An Automated Workflow to Improve Efficiency in Radiation Therapy Treatment Planning by Prioritizing Organs at Risk.
An Automated Workflow to Improve Efficiency in Radiation Therapy Treatment Planning by Prioritizing Organs at Risk.
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DOI：
10.1016/j.adro.2020.06.012
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发表时间：
2020-11
影响因子：
2.3
通讯作者：
Siebers JV
中科院分区：
文献类型：
--
作者：
Aliotta E;Nourzadeh H;Choi W;Leandro Alves VG;Siebers JV
人工勾画危险器官(OAR)是一项费时费力的工作。自动勾画(AD)可以减少对MD的需求，但由于当前的算法不完善，通常仍使用手动审查和修改。认识到许多桨离重要的剂量水平足够远，不会构成现实的风险，我们假设一些桨可以排除在MD和手动审查之外，没有临床效果。这项研究的目的是开发一种自动识别这些桨的方法，并实现更有效的工作流程，在不降低临床质量的情况下合并AD。仅使用处方和目标体积信息，为n=10名头颈部癌症患者生成了初步剂量图估计。临床OAR目标的保守估计是使用具有空间扩展缓冲的AD结构来计算的，以考虑潜在的描述不确定性。估计剂量指标低于临床耐受性的OAR被认为是低优先级的，并被排除在MD和/或手动审查之外。然后使用高优先级MD桨和低优先级AD桨对最终计划进行优化，并与使用所有MD桨生成的参考计划进行比较。多个不同的空间缓冲区被用来适应不同的潜在划定不确定性。使用拟议的方法，201个桨中的67个被确定为低优先级，这使得需要人工划定/审查的结构减少了33%。使用低优先级AD桨优化的计划在没有审查或修改的情况下满足了当使用所有MD桨时达到的所有规划目标，表明临床等效性。使用估计的剂量分布来确定桨的优先顺序可以在不影响临床相关剂量学的情况下大幅减少所需的MD和复查。
Manual delineation (MD) of organs at risk (OAR) is time and labor intensive. Auto-delineation (AD) can reduce the need for MD, but because current algorithms are imperfect, manual review and modification is still typically used. Recognizing that many OARs are sufficiently far from important dose levels that they do not pose a realistic risk, we hypothesize that some OARs can be excluded from MD and manual review with no clinical effect. The purpose of this study was to develop a method that automatically identifies these OARs and enables more efficient workflows that incorporate AD without degrading clinical quality. Preliminary dose map estimates were generated for n = 10 patients with head and neck cancers using only prescription and target-volume information. Conservative estimates of clinical OAR objectives were computed using AD structures with spatial expansion buffers to account for potential delineation uncertainties. OARs with estimated dose metrics below clinical tolerances were deemed low priority and excluded from MD and/or manual review. Final plans were then optimized using high-priority MD OARs and low-priority AD OARs and compared with reference plans generated using all MD OARs. Multiple different spatial buffers were used to accommodate different potential delineation uncertainties. Sixty-seven out of 201 total OARs were identified as low-priority using the proposed methodology, which permitted a 33% reduction in structures requiring manual delineation/review. Plans optimized using low-priority AD OARs without review or modification met all planning objectives that were met when all MD OARs were used, indicating clinical equivalence. Prioritizing OARs using estimated dose distributions allowed a substantial reduction in required MD and review without affecting clinically relevant dosimetry.
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影响因子：
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