Microstructural grey matter alterations in patients with behavioural variant frontotemporal dementia.

Behavioural variant frontotemporal dementia is characterized by progressive changes to personality and behaviour, yet early detection and disease staging remain challenging. Current clinical neuroimaging relies on visual assessment of atrophy patterns, which may overlook subtle structural changes. While volumetric analysis has improved the ability to detect neurodegeneration and track disease progression, it may lack the sensitivity to identify microstructural alterations that precede frank atrophy. Texture analysis, a quantitative approach that evaluates the spatial regularity of grey matter density, has demonstrated promise in detecting early microstructural changes in Alzheimer's disease and distinguishing frontotemporal dementia subtypes. However, its potential as a biomarker for early behavioural variant frontotemporal dementia detection and disease staging remain unexplored. This study evaluates the potential of autocorrelation-based texture features as biomarkers for detecting early-stage behavioural variant frontotemporal dementia and tracking disease progression, comparing their sensitivity and specificity to regional brain volume. We analysed structural MRI scans from behavioural variant frontotemporal dementia patients with mild (