Zimmerman-Moreno Gali, Ben Bashat Dafna, Artzi Moran, Nefussy Beatrice, Drory Vivian, Aizenstein Orna, Greenspan Hayit
Department of Biomedical Engineering, Tel Aviv University, 69978, Israel.
The Functional Brain Center, the Wohl Institute for Advanced Imaging, Tel Aviv Sourasky Medical Center, 6 Weizmann St. Tel Aviv 64239, Israel.
Hum Brain Mapp. 2016 Feb;37(2):477-90. doi: 10.1002/hbm.23043. Epub 2015 Oct 31.
We present a novel method for fiber-based comparison of diffusion tensor imaging (DTI) scans of groups of subjects. The method entails initial preprocessing and fiber reconstruction by tractography of each brain in its native coordinate system. Several diffusion parameters are sampled along each fiber and used in subsequent comparisons. A spatial correspondence between subjects is established based on geometric similarity between fibers in a template set (several choices for template are explored), and fibers in all other subjects. Diffusion parameters between groups are compared statistically for each template fiber. Results are presented at single fiber resolution. As an initial exploratory step in neurological population studies this method points to the locations affected by the pathology of interest, without requiring a hypothesis. It does not make any grouping assumptions on the fibers and no manual intervention is needed. The framework was applied here to 18 healthy subjects and 23 amyotrophic lateral sclerosis (ALS) patients. The results are compatible with previous findings and with the tract based spatial statistics (TBSS) method. Hum Brain Mapp 37:477-490, 2016. © 2015 Wiley Periodicals, Inc.
我们提出了一种基于纤维的新方法,用于对多组受试者的扩散张量成像(DTI)扫描进行比较。该方法需要在每个大脑的原始坐标系中进行初始预处理和通过纤维束成像进行纤维重建。沿着每条纤维对几个扩散参数进行采样,并用于后续比较。基于模板集中的纤维(探索了几种模板选择)与所有其他受试者的纤维之间的几何相似性,在受试者之间建立空间对应关系。针对每个模板纤维对组间的扩散参数进行统计学比较。结果以单纤维分辨率呈现。作为神经人群研究中的初步探索步骤,该方法指出了受感兴趣的病理学影响的位置,而无需假设。它不对纤维进行任何分组假设,也无需人工干预。该框架在此应用于18名健康受试者和23名肌萎缩侧索硬化症(ALS)患者。结果与先前的发现以及基于纤维束的空间统计学(TBSS)方法一致。《人类大脑图谱》37:477 - 490,2016年。© 2015威利期刊公司。