Wang Xinzhuo, Miralbell Raymond, Fargier-Bochaton Odile, Bulling Shelley, Vallée Jean Paul, Dipasquale Giovanna
Division of Radiation Oncology, Tianjin Union Medicine Center, China.
Division of Radiation Oncology, Geneva University Hospital, Switzerland.
Technol Cancer Res Treat. 2020 Jan-Dec;19:1533033820920624. doi: 10.1177/1533033820920624.
Delineation of organs at risk is a time-consuming task. This study evaluates the benefits of using single-subject atlas-based automatic segmentation of organs at risk in patients with breast cancer treated in prone position, with 2 different criteria for choosing the atlas subject. Together with laterality (left/right), the criteria used were either (1) breast volume or (2) body mass index and breast cup size.
An atlas supporting different selection criteria for automatic segmentation was generated from contours drawn by a senior radiation oncologist (RO_A). Atlas organs at risk included heart, left anterior descending artery, and right coronary artery. Manual contours drawn by RO_A and automatic segmentation contours of organs at risk and breast clinical target volume were created for 27 nonatlas patients. A second radiation oncologist (RO_B) manually contoured (M_B) the breast clinical target volume and the heart. Contouring times were recorded and the reliability of the automatic segmentation was assessed in the context of 3-D planning.
Accounting for body mass index and breast cup size improved automatic segmentation results compared to breast volume-based sampling, especially for the heart (mean similarity indexes >0.9 for automatic segmentation organs at risk and clinical target volume after RO_A editing). Mean similarity indexes for the left anterior descending artery and the right coronary artery edited by RO_A expanded by 1 cm were ≥0.8. Using automatic segmentation reduced contouring time by 40%. For each parameter analyzed (eg, D), the difference in dose, averaged over all patients, between automatic segmentation structures edited by RO_A and the same structure manually drawn by RO_A was <1.5% of the prescribed dose. The mean heart dose was reliable for the unedited heart segmentation, and for right-sided treatments, automatic segmentation was adequate for treatment planning with 3-D conformal tangential fields.
Automatic segmentation for prone breast radiotherapy stratified by body mass index and breast cup size improved segmentation accuracy for the heart and coronary vessels compared to breast volume sampling. A significant reduction in contouring time can be achieved by using automatic segmentation.
勾画危及器官是一项耗时的任务。本研究评估了在俯卧位接受治疗的乳腺癌患者中，使用基于单病例图谱的自动分割危及器官的益处，以及选择图谱病例的2种不同标准。除了左右侧别外，使用的标准要么是（1）乳房体积，要么是（2）体重指数和胸罩罩杯尺寸。
由一位资深放射肿瘤学家（RO_A）绘制的轮廓生成了一个支持不同自动分割选择标准的图谱。图谱中的危及器官包括心脏、左前降支动脉和右冠状动脉。为27例非图谱病例创建了RO_A绘制的手动轮廓以及危及器官和乳房临床靶区体积的自动分割轮廓。另一位放射肿瘤学家（RO_B）手动勾勒（M_B）乳房临床靶区体积和心脏。记录轮廓绘制时间，并在三维计划的背景下评估自动分割的可靠性。
与基于乳房体积的采样相比，考虑体重指数和胸罩罩杯尺寸可改善自动分割结果，尤其是对于心脏（RO_A编辑后，危及器官和临床靶区体积的自动分割平均相似性指数>0.9）。RO_A编辑的左前降支动脉和右冠状动脉平均相似性指数在扩展1 cm后≥0.8。使用自动分割可将轮廓绘制时间减少40%。对于分析的每个参数（例如D），所有患者自动分割结构（经RO_A编辑）与RO_A手动绘制的相同结构之间的剂量差异平均小于处方剂量的1.5%。未编辑的心脏分割的平均心脏剂量可靠，对于右侧治疗，自动分割足以用于三维适形切线野的治疗计划。
与乳房体积采样相比，按体重指数和胸罩罩杯尺寸分层的俯卧位乳腺癌放疗自动分割提高了心脏和冠状动脉的分割准确性。使用自动分割可显著减少轮廓绘制时间。
