Evaluation of the efficacy of automated machine learning enhanced planning system and a comparative analysis with manual planning system.

IF 1.3
Anand Jadhav, Ajinkya Gupte, Sachin Rasal, Omkar Awate, Prasad Raj Dandekar
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引用次数: 0

Abstract

Introduction: The aim of radiotherapy treatment is to deliver a high dose of radiation precisely to the target volume while minimizing exposure to the surrounding organs at risk. This approach maximizes the likelihood of tumor control and reduces the risk of adverse side effects. Treatment planning systems (TPS) are crucial in achieving this goal. However, the manual planning process is time-consuming, resource-intensive, and subject to variability based on the skill and experience of individual planners. Automated planning aims to reduce inter-plan variation and planning duration while maintaining or improving plan quality. Varian Medical Systems introduced the Ethos platform, an automated planning and delivery system utilizing an Intelligent Optimization Engine (IOE). This study evaluates the efficacy of automated plan generation using the Varian Ethos IOE for prostate cancer treatment, compared with plans generated using the Eclipse TPS with the anisotropic analytical algorithm (AAA).

Materials and methods: Fifteen retrospective patients diagnosed with prostate cancer, treated with a dose of 60 Gy in 20 fractions to the prostate, were included. Treatment approved Eclipse plans were recalculated and reoptimized with the same objective function, and then exported to the Ethos TPS. The Ethos TPS generates a total of five plans-7-, 9-, and 12-field IMRT plans, and 2- and 3-arc VMAT plans, respectively, maintaining fixed beam geometry. Two additional plans were also generated on Ethos: one maintaining identical parameters from Eclipse for calculation purposes, and a second involving re-optimization. The primary objective was to assess the number of prespecified dose constraints met, while the secondary objective was to compare dosimetric parameters, such as target coverage, dose conformity, dose homogeneity, and OAR sparing between the Ethos and Eclipse plans.

Results: There was no statistically significant difference between the Eclipse plan and the Ethos-generated plans in meeting the prespecified criteria. For PTV coverage, mean values for V95 > 95% were achieved across all plans. The mean values for V105 < 5% were well below the threshold, indicating minimal hotspots. The conformity index (CI) was close to 1, and the homogeneity index (HI) was close to 0 across all plans, indicating good dose distribution and uniformity. OAR sparing for the urinary bladder, rectum, and penile bulb was within acceptable limits, meeting dose constraints in all plans. Monitor unit (MU) values were higher for Ethos plans compared to Eclipse but remained within clinically acceptable ranges.

Conclusion: The Ethos TPS, using its IOE, demonstrated the capability to generate high-quality radiotherapy plans for prostate cancer that are comparable to those produced by the Eclipse TPS. This suggests that the automated planning system can effectively reduce planning time and resource consumption while maintaining plan quality, thus supporting its potential clinical implementation.

自动化机器学习增强规划系统的效能评估及与人工规划系统的比较分析。
导读:放射治疗的目的是将高剂量的辐射精确地传递到目标体积,同时最大限度地减少对周围危险器官的暴露。这种方法最大限度地提高了肿瘤控制的可能性,并降低了不良副作用的风险。治疗计划系统(TPS)对于实现这一目标至关重要。然而,手工规划过程是耗时的,资源密集的,并且受制于基于个人规划人员的技能和经验的可变性。自动化计划旨在减少计划之间的变化和计划持续时间,同时保持或提高计划质量。瓦里安医疗系统公司推出了Ethos平台,这是一个利用智能优化引擎(IOE)的自动化规划和交付系统。本研究评估了使用Varian Ethos IOE自动生成计划用于前列腺癌治疗的有效性,并与使用Eclipse TPS和各向异性分析算法(AAA)生成计划进行了比较。材料与方法:回顾性分析15例诊断为前列腺癌的患者,治疗剂量为60 Gy,分20段对前列腺进行治疗。以相同的目标函数重新计算和优化治疗批准的Eclipse计划,然后导出到Ethos TPS。Ethos TPS共生成五种方案,分别为7、9和12场IMRT方案,以及2弧和3弧VMAT方案,保持固定的光束几何形状。在Ethos上还生成了两个额外的计划:一个是维护来自Eclipse的相同参数,用于计算目的,另一个涉及重新优化。主要目的是评估满足预先规定剂量限制的数量,而次要目的是比较剂量学参数,如Ethos和Eclipse计划之间的目标覆盖率、剂量一致性、剂量均匀性和OAR节约。结果:Eclipse计划与ethos生成计划在满足预定标准方面无统计学差异。对于PTV覆盖,所有计划的平均值为95亿美元,达到95%。V105 < 5%的平均值远低于阈值,表明热点最小。各方案的符合性指数(CI)接近于1,均匀性指数(HI)接近于0,说明剂量分布均匀性好。膀胱、直肠和阴茎球的OAR保留在可接受的范围内,满足所有计划的剂量限制。与Eclipse相比,Ethos计划的监测单位(MU)值更高,但仍在临床可接受的范围内。结论:Ethos TPS,利用其IOE,证明了能够产生与Eclipse TPS相当的高质量前列腺癌放疗计划。这说明自动化计划系统在保证计划质量的同时,可以有效减少计划时间和资源消耗,从而支持其潜在的临床实施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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