Longitudinal rs-fMRI changes reveal local brain function in patients with schizophrenia
Poster No:
496
Submission Type:
Abstract Submission
Authors:
Song Liu1, Yong Han1, Han Shi1, Xiaoge Guo1, Xiujuan Wang1, Luxian Lv1, Wenqiang Li1, Yongfeng Yang1
Institutions:
1the Second Affiliated Hospital of Xinxiang Medical University, Xinxiang, HENAN
First Author:
Co-Author(s):
Introduction:
Schizophrenia (SZ) is a serious psychiatric disorder that affects 1% of the world's population and the main symptoms can be classified as positive, negative, and general psychopathology symptoms [1,2]. Regional brain function is measured by assessing ALFF, fALFF, and ReHo [3,4]. These 3 voxel based metrics define brain functional characteristics from different perspectives and show a progressive relationship that allows for more sensitive identification of regional abnormalities. A reliable brain atlas reflecting this subdivision is essential to quantitatively investigate the functional and structural characteristics of the human brain. We used Brainnetome Atlas [5]to investigate the changes in rs-fMRI indicators before and after treatment in SZ patients and their association with symptoms and cognitive function.
Methods:
This study recruited 109 patients with SZ from the Second Affiliated Hospital of Xinxiang Medical College. Collect their baseline and 8-week post-treatment imaging, PANSS and MATRICS consensus cognitive test (MCCB) data. The patient meets the clinical diagnostic criteria for SZ in DSM-IV of the United States, and is confirmed by two attending physicians or more psychiatrists. Preprocess the original image of the patient, and then calculate individual ALFF, fALFF, and ReHo to evaluate functional activity. Statistical analysis was conducted using Matlab2020a, and statistical charts were conducted using PyCharm software based on Python. All continuous variables are represented by the mean SD. Map the resting fMRI indicators (ALFF, fALFF, and ReHo) calculated by SZ patients to Brainnetome Atlas in Matlab software, and extract the mean values of each brain region in the map for analysis. To determine the differences in resting fMRI indicators between baseline and 8-week treatment patients, we used paired sample t-tests for analysis and performed Bonferroni correction on the results. Then, Pearson correlation analysis was performed on the baseline resting fMRI indicators of brain regions that underwent changes after treatment with PANSS reduction rate, Spearman correlation analysis was performed on MCCB reduction rate (MCCB reduction rates did not conform to normal distribution), and Bonferroni correction was performed on the results.
Results:
Compared with baseline, after 8 weeks of treatment, the brain regions with increased ALFF were distributed in the frontal lobe, parietal lobe, insula gyrus, cingulate gyrus, and basal ganglia; The brain regions with reduced ALFF are distributed in the temporal and occipital lobes; The increased brain area of fALFF is distributed in the temporal lobe, cingulate gyrus, basal ganglia, and thalamus; The brain regions with decreased fALFF are distributed in the frontal, temporal, parietal, and occipital lobes; The increased brain area of ReHo is distributed in the frontal lobe; The brain regions with reduced ReHo are distributed in the frontal lobe, temporal lobe, parietal lobe, insular gyrus, and occipital lobe (Figure 1). The correlation analysis between baseline resting fMRI indicators and PANSS and MCCB reduction rates in brain regions that underwent changes after treatment is shown in Figure 2.
Conclusions:
This study found that the brain regions with changes in local brain function before and after treatment were mainly concentrated in the frontal lobe, temporal lobe, and occipital lobe. Two subregions of the middle frontal gyrus were negatively correlated with the reduction rate of positive factors and general symptoms, respectively. The two subregions of the occipital lobe were positively correlated with word learning and symbol encoding in MCCB.These findings provide new evidence for the hypothesis of abnormal SZ functional activity and potential neurobiological objective indicators for clinical diagnosis and efficacy prediction.
Disorders of the Nervous System:
Psychiatric (eg. Depression, Anxiety, Schizophrenia) 1
Modeling and Analysis Methods:
Task-Independent and Resting-State Analysis 2
Keywords:
FUNCTIONAL MRI
Schizophrenia
Other - ALFF; fALFF; ReHo; symptom; cognitive
1|2Indicates the priority used for review
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[4] Zang Y.（2004a），'Regional homogeneity approach to fMRI data analysis'，NeuroImage，vol. 22， no. 1， pp. 394–400
[5] Fan LZ. (2016a)，'The Human Brainnetome Atlas: A New Brain Atlas Based on Connectional Architecture'，Cerebral Cortex， vol. 26， no. 8， pp. 3508-26