Movement Control and Neuroplasticity Research Group, Department of Kinesiology KU Leuven, Belgium ; CNRS, INCIA, UMR 5287, University of Bordeaux Talence, France.
Department of Electrical Engineering - ESAT - PSI & iMinds - Future Health Department KU Leuven, Belgium.
Front Aging Neurosci. 2014 Jun 23;6:124. doi: 10.3389/fnagi.2014.00124. eCollection 2014.
Healthy ageing coincides with a progressive decline of brain gray matter (GM) ultimately affecting the entire brain. For a long time, manual delineation-based volumetry within predefined regions of interest (ROI) has been the gold standard for assessing such degeneration. Voxel-Based Morphometry (VBM) offers an automated alternative approach that, however, relies critically on the segmentation and spatial normalization of a large collection of images from different subjects. This can be achieved via different algorithms, with SPM5/SPM8, DARTEL of SPM8 and FSL tools (FAST, FNIRT) being three of the most frequently used. We complemented these voxel based measurements with a ROI based approach, whereby the ROIs are defined by transforms of an atlas (containing different tissue probability maps as well as predefined anatomic labels) to the individual subject images in order to obtain volumetric information at the level of the whole brain or within separate ROIs. Comparing GM decline between 21 young subjects (mean age 23) and 18 elderly (mean age 66) revealed that volumetric measurements differed significantly between methods. The unified segmentation/normalization of SPM5/SPM8 revealed the largest age-related differences and DARTEL the smallest, with FSL being more similar to the DARTEL approach. Method specific differences were substantial after segmentation and most pronounced for the cortical structures in close vicinity to major sulci and fissures. Our findings suggest that algorithms that provide only limited degrees of freedom for local deformations (such as the unified segmentation and normalization of SPM5/SPM8) tend to overestimate between-group differences in VBM results when compared to methods providing more flexible warping. This difference seems to be most pronounced if the anatomy of one of the groups deviates from custom templates, a finding that is of particular importance when results are compared across studies using different VBM methods.
健康老龄化与大脑灰质（GM）的逐渐减少相吻合，最终影响整个大脑。长期以来，基于手动勾画的感兴趣区域（ROI）体积测量一直是评估这种退行性变的金标准。体素基形态测量学（VBM）提供了一种自动替代方法，然而，它严重依赖于对来自不同受试者的大量图像进行分割和空间归一化。这可以通过不同的算法来实现，其中 SPM5/SPM8、SPM8 的 DARTEL 和 FSL 工具（FAST、FNIRT）是最常用的三种算法。我们通过基于 ROI 的方法补充了这些基于体素的测量，其中 ROI 通过对包含不同组织概率图以及预定义解剖标签的图谱的转换来定义，以便在整个大脑或单独的 ROI 水平上获得体积信息。比较 21 名年轻受试者（平均年龄 23 岁）和 18 名老年受试者（平均年龄 66 岁）之间的 GM 下降，发现不同方法之间的体积测量存在显著差异。SPM5/SPM8 的统一分割/归一化方法显示出最大的年龄相关性差异，DARTEL 方法显示出最小的差异，FSL 方法与 DARTEL 方法更为相似。分割后，方法特异性差异较大，与主要脑沟和脑裂附近的皮质结构最为明显。我们的研究结果表明，对于局部变形提供有限自由度的算法（如 SPM5/SPM8 的统一分割和归一化）与提供更灵活变形的方法相比，在 VBM 结果中往往会高估组间差异。如果其中一个组的解剖结构偏离自定义模板，这种差异最为明显，这一发现对于使用不同 VBM 方法进行研究结果比较时尤为重要。
