Evaluating the robustness of DTI-ALPS in clinical context: a meta-analytic parallel on Alzheimer's and Parkinson's diseases.

In recent years, the glymphatic system has received increasing attention due to its possible implications in biological mechanisms associated with neurodegeneration. In the field of human brain mapping, this led to the development of diffusion tensor image analysis along the perivascular space (DTI-ALPS) index. While this index has been repeatedly used to investigate possible differences between neurodegenerative disorders and healthy controls, a comprehensive evaluation of its stability across multiple measurements and different disorders is still missing. In this study, we perform a Bayesian meta-analysis aiming to assess the consistency of the DTI-ALPS results previously reported for 12 studies on Parkinson's disease and 11 studies on Alzheimer's disease. We also evaluated if the measured value of the DTI-ALPS index can quantitatively inform the diagnostic process, allowing disambiguation between these two disorders. Our results, expressed in terms of Bayes' Factor values, confirmed that the DTI-ALPS index is consistent in measuring the different functioning of the glymphatic system between healthy subjects and patients for both Parkinson's disease (Log10(BF10) = 30) and Alzheimer's disease (Log10(BF10) = 10). Moreover, we showed that the DTI-ALPS can be used to compare these two disorders directly, therefore providing a first proof of concept supporting the reliability of taking into consideration this neuroimaging measurement in the diagnostic process. Our study underscores the potential of the DTI-ALPS index in advancing our understanding of neurodegenerative pathologies and enhancing clinical diagnostics.