Reed Valerie K, Woodward Wendy A, Zhang Lifei, Strom Eric A, Perkins George H, Tereffe Welela, Oh Julia L, Yu T Kuan, Bedrosian Isabelle, Whitman Gary J, Buchholz Thomas A, Dong Lei
Department of Radiation Oncology, University of Texas M. D. Anderson Cancer Center, Houston, TX 77030, USA.
Int J Radiat Oncol Biol Phys. 2009 Apr 1;73(5):1493-500. doi: 10.1016/j.ijrobp.2008.07.001. Epub 2008 Sep 17.
To compare interobserver variations in delineating the whole breast for treatment planning using two contouring methods.
Autosegmented contours were generated by a deformable image registration-based breast segmentation method (DEF-SEG) by mapping the whole breast clinical target volume (CTVwb) from a template case to a new patient case. Eight breast radiation oncologists modified the autosegmented contours as necessary to achieve a clinically appropriate CTVwb and then recontoured the same case from scratch for comparison. The times to complete each approach, as well as the interobserver variations, were analyzed. The template case was also mapped to 10 breast cancer patients with a body mass index of 19.1-35.9 kg/m(2). The three-dimensional surface-to-surface distances and volume overlapping analyses were computed to quantify contour variations.
The median time to edit the DEF-SEG-generated CTVwb was 12.9 min (range, 3.4-35.9) compared with 18.6 min (range, 8.9-45.2) to contour the CTVwb from scratch (30% faster, p = 0.028). The mean surface-to-surface distance was noticeably reduced from 1.6 mm among the contours generated from scratch to 1.0 mm using the DEF-SEG method (p = 0.047). The deformed contours in 10 patients achieved 94% volume overlap before correction and required editing of 5% (range, 1-10%) of the contoured volume.
Significant interobserver variations suggested a lack of consensus regarding the CTVwb, even among breast cancer specialists. Using the DEF-SEG method produced more consistent results and required less time. The DEF-SEG method can be successfully applied to patients with different body mass indexes.
比较使用两种轮廓勾画方法在勾画全乳以进行治疗计划时观察者间的差异。
通过基于可变形图像配准的乳房分割方法(DEF-SEG)生成自动分割轮廓,即将全乳临床靶区(CTVwb)从模板病例映射到新患者病例。八位乳腺放疗肿瘤学家根据需要修改自动分割轮廓以获得临床上合适的CTVwb,然后从零开始重新勾画同一病例以进行比较。分析完成每种方法的时间以及观察者间的差异。模板病例还被映射到10名体重指数为19.1 - 35.9 kg/m²的乳腺癌患者。计算三维表面到表面距离和体积重叠分析以量化轮廓差异。
编辑DEF-SEG生成的CTVwb的中位时间为12.9分钟(范围3.4 - 35.9分钟),而从零开始勾画CTVwb的时间为18.6分钟(范围8.9 - 45.2分钟)(快30%,p = 0.028)。平均表面到表面距离从从零开始生成的轮廓间的1.6毫米显著减少到使用DEF-SEG方法时的1.0毫米(p = 0.047)。10名患者中变形后的轮廓在校正前实现了94%的体积重叠,并且需要编辑轮廓体积的5%(范围1 - 10%)。
显著的观察者间差异表明即使在乳腺癌专家中对于CTVwb也缺乏共识。使用DEF-SEG方法产生了更一致的结果且所需时间更少。DEF-SEG方法可以成功应用于不同体重指数的患者。