Macrostructural and microstructural alterations of hippocampal subregions in T2DM: NODDI provides added value to DTI and volumetric analyses - Xuan Huang; Ziyu Diao; Die Shen; Jianyu Li; Jiahe Wang; Kun Wang; Shijun Qiu (Brain Research Bulletin)
Objective: We explored macrostructural and microstructural changes in the hippocampal subregions of patients with type 2 diabetes mellitus (T2DM) and compared the effectiveness of neurite orientation dispersion and density imaging (NODDI) with that of traditional diffusion tensor imaging (DTI) and volumetric analysis in detecting structural alterations. Methods: A total of 302 participants (128 T2DM patients and 174 healthy controls) underwent 3.0-T magnetic resonance imaging and neuropsychological assessments. Hippocampal subregions were segmented and registered using FreeSurfer and SPM, with DTI and NODDI analyses being performed to assess microstructural changes. Neuropsychological and clinical data were further analyzed to explore correlations with cognitive function. Results: Significant microstructural alterations were observed in the hippocampal subregions of T2DM patients, with NODDI detecting abnormalities in approximately 70 % of the subregions, which were characterized by increased neurite density index (NDI), orientation dispersion index (ODI), and free water fraction (FWF) values, thus suggesting increased neurite density, disrupted orientation, and elevated free water content across most hippocampal subfields. DTI and NODDI analyses consistently identified the hippocampus-amygdala transition area (HATA) as a subregion that is particularly sensitive to microstructural changes in T2DM patients. Moreover, the NDI and FWF values were significantly correlated with cognitive performance, with the molecular layer and hippocampal tail exhibiting the strongest associations between microstructural indices and cognitive function. Conclusion: This study reveals microstructural alterations in the hippocampal subregions of T2DM patients, with particular changes being observed in the HATA region, moreover, this study highlights the advantages of the NODDI model in detecting these subtle changes, thereby providing important theoretical insights for future research.