Cortical Thickness and Clinical Findings in Prescholar Children With Autism Spectrum Disorder

• Published in: Frontiers in neuroscience 2022-02, Vol.15, p.776860-776860
• Main Authors: Lucibello, Simona, Bertè, Giovanna, Verdolotti, Tommaso, Lucignani, Martina, Napolitano, Antonio, D'Abronzo, Rosa, Cicala, Maria G, Pede, Elisa, Chieffo, Daniela, Mariotti, Paolo, Colosimo, Cesare, Mercuri, Eugenio, Battini, Roberta
• Format: Article
• Language: English
• Subjects: Autism; autism spectrum disorder (ASD); Autistic children; Automation; Behavior; Brain; Communication; cortical thickness; Datasets; Environmental factors; local gyrification index; Magnetic resonance imaging; MRI; Neural networks; Neuroimaging; neuropsychological; Neuroscience; pre-scholar child; Risk factors; Substantia alba
• ISSN: 1662-4548; 1662-453X; 1662-453X
• DOI: 10.3389/fnins.2021.776860

The term autism spectrum disorder (ASD) includes a wide variability of clinical presentation, and this clinical heterogeneity seems to reflect a still unclear multifactorial etiopathogenesis, encompassing different genetic risk factors and susceptibility to environmental factors. Several studies and many theories recognize as mechanisms of autism a disruption of brain development and maturation time course, suggesting the existence of common neurobiological substrates, such as defective synaptic structure and aberrant brain connectivity. Magnetic resonance imaging (MRI) plays an important role in both assessment of region-specific structural changes and quantification of specific alterations in gray or white matter, which could lead to the identification of an MRI biomarker. In this study, we performed measurement of cortical thickness in a selected well-known group of preschool ASD subjects with the aim of finding correlation between cortical metrics and clinical scores to understand the underlying mechanism of symptoms and to support early clinical diagnosis. Our results confirm that recent brain MRI techniques combined with clinical data can provide some useful information in defining the cerebral regions involved in ASD although large sample studies with homogeneous analytical and multisite approaches are needed.