Keywords: Data Processing, Dementia, Texture analysis, Volume, Structural MRI images, Behavior variant frontotemporal dementia
Motivation: Current neuroimaging techniques for frontotemporal dementia (FTD) rely heavily on volumetric measurements, detecting changes only after substantial neurodegeneration. This study aims to identify sensitive imaging biomarkers for early microstructural changes and differentiate between disease stages
Goal(s): To evaluate whether texture-based MRI features can detect early abnormalities in FTD and distinguish between mild and moderate dementia.
Approach: We performed texture analysis on T1-weighted MRI scans from healthy controls, patients with mild, and those with moderate dementia, comparing volumetric and texture-based measures across groups.
Results: Texture features identified differences between disease stages that volumetric analysis could not, serving as more sensitive markers for FTD progression.
Impact: This study advances the understanding of frontotemporal dementia by demonstrating the utility of texture-based MRI features as sensitive biomarkers for early detection and differentiating between disease stages, potentially improving diagnosis accuracy and developing personalized treatment strategies.
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