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Volume-based and Surface-Based Methods in Autism Compared with Healthy Controls Are Free surfer and CAT12 in Agreement?

Authors :
FARAJI, Reyhane
GANJI, Zohreh
KHANDAN KHADEM, Zahra
AKBARI-LALIMI, Hossein
EIDY, Fereshteh
ZARE, Hoda
Source :
Iranian Journal of Child Neurology; Winter2024, Vol. 18 Issue 1, p93-118, 26p
Publication Year :
2024

Abstract

Objectives: Autism Spectrum Disorder (ASD) encompasses a range of neurodevelopmental disorders, and early detection is crucial. This study aims to identify the Regions of Interest (ROIs) with significant differences between healthy controls and individuals with autism, as well as evaluate the agreement between FreeSurfer 6 (FS6) and Computational Anatomy Toolbox (CAT12) methods. Materials & Methods ISurface-based and volume-based features were extracted from FS software and CAT12 toolbox for Statistical Parametric Mapping (SPM) software to estimate ROI-wise biomarkers. These biomarkers were compared between 18 males Typically Developing Controls (TDCs) and 40 male subjects with ASD to assess group differences for each method. Finally, agreement and regression analyses were performed between the two methods for TDCs and ASD groups. Results Both methods revealed ROIs with significant differences for each parameter. The Analysis of Covariance (ANCOVA) showed that both TDCs and ASD groups indicated a significant relationship between the two methods (p<0.001). The R2 values for TDCs and ASD groups were 0.692 and 0.680, respectively, demonstrating a moderate correlation between CAT12 and FS6. Bland-Altman graphs showed a moderate level of agreement between the two methods. Conclusion The moderate correlation and agreement between CAT12 and FS6 suggest that while some consistency is observed in the results, CAT12 is not a superior substitute for FS6 software. Further research is needed to identify a potential replacement for this method. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
17354668
Volume :
18
Issue :
1
Database :
Supplemental Index
Journal :
Iranian Journal of Child Neurology
Publication Type :
Academic Journal
Accession number :
175433843
Full Text :
https://doi.org/10.22037/IJCN.V18i1.43294