Cerebellar Structural Abnormality in Autism Spectrum Disorder: A Magnetic Resonance Imaging Study
- Author:
Qifang LU
1
;
Jin CHEN
;
Yanming WANG
;
Li HUANG
;
Zhoufan JIANG
;
Benedictor Alexander NGUCHU
;
Shishuo CHEN
;
Bensheng QIU
;
Xiaoxiao WANG
Author Information
- Publication Type:Original Article
- From:Psychiatry Investigation 2023;20(4):334-340
- CountryRepublic of Korea
- Language:English
-
Abstract:
Objective:This study uses structural magnetic resonance imaging to explore changes in the cerebellar lobules in patients with autism spectrum disorder (ASD) and further analyze the correlation between cerebellar structural changes and clinical symptoms of ASD.
Methods:A total of 75 patients with ASD and 97 typically developing (TD) subjects from Autism Brain Imaging Data Exchange dataset were recruited. We adopted an advanced automatic cerebellar lobule segmentation technique called CEREbellum Segmentation to segment each cerebellar hemisphere into 12 lobules. Normalized cortical thickness of each lobule was recorded, and group differences in the cortical measures were evaluated. Correlation analysis was also performed between the normalized cortical thickness and the score of Autism Diagnostic Interview-Revised.
Results:Results from analysis of variance showed that the normalized cortical thickness of the ASD group differed significantly from that of the TD group; specifically, the ASD group had lower normalized cortical thickness than the TD group. Post-hoc analysis revealed that the differences were more predominant in the left lobule VI, left lobule Crus I and left lobule X, and in the right lobule VI and right lobule Crus I. Lowered normalized cortical thickness in the left lobule Crus I in the ASD patients correlated positively with the abnormality of development evident at or before 36 months subscore.
Conclusion:These results suggest abnormal development of cerebellar lobule structures in ASD patients, and such abnormality might significantly influence the pathogenesis of ASD. These findings provide new insights into the neural mechanisms of ASD, which may be clinically relevant to ASD diagnosis.
