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Fluorescence tomography in a murine model of Alzheimer's disease

机译:阿尔茨海默氏病小鼠模型中的荧光层析成像

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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 μm-resolution, digital, segmented mouse atlas. 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.
机译:鼠类阿尔茨海默氏病模型中淀粉样蛋白斑块的非侵入性分子成像将加速药物开发和基础阿尔茨海默氏症的研究。淀粉样蛋白斑块在大小和空间分布上不同于传统的荧光靶标,因此对生物标记物的发展和层析成像提出了独特的挑战。为了研究成像的可行性并建立生物标记标准,我们从分辨率为100μm的数字化分段鼠标图集中开发了一种数字鼠标头模型。与目前的阿尔茨海默氏病转基因小鼠模型相似,大脑的皮质区域充满了斑块的空间均匀分布,这些斑块的荧光特性与周围的大脑组织不同。使用不同的噬菌斑密度,检测几何形状和背景荧光,使用蒙特卡洛算法模拟荧光。我们的初步结果表明,屏蔽效应可能需要非线性重构算法,并且背景荧光会严重阻碍定量负荷估算。这里介绍的基于蒙特卡洛的方法为研究鼠类阿尔茨海默病模型中非侵入性成像的可行性和优化实验条件提供了一种有力的方法。

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