Senjem Matthew L, Gunter Jeffrey L, Shiung Maria M, Petersen Ronald C, Jack Clifford R
Department of Radiology, Mayo Clinic and Foundation, Rochester, MN 55905, USA.
Neuroimage. 2005 Jun;26(2):600-8. doi: 10.1016/j.neuroimage.2005.02.005. Epub 2005 Apr 12.
Voxel-based morphometry (VBM) is a popular method for probing inter-group differences in brain morphology. Variation in the detailed implementation of the algorithm, however, will affect the apparent results of VBM analyses and in turn the inferences drawn about the anatomic expression of specific disease states. We qualitatively assessed group comparisons of 43 normal elderly control subjects and 51 patients with probable Alzheimer's disease, using five different VBM variations. Based on the known pathologic expression of the disease, we evaluated the biological plausibility of each. The use of a custom template and custom tissue class prior probability images (priors) produced inter-group comparison maps with greater biological plausibility than the use of the Montreal Neurological Institute (MNI) template and priors. We present a method for initializing the normalization to a custom template, and conclude that, when incorporated into the VBM processing chain, it yields the most biologically plausible inter-group differences of the five methods presented.
基于体素的形态测量学（VBM）是一种用于探究脑形态学组间差异的常用方法。然而，该算法详细实现过程中的变化会影响VBM分析的表面结果，进而影响对特定疾病状态解剖学表现的推断。我们使用五种不同的VBM变体，对43名正常老年对照受试者和51名可能患有阿尔茨海默病的患者进行了定性组间比较。基于该疾病已知的病理表现，我们评估了每种方法的生物学合理性。与使用蒙特利尔神经病学研究所（MNI）模板和先验概率图像相比，使用自定义模板和自定义组织类别先验概率图像（先验）生成的组间比较图具有更高的生物学合理性。我们提出了一种将归一化初始化为自定义模板的方法，并得出结论，当将其纳入VBM处理链时，它能产生本文所介绍的五种方法中生物学合理性最高的组间差异。
