# Image-based cerebrovascular network snythesis(iCNS) to model Alzheimer's Disease > **NIH NIH R01** · UNIVERSITY OF ILLINOIS AT CHICAGO · 2023 · $751,339 ## Abstract Significant resources on age-related neurodegeneration are directed toward animal research in the assumption that results will inform our understanding of parallel processes in human. Yet, no reliable method exists to accurately translate cerebral blood flow or metabolic data from animal to human. For lack of rigorous mathematical methods for cerebral metabolic parameters between species, translation of valuable research data from mouse to human remains guesswork. There is a need for a predictive computational framework that quantifies cerebral blood flow and metabolism in normal and diseased human brain states. Our long term goal is to quantify fundamental physiological processes of aging and Alzheimer’s disease (AD), so that their effects can be slowed or even partially reversed. The objective is to expand the utility of MRI analysis by magnifying the detectability of age-related microcirculatory changes in humans with a mechanistic mathematical framework. It is our hypothesis that age and AD related changes in the microcirculation also generate macroscopic perturbations of hemodynamic and/or oxygen perfusion states that will be detectable with advanced MRI techniques, when guided by rigorous brain simulations over all relevant length scales. The rationale is that critical physiological metrics for dysfunction in aged brains (=aging biomarkers) will be exposed by systematic exploration and simulation of fundamental hemodynamic and metabolic processes. The central hypothesis will be tested by pursuing three specific aims: Aim 1) Assess the predictive value of mechanistic modeling by simulating the link between capillary stalling, vascular tracer transit properties, and tissue oxygen delivery, and validate predictions using advanced microscopic imaging in mouse. We determine the effects of aging and AD in aged rodent brains. Aim 2) Develop mechanistic multiscale model for predicting the impact of cerebral perfusion on oxygen metabolism in the human cortex under normal and pathological conditions. Anatomically detailed mechanistic models of cerebral circulation in human will predict the effect of structural and functional changes in AD on oxygen extraction in the human brain with MRI. Aim 3) Assess the predictive value of mechanistic multiscale modeling to quantify microvascular properties across the human brain cortex in health and disease using advanced MRI. To validate the mechanistic translation from mouse to human, we will measure age-related metabolic functions in cohorts of aged and Alzheimer patients. We identify hemodynamic and metabolic metrics (=biomarkers) that correlate with cognitive decline This contribution is significant because it will predict how changes in vascular morphometry and metabolism lead to neurological decline. It will identify biomarkers visible in noninvasive diagnostic imaging in humans that signal age-related deterioration before symptoms develop. The mechanistic framework relating data acquired in mouse to hu... ## Key facts - **NIH application ID:** 10561232 - **Project number:** 1R01AG079894-01 - **Recipient organization:** UNIVERSITY OF ILLINOIS AT CHICAGO - **Principal Investigator:** ANDREAS A LINNINGER - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2023 - **Award amount:** $751,339 - **Award type:** 1 - **Project period:** 2022-12-15 → 2027-11-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10561232 ## Citation > US National Institutes of Health, RePORTER application 10561232, Image-based cerebrovascular network snythesis(iCNS) to model Alzheimer's Disease (1R01AG079894-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10561232. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*