Abstract

Automated Cortical Thickness Analysis (ACTA) has emerged as a pivotal tool in neuroimaging, enabling the precise measurement of cortical thickness from structural MRI scans. This literature review synthesizes key advancements in ACTA methodologies, including the introduction of automated cortical surface reconstruction, standardization in cortical parcellation, power analysis, and the integration of machine learning techniques. The review highlights the significant applications of ACTA in understanding brain structure and function, particularly in aging, neurodegenerative diseases like Alzheimer's, and psychiatric conditions such as schizophrenia and Autism Spectrum Disorder (ASD). Studies reveal that cortical thinning, as measured by ACTA, is a crucial biomarker for cognitive decline, disease progression, and symptom severity across various conditions. The integration of ACTA with other neuroimaging modalities offers promising avenues for future research. As neuroimaging continues to evolve, ACTA's contributions to clinical practice and research underscore its potential to improve diagnostic accuracy and guide personalized therapeutic interventions.