Brain Volume and Cortical Thickness in Type 2 Diabetes: Software Implementation and Comparative Analysis

Abstract

This thesis aimed to investigate the effects of Type 2 Diabetes Mellitus (T2DM) on brain volumetrics, specifically in terms of changes in cortical thickness and grey matter volume. Using the surface based morphometry software FreeSurfer and Fast- Surfer, a comparative analysis was conducted to evaluate the reliability, effectiveness, and runtime of these software in assessing brain morphology in individuals with T2DM compared to healthy controls. MRI data from two datasets, OASIS and MIND, were processed and analysed, focusing on regions of interest included in the Desikan–Killiany–Tourville atlas using both software. Intra-software reliability was assessed through three metrics, Pearson Correlation Coefficient, Intraclass Correlation Coefficient, and Test-Retest Variability. This was done to determine if both software are consistent in their estimates of brain volumetrics. The inter-software reliability was assessed through the Intraclass Correlation Coefficient. The inter-software reliability was performed to determine if FastSurfer gives a similar result to FreeSurfer, which is more extensively validated. Additionally, the runtime performance of FreeSurfer and FastSurfer was compared to determine their efficiency. The results demonstrated high intra-software reliability for both FreeSurfer and FastSurfer in measuring brain volumes and cortical thickness. The two software also demonstrated high inter-software reliability, demonstrating that FastSurfer has a similar accuracy to FreeSurfer. FastSurfer also exhibited a significantly faster runtime. All of this combined highlights FastSurfer’s potential for large-scale studies and clinical applications. However, contrary to expectations based on prior literature, significant differences in brain volumes between the T2DM group and healthy controls were not found. In conclusion, while this study validates the use of FreeSurfer and FastSurfer for neuroimaging analysis, it also highlights the complexity of detecting brain volume changes associated with T2DM, pointing towards the necessity for further investigations. The improved runtime, as well as the high intra- and inter-software reliability of FastSurfer suggests it as a preferable software for this purpose.