Sagol Brain Institute, 26738Tel Aviv Sourasky Medical Center, Tel Aviv, Israel.
196686Department of Mathematics, Bar Ilan University, Ramat Gan, Israel.
Technol Cancer Res Treat. 2022 Jan-Dec;21:15330338221131387. doi: 10.1177/15330338221131387.
White-matter tract segmentation in patients with brain pathology can guide surgical planning and can be used for tissue integrity assessment. Recently, TractSeg was proposed for automatic tract segmentation in healthy subjects. The aim of this study was to assess the use of TractSeg for corticospinal-tract (CST) segmentation in a large cohort of patients with brain pathology and to evaluate its consistency in repeated measurements. A total of 649 diffusion-tensor-imaging scans were included, of them: 625 patients and 24 scans from 12 healthy controls (scanned twice for consistency assessment). Manual CST labeling was performed in all cases, and by 2 raters for the healthy subjects. Segmentation results were evaluated based on the Dice score. In order to evaluate consistency in repeated measurements, volume, Fractional Anisotropy (FA), and Mean Diffusivity (MD) values were extracted and correlated for the manual versus automatic methods. For the automatic CST segmentation Dice scores of 0.63 and 0.64 for the training and testing datasets were obtained. Higher consistency between measurements was detected for the automatic segmentation, with between measurements correlations of volume = 0.92/0.65, MD = 0.94/0.75 for the automatic versus manual segmentation. The TractSeg method enables automatic CST segmentation in patients with brain pathology. Superior measurements consistency was detected for the automatic in comparison to manual fiber segmentation, which indicates an advantage when using this method for clinical and longitudinal studies.
脑病理患者的白质束分割可指导手术规划,并可用于评估组织完整性。最近,提出了 TractSeg 用于健康受试者的自动束分割。本研究旨在评估 TractSeg 在大量脑病理患者中用于皮质脊髓束(CST)分割的用途,并评估其在重复测量中的一致性。共纳入 649 例弥散张量成像扫描,其中:625 例患者和 12 例健康对照者的 24 例扫描(为了评估一致性,扫描了两次)。所有病例均进行手动 CST 标记,健康受试者由 2 名评分者进行。基于 Dice 评分评估分割结果。为了评估重复测量的一致性,提取并比较了手动与自动方法的体积、分数各向异性(FA)和平均扩散系数(MD)值。对于自动 CST 分割,训练集和测试集的 Dice 评分为 0.63 和 0.64。与手动分割相比,自动分割的测量一致性更高,自动分割的体积相关性为 0.92/0.65,MD 相关性为 0.94/0.75。TractSeg 方法可实现脑病理患者的自动 CST 分割。与手动纤维分割相比,自动分割的测量一致性更高,这表明在临床和纵向研究中使用该方法具有优势。