A study of diffusion MRI signatures linked to hypertensive arteriopathy and cerebral amyloid angiopathy in cerebral small vessel disease.
We developed a machine learning framework to quantify disease heterogeneity and progression in multiple system atrophy and Parkinson's disease using structural and diffusion MRI.
A book chapter reviewing AI applications in dementia research including imaging biomarkers, machine learning classification, and disease progression modeling.
We applied the THETA score to investigate cognitive resilience mechanisms in individuals with heterogeneous global tau burden.
We used diffusion imaging measures to distinguish between hypertensive arteriopathy and cerebral amyloid angiopathy contributions to small vessel disease.
THETA is a machine-learning tau PET measure that captures the spatial pattern of tau deposition across the brain in Alzheimer's disease.
We validated the THETA score using longitudinal PET data and histopathology, demonstrating its association with disease progression and neuropathological staging.
We examined vascular risk factors, gait measures, behavioral symptoms, and plasma biomarkers as indicators of vascular contributions to cognitive impairment and dementia.
We evaluated non-imaging measures for predicting variability in white matter changes relevant to vascular contributions to cognitive impairment and dementia.
We characterized white matter degeneration pathways associated with regional tau deposition in Alzheimer's disease.