Clinical implementation of automated treatment planning for whole-brain radiotherapy.
Clinical implementation of automated treatment planning for whole-brain radiotherapy.
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DOI：
10.1002/acm2.13350
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发表时间：
2021-09
影响因子：
2.1
通讯作者：
Wen Z
中科院分区：
文献类型：
--
作者：
Han EY;Cardenas CE;Nguyen C;Hancock D;Xiao Y;Mumme R;Court LE;Rhee DJ;Netherton TJ;Li J;Yeboa DN;Wang C;Briere TM;Balter P;Martel MK;Wen Z
该研究的目的是开发和临床部署一种自动化的、基于深度学习的全脑放疗（WBRT）治疗计划方法。我们收集了520例接受WBRT的患者的CT图像和放射治疗计划，以自动定义射束孔径。这些患者被分为训练集（n = 312）、交叉验证集（n = 104）和测试集（n = 104），用于训练和评估深度学习模型。DeepLabV 3+架构经过训练，可使用数字重建X线照片（DRR）自动定义横向相对射野上的射束孔径。对于射束孔径评价，在临床展开前使用测试集完成第一次定量分析，在临床展开后90天进行第二次定量分析。比较了临床使用和预测射野之间前下缘的平均表面距离和Hausdorff距离。通过脑、筛板和透镜的各种剂量-体积直方图指标评价临床使用的计划和深度学习生成的计划。第1次定量分析显示，视野前下缘的平均表面距离和Hausdorff距离分别为7.1 mm（±3.8 mm）和11.2 mm（±5.2 mm）。回顾性剂量测定比较显示，自动生成计划的脑部剂量覆盖率（D99%、D95%、D1%）分别为29.7、30.3和32.5戈伊，与临床使用的计划相比，两种晶状体的平均剂量降低了19.0%。临床展开后，第二次定量分析显示，预测和临床使用射野之间的平均表面距离和Hausdorff距离分别为2.6 mm（±3.2 mm）和4.5 mm（±5.6 mm）。总之，在我们的诊所中实施了针对WBRT的自动化患者特定治疗计划解决方案。预测的射野与临床使用的射野一致，预测的计划在剂量学上具有可比性。
The purpose of the study was to develop and clinically deploy an automated, deep learning‐based approach to treatment planning for whole‐brain radiotherapy (WBRT). We collected CT images and radiotherapy treatment plans to automate a beam aperture definition from 520 patients who received WBRT. These patients were split into training (n = 312), cross‐validation (n = 104), and test (n = 104) sets which were used to train and evaluate a deep learning model. The DeepLabV3+ architecture was trained to automatically define the beam apertures on lateral‐opposed fields using digitally reconstructed radiographs (DRRs). For the beam aperture evaluation, 1st quantitative analysis was completed using a test set before clinical deployment and 2nd quantitative analysis was conducted 90 days after clinical deployment. The mean surface distance and the Hausdorff distances were compared in the anterior‐inferior edge between the clinically used and the predicted fields. Clinically used plans and deep‐learning generated plans were evaluated by various dose–volume histogram metrics of brain, cribriform plate, and lens. The 1st quantitative analysis showed that the average mean surface distance and Hausdorff distance were 7.1 mm (±3.8 mm) and 11.2 mm (±5.2 mm), respectively, in the anterior–inferior edge of the field. The retrospective dosimetric comparison showed that brain dose coverage (D99%, D95%, D1%) of the automatically generated plans was 29.7, 30.3, and 32.5 Gy, respectively, and the average dose of both lenses was up to 19.0% lower when compared to the clinically used plans. Following the clinical deployment, the 2nd quantitative analysis showed that the average mean surface distance and Hausdorff distance between the predicted and clinically used fields were 2.6 mm (±3.2 mm) and 4.5 mm (±5.6 mm), respectively. In conclusion, the automated patient‐specific treatment planning solution for WBRT was implemented in our clinic. The predicted fields appeared consistent with clinically used fields and the predicted plans were dosimetrically comparable.
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影响因子：
3.3
作者：
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影响因子：
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