Department of Radiation Oncology, Advanced Centre for Treatment Research and Education in Cancer (ACTREC), Tata Memorial Centre, Navi Mumbai, Maharashtra 410210, India.
Department of Radiation Oncology, Advanced Centre for Treatment Research and Education in Cancer (ACTREC), Tata Memorial Centre, Navi Mumbai, Maharashtra 410210, India.
Phys Med. 2018 Mar;47:1-8. doi: 10.1016/j.ejmp.2018.01.013. Epub 2018 Feb 9.
To report the commissioning and validation of deformable image registration(DIR) software for adaptive contouring.
DIR (SmartAdapt®v13.6) was validated using two methods namely contour propagation accuracy and landmark tracking, using physical phantoms and clinical images of various disease sites. Five in-house made phantoms with various known deformations and a set of 10 virtual phantoms were used. Displacement in lateral, anterio-posterior (AP) and superior-inferior (SI) direction were evaluated for various organs and compared with the ground truth. Four clinical sites namely, brain (n = 5), HN (n = 9), cervix (n = 18) and prostate (n = 23) were used. Organs were manually delineated by a radiation oncologist, compared with the deformable image registration (DIR) generated contours. 3D slicer v4.5.0.1 was used to analyze Dice Similarity Co-efficient (DSC), shift in centre of mass (COM) and Hausdorff distances Hf.
Mean (SD) DSC, Hf (mm), Hf (mm) and COM of all the phantoms 1-5 were 0.84 (0.2) mm, 5.1 (7.4) mm, 1.6 (2.2) mm, and 1.6 (0.2) mm respectively. Phantom-5 had the largest deformation as compared to phantoms 1-4, and hence had suboptimal indices. The virtual phantom resulted in consistent results for all the ROIs investigated. Contours propagated for brain patients were better with a high DSC score (0.91 (0.04)) as compared to other sites (HN: 0.84, prostate: 0.81 and cervix 0.77). A similar trend was seen in other indices too. The accuracy of propagated contours is limited for complex deformations that include large volume and shape change of bladder and rectum respectively. Visual validation of the propagated contours is recommended for clinical implementation.
The DIR algorithm was commissioned and validated for adaptive contouring.
报告用于自适应勾画的形变图像配准（DIR）软件的调试和验证。
使用两种方法对 DIR（SmartAdapt®v13.6）进行验证，即轮廓传播准确性和标志点跟踪，使用物理体模和来自不同病变部位的临床图像。使用了五个具有不同已知变形的内部制作的体模和一组 10 个虚拟体模。评估了各种器官在侧向、前后（AP）和上下（SI）方向上的位移，并与真实情况进行了比较。使用了四个临床部位，分别是脑（n=5）、头颈部（HN，n=9）、宫颈（n=18）和前列腺（n=23）。由放射肿瘤学家手动勾画器官轮廓，与形变图像配准（DIR）生成的轮廓进行比较。使用 3D slicer v4.5.0.1 分析 Dice 相似系数（DSC）、质心（COM）位移和 Hausdorff 距离 Hf。
所有体模 1-5 的平均（标准差）DSC、Hf（mm）、Hf（mm）和 COM 分别为 0.84（0.2）mm、5.1（7.4）mm、1.6（2.2）mm 和 1.6（0.2）mm。与体模 1-4 相比，体模 5 的变形最大，因此指标不理想。对于所有研究的 ROI，虚拟体模都产生了一致的结果。与其他部位（HN：0.84、前列腺：0.81 和宫颈：0.77）相比，脑患者的轮廓传播效果更好，具有较高的 DSC 评分（0.91（0.04））。其他指标也呈现出类似的趋势。对于包括膀胱和直肠分别的大体积和形状变化在内的复杂变形，传播轮廓的准确性受到限制。建议对传播轮廓进行视觉验证，以便于临床实施。
已为自适应勾画调试和验证了 DIR 算法。
Zotero 插件