Xie Long, Wisse Laura E M, Das Sandhitsu R, Ittyerah Ranjit, Wang Jiancong, Wolk David A, Yushkevich Paul A
Penn Image Computing and Science Laboratory (PICSL), Department of Radiology, University of Pennsylvania, Philadelphia, USA.
Department of Neurology, University of Pennsylvania, Philadelphia, USA.
Shape Med Imaging (2018). 2018 Sep;11167:28-37. doi: 10.1007/978-3-030-04747-4_3. Epub 2018 Nov 23.
The perirhinal cortex (PRC) is a site of early neurofibrillary tangle (NFT) pathology in Alzheimer's disease (AD). Subtle morphological changes in the PRC have been reported in MRI studies of early AD, which has significance for clinical trials targeting preclinical AD. However, the PRC exhibits considerable anatomical variability with multiple described in the neuroanatomy literature. We hypothesize that different anatomical variants are associated with different patterns of AD-related effects in the PRC. Single-template approaches conventionally used for automated image-based brain morphometry are ill-equipped to test this hypothesis. This study uses graph-based groupwise registration and diffeomorphic landmark matching with geodesic shooting to build statistical shape models of discrete PRC variants and examine variant-specific effects of AD on PRC shape and thickness. Experimental results demonstrate that the statistical models recover the folding patterns of the known PRC variants and capture the expected shape variability within the population. By applying the proposed pipeline to a large dataset with subjects from different stages in the AD spectrum, we find 1) a pattern of cortical thinning consistent with the NFT pathology progression, 2) different patterns of the initial spatial distribution of cortical thinning between anatomical variants, and 3) an effect of AD on medial temporal lobe shape. As such, the proposed pipeline could have important utility in the early detection and monitoring of AD.
鼻周皮质（PRC）是阿尔茨海默病（AD）早期神经原纤维缠结（NFT）病理改变的发生部位。在早期AD的MRI研究中已报道了PRC的细微形态变化，这对于针对临床前AD的临床试验具有重要意义。然而，PRC在神经解剖学文献中描述的多种情况下表现出相当大的解剖变异性。我们假设不同的解剖变异与PRC中不同模式的AD相关效应有关。传统上用于基于图像的自动脑形态测量的单模板方法无法很好地检验这一假设。本研究使用基于图的组间配准和带有测地线射击的微分同胚地标匹配来构建离散PRC变异的统计形状模型，并研究AD对PRC形状和厚度的变异特异性影响。实验结果表明，统计模型恢复了已知PRC变异的折叠模式，并捕捉了群体内预期的形状变异性。通过将所提出的流程应用于一个包含来自AD谱系不同阶段受试者的大型数据集，我们发现：1）与NFT病理进展一致的皮质变薄模式；2）解剖变异之间皮质变薄初始空间分布的不同模式；3）AD对内侧颞叶形状的影响。因此，所提出的流程在AD的早期检测和监测中可能具有重要作用。
