Li X, Zhang Y Y, Shi Y H, Zhou L H, Zhen X
Department of Biomedical Engineering, Southern Medical University, Guangzhou, Guangdong, China.
Department of Radiotherapy Oncology, the First Hospital of Jilin University, Changchun, Jilin, China.
Technol Health Care. 2016 Apr 29;24 Suppl 2:S747-55. doi: 10.3233/THC-161204.
Deformable image registration (DIR) is a critical technic in adaptive radiotherapy (ART) to propagate contours between planning computerized tomography (CT) images and treatment CT/Cone-beam CT (CBCT) image to account for organ deformation for treatment re-planning. To validate the ability and accuracy of DIR algorithms in organ at risk (OAR) contours mapping, seven intensity-based DIR strategies are tested on the planning CT and weekly CBCT images from six Head & Neck cancer patients who underwent a 6 ∼ 7 weeks intensity-modulated radiation therapy (IMRT). Three similarity metrics, i.e. the Dice similarity coefficient (DSC), the percentage error (PE) and the Hausdorff distance (HD), are employed to measure the agreement between the propagated contours and the physician delineated ground truths. It is found that the performance of all the evaluated DIR algorithms declines as the treatment proceeds. No statistically significant performance difference is observed between different DIR algorithms (p> 0.05), except for the double force demons (DFD) which yields the worst result in terms of DSC and PE. For the metric HD, all the DIR algorithms behaved unsatisfactorily with no statistically significant performance difference (p= 0.273). These findings suggested that special care should be taken when utilizing the intensity-based DIR algorithms involved in this study to deform OAR contours between CT and CBCT, especially for those organs with low contrast.
可变形图像配准（DIR）是自适应放射治疗（ART）中的一项关键技术，用于在计划计算机断层扫描（CT）图像和治疗CT/锥形束CT（CBCT）图像之间传播轮廓，以考虑器官变形进行治疗重新计划。为了验证DIR算法在危及器官（OAR）轮廓映射中的能力和准确性，对6例接受了6至7周调强放射治疗（IMRT）的头颈癌患者的计划CT图像和每周CBCT图像测试了7种基于强度的DIR策略。采用三种相似性度量，即骰子相似系数（DSC）、百分比误差（PE）和豪斯多夫距离（HD），来测量传播轮廓与医生勾勒的地面真值之间的一致性。结果发现，随着治疗的进行，所有评估的DIR算法的性能都会下降。除了双力恶魔算法（DFD）在DSC和PE方面产生最差结果外，不同的DIR算法之间未观察到统计学上显著的性能差异（p>0.05）。对于HD度量，所有DIR算法的表现都不尽人意，且无统计学上显著的性能差异（p = 0.273）。这些发现表明，在利用本研究中涉及的基于强度的DIR算法在CT和CBCT之间使OAR轮廓变形时，应特别小心，尤其是对于那些对比度低的器官。
