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基于知识的前列腺容积调强弧形放疗计划工具的临床应用

Clinical implementation of a knowledge based planning tool for prostate VMAT.

作者信息

Powis Richard, Bird Andrew, Brennan Matthew, Hinks Susan, Newman Hannah, Reed Katie, Sage John, Webster Gareth

机构信息

Worcestershire Oncology Centre, Worcestershire Acute Hospitals NHS Trust, Worcester, UK.

Centre for Technology Enabled Health Care, Coventry University, Coventry, UK.

出版信息

Radiat Oncol. 2017 May 8;12(1):81. doi: 10.1186/s13014-017-0814-z.

Abstract

BACKGROUND

A knowledge based planning tool has been developed and implemented for prostate VMAT radiotherapy plans providing a target average rectum dose value based on previously achievable values for similar rectum/PTV overlap. The purpose of this planning tool is to highlight sub-optimal clinical plans and to improve plan quality and consistency.

METHODS

A historical cohort of 97 VMAT prostate plans was interrogated using a RayStation script and used to develop a local model for predicting optimum average rectum dose based on individual anatomy. A preliminary validation study was performed whereby historical plans identified as "optimal" and "sub-optimal" by the local model were replanned in a blinded study by four experienced planners and compared to the original clinical plan to assess whether any improvement in rectum dose was observed. The predictive model was then incorporated into a RayStation script and used as part of the clinical planning process. Planners were asked to use the script during planning to provide a patient specific prediction for optimum average rectum dose and to optimise the plan accordingly.

RESULTS

Plans identified as "sub-optimal" in the validation study observed a statistically significant improvement in average rectum dose compared to the clinical plan when replanned whereas plans that were identified as "optimal" observed no improvement when replanned. This provided confidence that the local model can identify plans that were suboptimal in terms of rectal sparing. Clinical implementation of the knowledge based planning tool reduced the population-averaged mean rectum dose by 5.6Gy. There was a small but statistically significant increase in total MU and femoral head dose and a reduction in conformity index. These did not affect the clinical acceptability of the plans and no significant changes to other plan quality metrics were observed.

CONCLUSIONS

The knowledge-based planning tool has enabled substantial reductions in population-averaged mean rectum dose for prostate VMAT patients. This suggests plans are improved when planners receive quantitative feedback on plan quality against historical data.

摘要

背景

已开发并实施了一种基于知识的计划工具,用于前列腺容积调强弧形放疗(VMAT)计划,该工具基于直肠/计划靶区(PTV)相似重叠情况下先前可实现的值,提供目标平均直肠剂量值。此计划工具的目的是突出显示次优临床计划,并提高计划质量和一致性。

方法

使用RayStation脚本对97例VMAT前列腺计划的历史队列进行分析,并用于开发基于个体解剖结构预测最佳平均直肠剂量的局部模型。进行了一项初步验证研究,在一项盲法研究中,由四位经验丰富的计划者对被局部模型识别为“最佳”和“次优”的历史计划重新进行计划,并与原始临床计划进行比较,以评估直肠剂量是否有任何改善。然后将预测模型纳入RayStation脚本,并用作临床计划过程的一部分。要求计划者在计划过程中使用该脚本,以提供患者特异性的最佳平均直肠剂量预测,并据此优化计划。

结果

在验证研究中被识别为“次优”的计划,重新计划时与临床计划相比,平均直肠剂量有统计学意义的改善,而被识别为“最佳”的计划重新计划时未观察到改善。这为局部模型能够识别在直肠保护方面次优的计划提供了信心。基于知识的计划工具的临床应用使总体平均直肠剂量降低了5.6Gy。总机器跳数(MU)和股骨头剂量有小幅但统计学意义的增加,适形指数降低。这些并未影响计划的临床可接受性,且未观察到其他计划质量指标有显著变化。

结论

基于知识的计划工具已使前列腺VMAT患者的总体平均直肠剂量大幅降低。这表明当计划者收到针对历史数据的计划质量定量反馈时,计划会得到改善。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4a41/5423022/24c5818bb4fc/13014_2017_814_Fig1_HTML.jpg

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