Shi Xiutao, Diwanji Tejan, Mooney Karen E, Lin Jolinta, Feigenberg Steven, D'Souza Warren D, Mistry Nilesh N
Department of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland 21201.
Med Phys. 2014 May;41(5):052304. doi: 10.1118/1.4870978.
Accurate determination of tumor position is crucial for successful application of motion compensated radiotherapy in lung cancer patients. This study tested the performance of an automated template matching algorithm in tracking the tumor position on cine-MR images by examining the tracking error and further comparing the tracking error to the interoperator variability of three human reviewers.
Cine-MR images of 12 lung cancer patients were analyzed. Tumor positions were determined both automatically with template matching and manually by a radiation oncologist and two additional reviewers trained by the radiation oncologist. Performance of the automated template matching was compared against the ground truth established by the radiation oncologist. Additionally, the tracking error of template matching, defined as the difference in the tumor positions determined with template matching and the ground truth, was investigated and compared to the interoperator variability for all patients in the anterior-posterior (AP) and superior-inferior (SI) directions, respectively.
The median tracking error for ten out of the 12 patients studied in both the AP and SI directions was less than 1 pixel (= 1.95 mm). Furthermore, the median tracking error for seven patients in the AP direction and nine patients in the SI direction was less than half a pixel (= 0.975 mm). The median tracking error was positively correlated with the tumor motion magnitude in both the AP (R = 0.55, p = 0.06) and SI (R = 0.67, p = 0.02) directions. Also, a strong correlation was observed between tracking error and interoperator variability (y = 0.26 + 1.25x, R = 0.84, p < 0.001) with the latter larger.
Results from this study indicate that the performance of template matching is comparable with or better than that of manual tumor localization. This study serves as preliminary investigations towards developing online motion tracking techniques for hybrid MRI-Linac systems. Accuracy of template matching makes it a suitable candidate to replace the labor intensive manual tumor localization for obtaining the ground truth when testing other motion management techniques.
准确确定肿瘤位置对于肺癌患者成功应用运动补偿放疗至关重要。本研究通过检查跟踪误差，并进一步将跟踪误差与三位人类阅片者的阅片者间变异性进行比较，测试了一种自动模板匹配算法在电影磁共振（cine-MR）图像上跟踪肿瘤位置的性能。
分析了12例肺癌患者的cine-MR图像。肿瘤位置通过模板匹配自动确定，同时由放射肿瘤学家以及另外两名由放射肿瘤学家培训的阅片者手动确定。将自动模板匹配的性能与放射肿瘤学家确定的真实情况进行比较。此外，研究了模板匹配的跟踪误差，其定义为通过模板匹配确定的肿瘤位置与真实情况之间的差异，并分别在前后（AP）和上下（SI）方向上与所有患者的阅片者间变异性进行比较。
在研究的12例患者中，有10例患者在AP和SI方向上的中位跟踪误差均小于1像素（=1.95毫米）。此外，7例患者在AP方向上的中位跟踪误差和9例患者在SI方向上的中位跟踪误差小于半个像素（=0.975毫米）。中位跟踪误差在AP（R = 0.55，p = 0.06）和SI（R = 0.67，p = 0.02）方向上均与肿瘤运动幅度呈正相关。此外，观察到跟踪误差与阅片者间变异性之间存在强相关性（y = 0.26 + 1.25x，R = 0.84，p < 0.001），后者更大。
本研究结果表明，模板匹配的性能与手动肿瘤定位相当或更好。本研究作为开发用于混合MRI-直线加速器系统的在线运动跟踪技术的初步研究。模板匹配的准确性使其成为在测试其他运动管理技术时替代劳动强度大的手动肿瘤定位以获得真实情况的合适候选方法。
