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Differences in topological progression profile among neurodegenerative diseases from imaging data

机译:成像数据中神经退行性疾病中拓扑进展型的差异

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摘要

The spatial distribution of atrophy in neurodegenerative diseases suggests that brain connectivity mediates disease propagation. Different descriptors of the connectivity graph potentially relate to different underlying mechanisms of propagation. Previous approaches for evaluating the influence of connectivity on neurodegeneration consider each descriptor in isolation and match predictions against late-stage atrophy patterns. We introduce the notion of a topological profile — a characteristic combination of topological descriptors that best describes the propagation of pathology in a particular disease. By drawing on recent advances in disease progression modeling, we estimate topological profiles from the full course of pathology accumulation, at both cohort and individual levels. Experimental results comparing topological profiles for Alzheimer’s disease, multiple sclerosis and normal ageing show that topological profiles explain the observed data better than single descriptors. Within each condition, most individual profiles cluster around the cohort-level profile, and individuals whose profiles align more closely with other cohort-level profiles show features of that cohort. The cohort-level profiles suggest new insights into the biological mechanisms underlying pathology propagation in each disease.
机译:神经变性疾病中萎缩的空间分布表明脑连接介导疾病繁殖。连接图的不同描述符可能与不同的传播潜在机制有关。以前用于评估连接对神经变性的影响的方法认为每个描述符的隔离和匹配后期萎缩模式的预测。我们介绍了拓扑配置文件的概念 - 一种最能描述特定疾病在特定疾病中病理繁殖的拓扑描述符的特征组合。通过绘制疾病进展建模的最近进展,我们在群组和个体层面都估计了从整个病理累积过程中的拓扑谱。实验结果比较阿尔茨海默病,多发性硬化和正常老化的拓扑曲线表明,拓扑型材比单个描述符更好地解释了观察到的数据。在每个条件下,围绕群组级配置文件的大多数个人配置文件集群,以及与其他队列级别配置文件更密切地对齐的个人群体显示该队列的功能。群组级概况表明了对每种疾病中病理繁殖的生物机制的新见解。

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