Computational Imaging of Cerebral Small Vessel Disease and Vascular Brain Integrity in Aging and Neurodegeneration

Cerebral small vessel disease (CSVD) is a major contributor to cognitive decline in aging and dementia, yet its mechanisms, temporal dynamics, and interaction with neurodegenerative pathology remain insufficiently understood. Across a series of projects, we develop and apply advanced MRI-based methods to quantify vascular brain injury, focusing on white matter hyperintensities (WMH) and enlarged perivascular spaces (ePVS) as complementary markers of small vessel dysfunction.

Methodologically, we design and validate automated and semi-automated segmentation and quantification pipelines for WMH and ePVS, combining algorithmic development with rigorous validation against expert clinical ratings and neuroradiological assessments. These tools enable high-throughput, reproducible extraction of vascular imaging phenotypes in large, multicenter cohorts such as DZNE-DELCODE.

Substantively, we investigate how vascular imaging markers relate to age, vascular risk factors (e.g., hypertension), cerebrospinal fluid biomarkers of Alzheimer’s pathology, and longitudinal cognitive trajectories. By integrating vascular MRI features with neurodegenerative and molecular markers, our work aims to disentangle shared and independent pathways through which vascular brain injury contributes to cognitive impairment. Overall, this research establishes quantitative vascular imaging markers as critical components of multimodal disease models, advancing a more mechanistic and integrative understanding of brain aging and dementia risk.