ABSTRACT Mixed pathologies of cerebral small vessel disease (SVD) and Alzheimer’s disease (AD) represent the most common cause of dementia in the elderly population. The presence of SVD exacerbates the progression of AD. Multiple sex-specific AD risk factors contribute to a heightened SVD-related AD risk in women. With its potent estrogenic, antioxidant, and anti-inflammatory effects, Equol has beneficial effects on cerebral blood vessels. Therefore, leveraging the ongoing NIA-funded multi-site "Arterial Stiffness, Cognition, and Equol (ACE)” trial, the proposed 7T-ACE study aims to characterize sex differences in cerebrovascular aging and associated neurochemical substrates (Aim 1) and to determine the role of Equol in improving cerebrovascular health (Aim 2). The proposed 7T-ACE study takes advantage of ultra-high field 7T vascular and molecular imaging to assess cerebrovascular aging and associated neurochemical changes. Our 7T vascular imaging characterizes blood-brain barrier (BBB) function, small vessel morphology, white matter microstructure, and white matter hyperintensities (WMH). Specifically, with advances in 7T time-of-flight MR angiography (TOF- MRA) and susceptibility weighted imaging (SWI) and with our newly developed and validated VesselMapper and BrainVein methods, we are able to characterize the morphological features of small arteries and small veins. Our 7T molecular MR imaging using the state-of-the-art whole-brain magnetic resonance spectroscopic imaging (MRSI) measures brain metabolites associated with cerebrovascular aging, including N- acetylaspartate (NAA) and glutamate (Glu) (markers of neuronal integrity) and myo-inositol (mI) (a marker of glial cells and inflammation). Compared to WMH (a conventional marker of SVD), these novel morphological and molecular markers reflect specific, early, mild, and reversible damage and thus are particularly important in developing therapeutic targets for disease prevention and treatment. Recently, brain age (BA) models have been developed using machine learning algorithms to predict age from T1-weighted MR images. These models primarily fit gray matter atrophy patterns (referred to as GM-BA) and lack discrimination regarding white matter, where vascular changes are prominent. Using these GM-BA models, women are consistently found to be 1.5-3.5 years younger than men. This obviously does not align with the epidemiologic findings that women are disproportionately affected by AD, suggesting that GM-BA models alone are not sufficient to characterize brain aging. Therefore, besides GM-BA models, a white matter brain age (WM-BA) model trained with WM microstructural features is proposed in this study to characterize cerebral white matter aging process. The proposed 7T-ACE study will characterize effects of sex and Equol treatment on cerebrovascular aging and associated neurochemical profiles. The proposed study will also identify primary factors contributing to these effects. Understanding ...