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Clinical validation of atlas-based auto-segmentation of pelvic volumes and normal tissue in rectal tumors using auto-segmentation computed system

机译:基于自动分割计算机系统基于图集的直肠肿瘤盆腔体积和正常组织自动分割的临床验证

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Purpose. To evaluate in two different settings-clinical practice and education/training-the reliability, time efficiency and the ideal sequence of an atlas-based auto-segmentation system in pelvic delineation of locally advanced rectal cancer. Methods. Fourteen consecutive patients were selected between October and December 2011. The images of four were used as an atlas and 10 used for validation. Two independent operators participated: a Delineator to contour and a Reviewer to perform an independent check (IC). The CTV, pelvic subsites and organs at risk were contoured in four different sequences. These included A: manual; B: auto-segmentation; C: auto-segmentation + manual revision; and D: manual + auto-segmentation + manual revision. Contouring was performed by the Delineator using the same planning CT. All of them underwent an IC by a Reviewer. The time required for all the contours were recorded and overlapping evaluation was assessed using a Dice coefficient. Results. In the clinical practice setting there have been 13 minutes time saved between sequences A versus sequences B (from 38 to 25 minutes, p = 0.002), a mean Dice coefficient in favor of sequences A for CTV and all subsites (p = 0.0195). In the educational/training setting there have been 35.2 minutes time saved between sequences C and D 8 (from 73.1 min to 37.9 min, p = 0.002). Conclusion. The preliminary data suggest that the use of an atlas-based auto-contouring system may help improve efficiencies in contouring in the clinical practice setting and could have a tutorial role in the educational/training setting.
机译:目的。要在两种不同的环境中进行评估(临床实践和教育/培训),以图集为基础的自动分割系统在局部晚期直肠癌的骨盆描绘中的可靠性,时间效率和理想顺序。方法。在2011年10月至2011年12月之间连续选择了14位患者。其中四幅图像用作图集,十幅图像用于验证。两名独立的操作员参加了会议:轮廓描绘者和审阅者执行独立检查(IC)。 CTV,骨盆亚位点和高风险器官按四个不同的顺序绘制轮廓。这些包括:A:手册; B:自动分段; C:自动细分+手动修订;和D:手动+自动细分+手动修订。轮廓线由Delineator使用相同的计划CT进行。所有这些人都经过了审阅者的IC。记录所有轮廓所需的时间,并使用Dice系数评估重叠评估。结果。在临床实践中,序列A与序列B之间节省了13分钟的时间(从38到25分钟,p = 0.002),对于CTV和所有子位点,支持D序列的平均Dice系数(p = 0.0195)。在教育/培训设置中,序列C和D 8之间节省了35.2分钟的时间(从73.1分钟到37.9分钟,p = 0.002)。结论。初步数据表明,使用基于图集的自动轮廓系统可以帮助提高临床实践环境中轮廓的效率,并且可以在教育/培训环境中起到指导作用。

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