Changes in the sulcal size associated with autism spectrum disorder revealed by sulcal morphometry.
Autism spectrum disorder (ASD) is a complex, neurodevelopmental disorder with various structural abnormalities for different patient groups. Because of the heterogeneity of the disorder, several biomarkers have been suggested so far. Here, we explore the potential of sulcal surface and length as biomarkers. Three-dimensional T1-weighted images of 15 adolescents of normal intelligence with ASD and 15 age-, sex-, and intelligence quotient-matched control adolescents were analysed using Brainvisa 4.0 (http://www.brainvisa.info), which automatically extracts the cortical folds and labels them as 59 sulcal pieces. For each sulcus, the surface, length, and mean geodesic depth were computed using morphometry analysis within this software package. General linear model was conducted to compare the estimated values for the two groups, ASD and control. In the ASD group, the left insula and the right intraparietal sulcus (IPS) had significantly higher values for surface and length, respectively. Nonetheless for all sulcal pieces, the mean geodesic depth was not significantly different between the two groups. Our results suggest that sulcal surface and length can have correlation with morphological changes of cortex in ASD. Greater surface area and length in insula and IPS, respectively, may reflect greater folding. This could result in greater separation of functions with an impact upon the integrative functions of these regions.
Department of Clinical Physics and Psychological Medicine, College of Medicine, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK. m.shokouhi.1@research.gla.ac.uk
Mahsa
M
Shokouhi
Justin H G
JH
Williams
Gordon D
GD
Waiter
Barrie
B
Condon
D000293:Adolescent; D000367:Age Factors; D015415:Biomarkers; D002540:Cerebral Cortex / Q000473:pathology*; D002648:Child; D002659:Child Development Disorders, Pervasive / Q000175:diagnosis* / Q000473:pathology*; D004292:Dominance, Cerebral / Q000502:physiology; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D021621:Imaging, Three-Dimensional; D016014:Linear Models; D008279:Magnetic Resonance Imaging; D008297:Male; D010296:Parietal Lobe / Q000473:pathology; D012016:Reference Values; D012984:Software; D013223:Statistics as Topic; D055815:Young Adult
D015415:Biomarkers