Clerx Lies, Gronenschild Ed H B M, Echavarri Carmen, Verhey Frans, Aalten Pauline, Jacobs Heidi I L
Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Centrum Limburg, Maastricht University Medical Center, P.O. Box 616, 6200 MD Maastricht, The Netherlands.
Curr Alzheimer Res. 2015;12(4):358-67. doi: 10.2174/1567205012666150324174813.
Alzheimer's disease-related pathology results in tremendous structural and functional changes in the brain. These morphological changes might lead to a less precise performance of automated brain segmentation techniques in AD-patients, which in turn could possibly lead to false allocations of gray matter, white matter or cerebrospinal fluid. FreeSurfer has been shown to operate as an accurate and reliable instrument to measure cortical thickness and volume of neuroanatomical structures. Considering the principal role of FreeSurfer in the imaging field of AD, the present study aims to investigate the robustness of FreeSurfer to capture morphological changes in the brain against varying processing variables in comparison to manual measurements (the gold standard). T1-weighted MRI scan data were used pertaining to a sample of 53 individuals (18 healthy participants, 18 patients with mild cognitive impairment, and 18 patients with mild AD). Data were analyzed with different FreeSurfer versions (v4.3.1, v4.5.0, v5.0.0, v5.1.0), on a custom-built cluster (LINUX) and a Macintosh (UNIX) workstation. Group differences across versions and workstations were most consistent for both the hippocampus and posterior cingulate, regions known to be affected in the earliest stages of the disease. The results showed that later versions of FreeSurfer were more sensitive to identify group differences and corresponded best with the results of gold standard manual volumetric methods. In conclusion, later versions of FreeSurfer were more accurate than earlier versions, especially in medial temporal and posterior parietal regions. This development is very promising for future applications of FreeSurfer in research studies and encourages the future role of FreeSurfer output as a candidate marker in clinical practice.
阿尔茨海默病相关病理导致大脑发生巨大的结构和功能变化。这些形态学改变可能会使针对阿尔茨海默病患者的自动脑分割技术的表现不够精确,进而可能导致灰质、白质或脑脊液的错误分配。FreeSurfer已被证明是一种准确可靠的工具,可用于测量神经解剖结构的皮质厚度和体积。考虑到FreeSurfer在阿尔茨海默病成像领域的主要作用,本研究旨在调查与手动测量(金标准)相比,FreeSurfer在面对不同处理变量时捕捉大脑形态学变化的稳健性。使用了53名个体(18名健康参与者、18名轻度认知障碍患者和18名轻度阿尔茨海默病患者)样本的T1加权磁共振成像扫描数据。在定制集群(LINUX)和Macintosh(UNIX)工作站上,使用不同版本的FreeSurfer(v4.3.1、v4.5.0、v5.0.0、v5.1.0)对数据进行分析。对于海马体和后扣带回这两个已知在疾病早期阶段会受到影响的区域,不同版本和工作站之间的组间差异最为一致。结果表明,FreeSurfer的较新版本在识别组间差异方面更敏感,并且与金标准手动体积测量方法的结果最为吻合。总之,FreeSurfer的较新版本比早期版本更准确,尤其是在内侧颞叶和顶叶后部区域。这一进展对于FreeSurfer在未来研究中的应用非常有前景,并鼓励将FreeSurfer输出作为临床实践中的候选标志物发挥未来作用。