PROJECT SUMMARY/ABSTRACT Alzheimer’s disease (AD) is among the top ten causes of death in the United States, but the only disease among them that has no treatment. Despite numerous trials to test potential therapeutics, it is hypothesized that most fail because the neurodegenerative process is too far progressed when a clinical diagnosis can be made. Therefore, it is imperative to identify patients at risk for developing disease so that treatment can be administered before cognitive decline. One of the first known signs of AD is amyloid-b (Ab) deposition in the extracellular space. The amyloid cascade hypothesis suggests that Ab is the primary cause of down- stream pathologic changes, such as neuroinflammation, which ultimately leads to neurodegeneration. This proposal seeks to examine the potential efficacy of newly developed quantitative neuroimaging techniques as a means to early detection of amyloid deposition and neuroinflammation in preclinical models of Alz- heimer’s disease. These techniques will be also used to evaluate the amyloid cascade hypothesis in order to better elucidate etiopathogenesis of disease. Specifically, this proposal will use multi-compartment diffu- sion weighted imaging (MC-DWI) to determine the sensitivity and specificity of various MC-DWI techniques to the molecular and cellular changes that are known to occur in the extra-neurite space in AD for (1) earlier diagnosis and (2) subsequent evaluation of disease progression and therapeutic monitoring in the develop- ment of new treatment paradigms. Efforts will also be directed towards evaluating the potential of ActiveAx, a four-compartment MC-DWI model, and its ability to sensitively and specifically track changes in Ab and microglial neuroinflammation in a murine model of AD before and after microglial ablation. This work will not only highlight the potential application of ActiveAx in disease monitoring but also investigate the potential therapeutic efficacy of microglial inhibition in AD. The proposed studies represent a significant advance in clinical care and research in AD with improvements across clinical diagnostic accuracy, patient risk stratifi- cation, therapeutic monitoring and understanding of Alzheimer’s disease etiology.