Fluorescence tomography in a murine model of Alzheimer's disease

Abstract

Noninvasive molecular imaging of amyloid plaques in murine Alzheimer's disease models would accelerate drug development and basic Alzheimer's research. Amyloid plaques differ from traditional fluorescent targets in size and spatial distribution and therefore present a unique challenge for biomarker development and tomography. To study imaging feasibility and establish biomarker criteria, we developed a digital mouse head model from a 100 &mgr;m-resolution, digital, segmented mouse atlas¹. The cortical region of the brain was filled with a spatially uniform distribution of plaques that had different fluorescent properties from the surrounding brain tissue, similar to current transgenic mouse models of Alzheimer's disease. Fluorescence was simulated with a Monte Carlo algorithm using different plaque densities, detection geometries, and background fluorescence. Our preliminary results demonstrated that shielding effects might require nonlinear reconstruction algorithms and that background fluorescence would seriously hinder quantitative burden estimation. The Monte Carlo based approach presented here offers a powerful way to study the feasibility of non-invasive imaging in murine Alzheimer's models and to optimize experimental conditions.