Abstract：
OBJECTIVE: This retrospective work aims to evaluate the possible impact on intra- and inter-observer variability, contouring time, and contour accuracy of introducing a pelvis computed tomography (CT) auto-segmentation tool in radiotherapy planning workflow.
METHODS: Tests were carried out on five structures (bladder, rectum, pelvic lymph-nodes, and femoral heads) of six previously treated subjects, enrolling five radiation oncologists (ROs) to manually re-contour and edit auto-contours generated with a male pelvis CT atlas created with the commercial software MIM MAESTRO. The ROs first delineated manual contours (M). Then they modified the auto-contours, producing automatic-modified (AM) contours. The procedure was repeated to evaluate intra-observer variability, producing M1, M2, AM1, and AM2 contour sets (each comprising 5 structures × 6 test patients × 5 ROs = 150 contours), for a total of 600 contours. Potential time savings was evaluated by comparing contouring and editing times. Structure contours were compared to a reference standard by means of Dice similarity coefficient (DSC) and mean distance to agreement (MDA), to assess intra- and inter-observer variability. To exclude any automation bias, ROs evaluated both M and AM sets as \"clinically acceptable\" or \"to be corrected\" in a blind test.
RESULTS: Comparing AM to M sets, a significant reduction of both inter-observer variability (p < 0.001) and contouring time (-45% whole pelvis, p < 0.001) was obtained. Intra-observer variability reduction was significant only for bladder and femoral heads (p < 0.001). The statistical test showed no significant bias.
CONCLUSIONS: Our atlas-based workflow proved to be effective for clinical practice as it can improve contour reproducibility and generate time savings. Based on these findings, institutions are encouraged to implement their auto-segmentation method.
METHODS: Tests were carried out on five structures (bladder, rectum, pelvic lymph-nodes, and femoral heads) of six previously treated subjects, enrolling five radiation oncologists (ROs) to manually re-contour and edit auto-contours generated with a male pelvis CT atlas created with the commercial software MIM MAESTRO. The ROs first delineated manual contours (M). Then they modified the auto-contours, producing automatic-modified (AM) contours. The procedure was repeated to evaluate intra-observer variability, producing M1, M2, AM1, and AM2 contour sets (each comprising 5 structures × 6 test patients × 5 ROs = 150 contours), for a total of 600 contours. Potential time savings was evaluated by comparing contouring and editing times. Structure contours were compared to a reference standard by means of Dice similarity coefficient (DSC) and mean distance to agreement (MDA), to assess intra- and inter-observer variability. To exclude any automation bias, ROs evaluated both M and AM sets as \"clinically acceptable\" or \"to be corrected\" in a blind test.
RESULTS: Comparing AM to M sets, a significant reduction of both inter-observer variability (p < 0.001) and contouring time (-45% whole pelvis, p < 0.001) was obtained. Intra-observer variability reduction was significant only for bladder and femoral heads (p < 0.001). The statistical test showed no significant bias.
CONCLUSIONS: Our atlas-based workflow proved to be effective for clinical practice as it can improve contour reproducibility and generate time savings. Based on these findings, institutions are encouraged to implement their auto-segmentation method.
摘要：
目的：这项回顾性工作旨在评估对观察者内部和观察者之间变异性的可能影响，轮廓时间,以及在放射治疗计划工作流程中引入骨盆计算机断层扫描（CT）自动分割工具的轮廓精度。
方法：对五个结构进行了测试（膀胱，直肠,盆腔淋巴结,和股骨头）的六个先前接受过治疗的受试者，招募五名放射肿瘤学家（RO）手动重新轮廓并编辑使用商业软件MIMMAESTRO创建的男性骨盆CT图谱生成的自动轮廓。RO首先描绘手动轮廓(M)。然后他们修改了自动轮廓，生产自动修改（AM）轮廓。重复该程序以评估观察者内部的变异性，产生M1、M2、AM1和AM2轮廓集（每个包括5个结构×6个测试患者×5个ROs=150个轮廓），共600个轮廓。通过比较轮廓和编辑时间来评估潜在的时间节省。通过Dice相似性系数（DSC）和平均一致性距离（MDA）将结构轮廓与参考标准进行比较，评估观察者内部和观察者之间的变异性。为了排除任何自动化偏差，RO在盲测试中将M和AM集评估为“临床上可接受”或“待校正”。
结果：比较AM和M集，观察者间变异性（p<0.001）和轮廓时间（-45％整个骨盆，获得p<0.001)。仅膀胱和股骨头的观察者内变异性降低显着（p<0.001）。经统计学检验无显著偏差。
结论：我们基于图谱的工作流程被证明对临床实践有效，因为它可以提高轮廓可重复性并节省时间。基于这些发现,鼓励机构实施他们的自动分割方法。
方法：对五个结构进行了测试（膀胱，直肠,盆腔淋巴结,和股骨头）的六个先前接受过治疗的受试者，招募五名放射肿瘤学家（RO）手动重新轮廓并编辑使用商业软件MIMMAESTRO创建的男性骨盆CT图谱生成的自动轮廓。RO首先描绘手动轮廓(M)。然后他们修改了自动轮廓，生产自动修改（AM）轮廓。重复该程序以评估观察者内部的变异性，产生M1、M2、AM1和AM2轮廓集（每个包括5个结构×6个测试患者×5个ROs=150个轮廓），共600个轮廓。通过比较轮廓和编辑时间来评估潜在的时间节省。通过Dice相似性系数（DSC）和平均一致性距离（MDA）将结构轮廓与参考标准进行比较，评估观察者内部和观察者之间的变异性。为了排除任何自动化偏差，RO在盲测试中将M和AM集评估为“临床上可接受”或“待校正”。
结果：比较AM和M集，观察者间变异性（p<0.001）和轮廓时间（-45％整个骨盆，获得p<0.001)。仅膀胱和股骨头的观察者内变异性降低显着（p<0.001）。经统计学检验无显著偏差。
结论：我们基于图谱的工作流程被证明对临床实践有效，因为它可以提高轮廓可重复性并节省时间。基于这些发现,鼓励机构实施他们的自动分割方法。
