Computational anatomy and neuropsychiatric disease: probabilistic assessment of variation and statistical inference of group difference, hemispheric asymmetry, and time-dependent change
Computational anatomy and neuropsychiatric disease: probabilistic assessment of variation and statistical inference of group difference, hemispheric asymmetry, and time-dependent change
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DOI：
10.1016/j.neuroimage.2004.07.025
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发表时间：
2004-01-01
期刊：
影响因子：
5.7
通讯作者：
Miller, MI
中科院分区：
文献类型：
--
作者：
Csernansky, JG;Wang, L;Miller, MI
本文综述了计算解剖学（CA）的三个组成部分：（I）大变形映射的计算，即对于两个解剖结构的任何给定坐标系表示，计算从一个到另一个的微分同胚变换；（ii）解剖结构之间解剖变异的经验概率定律的计算；以及（iii）关于神经精神疾病状态的推断的构建。CA利用从大变形映射中获得的时空向量场信息来评估解剖变异性，并促进对神经精神障碍患者脑结构异常的检测和量化。神经解剖结构分为两种类型：皮质下结构——由单个表面包围的灰质（GM）体积——和皮质套结构——位于白质（WM）和脑脊液（CSF）之间的大脑皮质套的解剖学上不同的部分。由于这两种结构的几何形状存在根本差异，针对皮质下结构的研究开发了基于图像的大变形高维脑映射（HDBM - LD）和大变形微分同胚度量匹配（LDDMM），针对皮质套结构的研究开发了标记皮质套距离映射（LCMDM）。使用CA对神经精神障碍的研究通常需要对每组受试者数量相对较少的假设组间差异进行检验。提高检验此类假设能力的方法包括量化单个结构形状的方法、相关结构形状之间的关系（例如，不对称性）以及形状随时间的变化。介绍了将这些方法应用于精神分裂症患者和极轻度至轻度阿尔茨海默病（AD）患者研究的有前景的初步研究。（C）2004 Elsevier Inc.保留所有权利。
Three components of computational anatomy (CA) are reviewed in this paper: (I) the computation of large-deformation maps, that is, for any given coordinate system representations of two anatomies, computing the diffemnorphic transformation from one to the other; (ii) the computation of empirical probability laws of anatomical variation between anatomies; and (iii) the construction of inferences regarding neuropsychiatric disease states. CA utilizes spatial-temporal vector field information obtained from large-deformation maps to assess anatomical variabilities and facilitate the detection and quantification of abnormalities of brain structure in subjects with neuropsychiatric disorders. Neuroanatomical structures are divided into two types: subcortical structures-gray matter (GM) volumes enclosed by a single surface-and cortical mantle structuresanatomically distinct portions of the cerebral cortical mantle layered between the white matter (WM) and cerebrospinal fluid (CSF). Because of fundamental differences in the geometry of these two types of structures, image-based large-deformation high-dimensional brain mapping (HDBM-LD) and large-deformation diffeomorphic metric matching (LDDMM) were developed for the study of subcortical structures and labeled cortical mantle distance mapping (LCMDM) was developed for the study of cortical mantle structures. Studies of neuropsychiatric disorders using CA usually require the testing of hypothesized group differences with relatively small numbers of subjects per group. Approaches that increase the power for testing such hypotheses include methods to quantify the shapes of individual structures, relationships between the shapes of related structures (e.g., asymmetry), and changes of shapes over time. Promising preliminary studies employing these approaches to studies of subjects with schizophrenia and very mild to mild Alzheimer's disease (AD) are presented. (C) 2004 Elsevier Inc. All rights reserved.