Prior studies have shown that atrophy in vulnerable cortical regions is associated with an increased risk of progression to clinical dementia. In this work, we utilize the longitudinal structural magnetic resonance imaging (MRI) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to investigate the relationship between the temporally changing spatial topography of cortical thickness and conversion from mild cognitive impairment to Alzheimer's disease (AD). We develop a novel Bayesian latent spatial model that employs the spatial information underlying the thickness effects across the cortical surface. The proposed method facilitates the development of imaging markers by reliably quantifying and mapping the regional vulnerability to AD progression across the cortical surface. Simulation results showed substantial gains in statistical power and estimation performance by accounting for the spatial structure of the association. Using MRI data from ADNI, we examined the topographic patterns of anatomic regions where cortical thinning is associated with an increased risk of developing AD.

中文翻译：

---

贝叶斯潜在空间模型，用于映射进展为阿尔茨海默氏病的皮层特征

先前的研究表明，脆弱的皮质区域萎缩与发展为痴呆症的风险增加有关。在这项工作中，我们利用阿尔茨海默氏病神经影像学倡议（ADNI）的纵向结构磁共振成像（MRI）数据来研究皮质厚度随时间变化的空间形貌与从轻度认知障碍到阿尔茨海默氏病（AD）的转化之间的关系。我们开发了一种新颖的贝叶斯潜在空间模型，该模型利用了整个皮质表面厚度效应背后的空间信息。所提出的方法通过可靠地量化和映射整个皮层表面AD进展的区域易损性，促进了成像标记的发展。仿真结果表明，通过考虑关联的空间结构，可以显着提高统计功效和估计性能。使用来自ADNI的MRI数据，我们检查了皮质变薄与AD发生风险增加相关的解剖区域的地形图。