Li Zhixi, Peck Kyung K, Brennan Nicole P, Jenabi Mehrnaz, Hsu Meier, Zhang Zhigang, Holodny Andrei I, Young Robert J
Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, USA.
Department of Radiology, Memorial Sloan-Kettering Cancer Center, New York, USA ; Department of Medical Physics, Memorial Sloan-Kettering Cancer Center, New York, USA.
J Biomed Sci Eng. 2013 Feb;6(2):192-200. doi: 10.4236/jbise.2013.62023.
The purpose of this study was to compare the deterministic and probabilistic tracking methods of diffusion tensor white matter fiber tractography in patients with brain tumors.
We identified 29 patients with left brain tumors <2 cm from the arcuate fasciculus who underwent pre-operative language fMRI and DTI. The arcuate fasciculus was reconstructed using a deterministic Fiber Assignment by Continuous Tracking (FACT) algorithm and a probabilistic method based on an extended Monte Carlo Random Walk algorithm. Tracking was controlled using two ROIs corresponding to Broca's and Wernicke's areas. Tracts in tumoraffected hemispheres were examined for extension between Broca's and Wernicke's areas, anterior-posterior length and volume, and compared with the normal contralateral tracts.
Probabilistic tracts displayed more complete anterior extension to Broca's area than did FACT tracts on the tumor-affected and normal sides (p < 0.0001). The median length ratio for tumor: normal sides was greater for probabilistic tracts than FACT tracts (p < 0.0001). The median tract volume ratio for tumor: normal sides was also greater for probabilistic tracts than FACT tracts (p = 0.01).
Probabilistic tractography reconstructs the arcuate fasciculus more completely and performs better through areas of tumor and/or edema. The FACT algorithm tends to underestimate the anterior-most fibers of the arcuate fasciculus, which are crossed by primary motor fibers.
本研究旨在比较脑肿瘤患者中扩散张量白质纤维束成像的确定性和概率性追踪方法。
我们纳入了29例左侧脑肿瘤距弓状束<2 cm的患者,这些患者均接受了术前语言功能磁共振成像(fMRI)和扩散张量成像(DTI)。使用连续追踪纤维分配(FACT)确定性算法和基于扩展蒙特卡罗随机游走算法的概率性方法重建弓状束。使用对应于布洛卡区和韦尼克区的两个感兴趣区(ROI)来控制追踪。检查肿瘤累及半球的纤维束在布洛卡区和韦尼克区之间的延伸、前后长度和体积,并与对侧正常纤维束进行比较。
在肿瘤累及侧和正常侧,概率性纤维束向布洛卡区的前向延伸比FACT纤维束更完整(p<0.0001)。概率性纤维束的肿瘤侧与正常侧长度中位数比值大于FACT纤维束(p<0.0001)。概率性纤维束的肿瘤侧与正常侧纤维束体积中位数比值也大于FACT纤维束(p = 0.01)。
概率性纤维束成像能更完整地重建弓状束,并且在穿过肿瘤和/或水肿区域时表现更佳。FACT算法往往会低估弓状束最前部的纤维,而这些纤维会被初级运动纤维交叉穿过。