A Novel Network Diffusion Model for Alzheimer's And Other Neurodegenerative Disea

描述（由申请人提供）：阿尔茨海默病（AD）和其他痴呆症影响着全球约2500万人，对老年患者的身心健康造成了巨大的损害。阿尔茨海默病治疗缺乏进展的一个主要原因是对其病因和进展机制缺乏根本的了解。尽管在使用复杂的神经解剖学算法检测和量化阿尔茨海默病的疾病进展方面取得了令人印象深刻的进展，但很少有系统级模型可以解释阿尔茨海默病中观察到的神经退行性变模式。我们现在提出了一个新的萎缩模型，作为一个假设的大脑网络的扩散过程。该模型以数学方式编码了基本的理解，即传播遵循纤维路径，以与局部萎缩梯度成正比的向外速率从更多的萎缩区域到较少的萎缩区域，类似于具有温度梯度的网络中的传热。令人惊讶的是，该模型暗示了阿尔茨海默病和其他退行性疾病的萎缩模式。最后，我们建议使用我们的模型来预测任何患者的未来萎缩模式，使用他们的基线神经影像学数据。

DESCRIPTION (provided by applicant): Alzheimer's Disease (AD) and other dementias affect approximately 25 million people worldwide, taking a huge toll on the physical and psychological well being of elderly patients. A major reason for lack of progress in AD treatment is a fundamental lack of understanding regarding its cause and mechanism of progression. Despite impressive progress in detecting and quantifying disease progression in AD using sophisticated neuroanatomic algorithms, there are very few system-level models which can explain the observed patterns of neurodegeneration in AD. We now propose a novel model of atrophy as a diffusion process on a hypothesized brain network. The model mathematically encodes the basic understanding that propagation follows fiber pathways, going from more to less atrophied regions at an outward rate proportional to the local atrophy gradient, in a manner akin to heat transfer in a network with temperature gradients. Surprisingly, the model implies atrophy patterns in AD and other degenerative diseases. Finally, we propose to use our model to predict the future atrophic patterns for any patient using their baseline neuroimaging data.