Comparative analysis of PET and multiparametric MRI biomarkers in Alzheimer's disease continuum cohort

Abstract

Background: Non-invasive biomarkers are key to early Alzheimer's disease (AD) detection. Multiparametric MRI and advanced imaging offer promising, accessible tools for identifying AD-related changes, supporting timely diagnosis and intervention. Objective: To assess how accurately multiparametric MRI biomarkers identify AD using Aβ-PET imaging as the reference, and to evaluate whether MRI metrics in AD-related brain regions can distinguish between Aβ-positive and Aβ-negative subjects across the AD continuum. Methods: In this exploratory retrospective study, 44 subjects aged 50–80 years were classified based on their PET and MRI biomarkers following the NIA-AA 2024 framework. MRI metrics included selected regional brain volumes (T1-weighted), mean diffusivity and fractional anisotropy (DTI-MD, DTI-FA), quantitative susceptibility mapping (QSM), and T1rho imaging. These were compared with amyloid load, and diagnostic performance was assessed using area-under-the-curve (AUC) analysis. Results: 25 subjects were Aβ+ (AD continuum), while 19 were Aβ- (controls). Volumes of the hippocampus, thalamus, amygdala, cingulate, putamen, and corpus callosum and DTI-MD in the hippocampus, corpus callosum, cuneus, and cingulate showed optimal diagnostic performance (AUC ≥ 0.80), with hippocampal volume and hippocampal DTI-MD showing AUCs > 0.90, (both p < 0.05). Combining hippocampal volumetry and hippocampal DTI-MD (AUC = 0.95, p < 0.001) improved diagnostic accuracy by 2.1% compared to using either biomarker alone. LASSO logistic regression analysis showed that amyloid positivity was significantly associated with hippocampal volume (p < 0.001). Conclusions: Hippocampal volumetry and hippocampal DTI-MD may be superior and more sensitive imaging biomarkers for AD. Their combined use could improve diagnostic accuracy and enhance early AD detection.