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Updated: Sep 10, 2025
Abbiategrasso Brain Bank Protocol for Collecting, Processing and Characterizing Aging Brains
Published on: June 3, 2020
Evaluation and interpretation of DTI-ALPS, a proposed surrogate marker for glymphatic clearance, in a large
Siddhartha Satpathi1, Robert I Reid1,2, Scott A Przybelski3
1Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
Background:
The diffusion tensor imaging along perivascular spaces index (DTI-ALPS), which measures diffusivity in the perivascular spaces along the medullary veins, has gained popularity and controversy as a surrogate marker of glymphatic clearance. The goal of this work is to automatically estimate DTI-ALPS in a large population-based sample, evaluate the correlates of the signal observed in the context of aging and dementia biomarkers, and evaluate its clinical usefulness.
Methods:
We identified 2715 participants aged 30 + years in the population-based Mayo Clinic Study of Aging with diffusion MRI. We calculated DTI-ALPS through a modified pipeline of previously published methods. We evaluated DTI-ALPS using different protocols and scanners and reported ICC for agreement. We examined the predictors of longitudinal DTI-ALPS with demographics (age, sex), vascular risk, clinical data (diagnosis, global cognition), and imaging markers (white matter hyperintensity (WMH), global amyloid load from PIB-PET, and temporal meta-ROI Tau-PET SUVR) in a subset of participants aged 50 + years using Pearson correlations, ANCOVA with adjustments for age and sex, and linear mixed effect models. We also compared the utility of DTI-ALPS with WMH for prediction of cognitive decline.
Results:
With modifications to the automated DTI-ALPS pipeline, consistent measurements can be made from data obtained with different protocols on different scanners. DTI-ALPS was negatively correlated with age, vascular risk, and WMH burden and was positively correlated with cognitive scores and higher in females. In the longitudinal models, WMH explained the greatest variability in decline of DTI-ALPS. The age and sex adjusted associations with AD biomarkers (amyloid and tau) were minimal. DTI-ALPS had a significant interaction with WMH on the rate of cognitive decline.
Conclusions:
DTI-ALPS can be reliably automated in large samples. The computed DTI-ALPS was associated with vascular dysfunction (vascular risk and WMH) and may provide additional complementary information about cognitive decline. The low associations with AD biomarkers suggest that DTI-ALPS may be a poor surrogate of AD.
