference between groups is determined by the chi-square test. The mean ± standard deviation is used to describe continuous variables that conform to a normal distribution, while the median and the first and third quartiles are used to describe those that do not conform to a normal distribution. The comparison between groups of the former is conducted using the independent samples t-test, while the latter is conducted using a non-parametric test.

7. The MRI data processing method for regional brain function and blood perfusion changes according to claim 6, characterized in that: In step (4), the perfusion parameters CBF, ATT, aCBV and the values ​​of ReHo, ALFF and fALFF of local brain spontaneous neural activity are compared between adult amblyopic patients and healthy control groups, and multiple comparison corrections are performed.

8. An MRI data processing device for regional brain function and blood perfusion changes, characterized in that: It includes: The image acquisition module is configured to collect T1-weighted imaging, T2-weighted imaging, diffusion-weighted imaging, high-resolution T1-weighted imaging, resting-state fMRI, and 3D-pCASL sequence imaging for each subject on a magnetic resonance scanner. The image processing module is configured to process resting-state fMRI to obtain local consistency ReHo, low-frequency amplitude ALFF, and low-frequency amplitude fraction fALFF. The sequence imaging processing module is configured to process 3D-pCASL sequence imaging to obtain perfusion parameters such as mean cerebral blood flow (mCBF), arterial transit time (ATT), and arterial cerebral blood volume (aCBV) in each region. The data analysis module is configured to perform statistical analysis on the data obtained from the image processing module and the sequence imaging processing module. It uses correlation analysis methods to determine the correlation between statistically significant indicators and scale scores. It compares whether there are differences in perfusion indicators CBF, ATT, aCBV and brain local spontaneous neural activity ReHo, ALFF and fALFF values ​​between adult amblyopic patients and healthy controls, and performs multiple comparison corrections.

Images