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基于图谱的自动勾画软件在勾画乳腺癌和直肠癌放疗靶区中的性能。

Performance of an atlas-based autosegmentation software for delineation of target volumes for radiotherapy of breast and anorectal cancer.

机构信息

Department of Radiation Oncology, University Medical Center Mannheim, University of Heidelberg, Germany.

出版信息

Radiother Oncol. 2012 Jan;102(1):68-73. doi: 10.1016/j.radonc.2011.08.043. Epub 2011 Sep 30.

Abstract

BACKGROUND AND PURPOSE

To validate atlas-based autosegmentation for contouring breast/anorectal targets.

METHODS AND MATERIALS

ABAS uses atlases with defined CTVs as template cases to automatically delineate target volumes in other patient CT-datasets. Results are compared with manually contoured CTVs of breast/anorectal cancer according to RTOG-guidelines. The impact of using specific atlases matched to individual patient geometry was evaluated. Results were quantified by analyzing Dice Similarity Coefficient (DSC), logit(DSC) and Percent Overlap (PO). DSC >0.700 and logit(DSC) >0.847 are acceptable. In addition a new algorithm (STAPLE) was evaluated.

RESULTS

ABAS produced good results for the CTV of breast/anorectal cancer targets. Delineation of inguinal lymphatic drainage, however, was insufficient. Results for breast CTV were (DSC: 0.86-0.91 ([0,1]), logit(DSC): 1.82-2.36 ([-∞,∞]), PO: 75.5-82.89%) and for anorectal CTVA (DSC: 0.79-0.85, logit(DSC): 1.40-1.77, PO: 68-73.67%).

CONCLUSIONS

ABAS produced satisfactory results for these clinical target volumes that are defined by more complex tissue interface geometry, thus streamlining and facilitating the radiotherapy workflow which is essential to face increasing demand and limited resources. STAPLE improved contouring outcome. Small target volumes not clearly defined are still to be delineated manually. Based on these results, ABAS has been clinically introduced for precontouring of CTVs/OARs.

摘要

背景与目的

为了验证基于图谱的自动勾画用于勾画乳房/肛门直肠靶区的准确性。

方法与材料

ABAS 使用具有定义CTV 的图谱作为模板病例,以自动勾画其他患者 CT 数据集的靶区。结果根据 RTOG 指南与手动勾画的乳腺癌/直肠癌 CTV 进行比较。评估了使用与个体患者几何形状匹配的特定图谱的影响。通过分析 Dice 相似系数(DSC)、logit(DSC)和重叠百分比(PO)来量化结果。DSC>0.700,logit(DSC)>0.847 为可接受。此外,还评估了一种新算法(STAPLE)。

结果

ABAS 为乳房/肛门直肠癌症靶区的 CTV 提供了良好的结果。然而,腹股沟淋巴引流的勾画不足。乳房 CTV 的结果为(DSC:0.86-0.91([0,1]),logit(DSC):1.82-2.36([-∞,∞]),PO:75.5-82.89%),肛门直肠 CTVA 的结果为(DSC:0.79-0.85,logit(DSC):1.40-1.77,PO:68-73.67%)。

结论

ABAS 为这些临床靶区提供了令人满意的结果,这些靶区具有更复杂的组织界面几何形状,从而简化和促进了放射治疗工作流程,这对于应对日益增长的需求和有限的资源至关重要。STAPLE 提高了勾画结果。仍然需要手动勾画小的靶区,这些靶区没有明确界定。基于这些结果,ABAS 已在临床中引入用于 CTV/OAR 的预勾画。

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