Automated Quantification of Glymphatic Flow Using the DTI-ALPS Index in Native Principal Axis Imaging Space: Implications for Neurocardiac Coupling, Cerebrovascular Hemodynamics, and Cardiometabolic Risk Stratification

Abstract The glymphatic system plays a pivotal role in cerebral waste clearance, and its dysfunction is implicated in neurodegenerative and cardiovascular pathologies. This study introduces an automated method for quantifying glymphatic flow using the diffusion tensor imaging analysis along the perivascular space (DTI-ALPS) index in native principal axis imaging space, addressing limitations in traditional approaches that rely on standardized templates prone to registration errors. We evaluated this technique in a cohort of 150 participants, including healthy controls and individuals with cardiometabolic risk factors such as hypertension, diabetes, and obesity. Results demonstrate that automated DTI-ALPS quantification reveals significant associations between reduced glymphatic efficiency and impaired neurocardiac coupling, altered cerebrovascular hemodynamics, and elevated cardiometabolic risk scores. Multivariate analyses indicate that glymphatic dysfunction mediates up to 40% of the variance in cognitive decline and vascular events in at-risk populations. These findings underscore the potential of this automated index as a non-invasive biomarker for early risk stratification and therapeutic monitoring in neurocardiac and cardiometabolic disorders. Keywords: Glymphatic system; DTI-ALPS index; Neurocardiac coupling; Cerebrovascular hemodynamics; Cardiometabolic risk; Diffusion tensor imaging; Principal axis space.