Dolz J, Kirişli H A, Fechter T, Karnitzki S, Oehlke O, Nestle U, Vermandel M, Massoptier L
AQUILAB, Loos-les-Lille 59120, France and University Lille, Inserm, CHU Lille, U1189-ONCO-THAI-Image Assisted Laser Therapy for Oncology, Lille F-59000, France.
AQUILAB, Loos-les-Lille 59120, France.
Med Phys. 2016 May;43(5):2569. doi: 10.1118/1.4947484.
Accurate delineation of organs at risk (OARs) on computed tomography (CT) image is required for radiation treatment planning (RTP). Manual delineation of OARs being time consuming and prone to high interobserver variability, many (semi-) automatic methods have been proposed. However, most of them are specific to a particular OAR. Here, an interactive computer-assisted system able to segment various OARs required for thoracic radiation therapy is introduced.
Segmentation information (foreground and background seeds) is interactively added by the user in any of the three main orthogonal views of the CT volume and is subsequently propagated within the whole volume. The proposed method is based on the combination of watershed transformation and graph-cuts algorithm, which is used as a powerful optimization technique to minimize the energy function. The OARs considered for thoracic radiation therapy are the lungs, spinal cord, trachea, proximal bronchus tree, heart, and esophagus. The method was evaluated on multivendor CT datasets of 30 patients. Two radiation oncologists participated in the study and manual delineations from the original RTP were used as ground truth for evaluation.
Delineation of the OARs obtained with the minimally interactive approach was approved to be usable for RTP in nearly 90% of the cases, excluding the esophagus, which segmentation was mostly rejected, thus leading to a gain of time ranging from 50% to 80% in RTP. Considering exclusively accepted cases, overall OARs, a Dice similarity coefficient higher than 0.7 and a Hausdorff distance below 10 mm with respect to the ground truth were achieved. In addition, the interobserver analysis did not highlight any statistically significant difference, at the exception of the segmentation of the heart, in terms of Hausdorff distance and volume difference.
An interactive, accurate, fast, and easy-to-use computer-assisted system able to segment various OARs required for thoracic radiation therapy has been presented and clinically evaluated. The introduction of the proposed system in clinical routine may offer valuable new option to radiation oncologists in performing RTP.
放射治疗计划（RTP）需要在计算机断层扫描（CT）图像上准确勾画危及器官（OARs）。由于手动勾画OARs既耗时又容易出现较高的观察者间变异性，因此人们提出了许多（半）自动方法。然而，其中大多数方法都特定于某一特定的OAR。在此，介绍一种能够分割胸部放射治疗所需各种OARs的交互式计算机辅助系统。
用户在CT容积的三个主要正交视图中的任何一个视图中交互式添加分割信息（前景和背景种子），随后在整个容积中传播。所提出的方法基于分水岭变换和图割算法的组合，图割算法用作强大的优化技术以最小化能量函数。胸部放射治疗所考虑的OARs包括肺、脊髓、气管、近端支气管树、心脏和食管。该方法在30例患者的多厂家CT数据集中进行了评估。两名放射肿瘤学家参与了该研究，并将原始RTP中的手动勾画用作评估的金标准。
采用最少交互方法获得的OARs勾画在近90%的病例中被批准可用于RTP，但食管除外，其分割大多被拒绝，从而使RTP中的时间节省了50%至80%。仅考虑被接受的病例，总体OARs与金标准相比，Dice相似系数高于0.7，豪斯多夫距离低于10 mm。此外，观察者间分析未发现除心脏分割外，在豪斯多夫距离和体积差异方面有任何统计学上的显著差异。
已经提出并临床评估了一种交互式、准确、快速且易于使用的计算机辅助系统，该系统能够分割胸部放射治疗所需的各种OARs。在临床常规中引入所提出的系统可能为放射肿瘤学家进行RTP提供有价值的新选择。
