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Predicting personalised optimal arc parameter using knowledge-based planning model for inoperable locally advanced lung cancer patients to reduce organ at risk doses
Biomedical Physics & Engineering Express ( IF 1.3 ) Pub Date : 2021-09-22 , DOI: 10.1088/2057-1976/ac2635
Nilesh S Tambe 1, 2 , Isabel M Pires 2 , Craig Moore 1 , Andrew Wieczorek 3 , Sunil Upadhyay 3 , Andrew W Beavis 1, 2, 4
Affiliation  

Objectives. Volumetric modulated arc therapy (VMAT) allows for reduction of organs at risk (OAR) volumes receiving higher doses, but increases OAR volumes receiving lower radiation doses and can subsequently increasing associated toxicity. Therefore, reduction of this low-dose-bath is crucial. This study investigates personalizing the optimization of VMAT arc parameters (gantry start and stop angles) to decrease OAR doses. Materials and Methods. Twenty previously treated locally advanced non-small cell lung cancer (NSCLC) patients treated with half-arcs were randomly selected from our database. These plans were re-optimized with seven different arcs parameters; optimization objectives were kept constant for all plans. All resulting plans were reviewed by two clinicians and the optimal plan (lowest OAR doses and adequate target coverage) was selected. Furthermore, knowledge-based planning (KBP) model was developed using these plans as ‘training data’ to predict optimal arc parameters for individual patients based on their anatomy. Treatment plan complexity scores and deliverability measurements were performed for both optimal and original clinical plans. Results. The results show that different arc geometries resulted in different dose distributions to the OAR but target coverage was mostly similar. Different arc geometries were required for different patients to minimize OAR doses. Comparison of the personalized against the standard (2 half-arcs) plans showed a significant reduction in lung V5 (lung volume receiving 5 Gy), mean lung dose and mean heart doses. Reduction in lung V20 and heart V30 were statistically insignificant. Plan complexity and deliverability measurements show the test plans can be delivered as planned. Conclusions. Our study demonstrated that personalizing arc parameters based on an individual patient’s anatomy significantly reduces both lung and heart doses. Dose reduction is expected to reduce toxicity and improve the quality of life for these patients.



中文翻译:

使用基于知识的规划模型为不能手术的局部晚期肺癌患者预测个性化最佳电弧参数,以降低器官风险剂量

目标。容积调制弧治疗 (VMAT) 允许减少接受较高剂量的危及器官 (OAR) 体积,但会增加接受较低辐射剂量的 OAR 体积,并可能随后增加相关毒性。因此,减少这种低剂量浴是至关重要的。本研究调查了 VMAT 弧形参数(机架开始和停止角度)的个性化优化以减少 OAR 剂量。材料和方法. 从我们的数据库中随机选择了 20 名先前接受过半弧治疗的局部晚期非小细胞肺癌 (NSCLC) 患者。这些计划使用七个不同的弧形参数进行了重新优化;所有计划的优化目标都保持不变。两名临床医生审查了所有由此产生的计划,并选择了最佳计划(最低 OAR 剂量和足够的目标覆盖率)。此外,基于知识的规划 (KBP) 模型是使用这些计划作为“训练数据”开发的,以根据个体患者的解剖结构预测最佳弧形参数。对最佳和原始临床计划进行了治疗计划复杂性评分和可交付性测量。结果。结果表明,不同的弧形几何形状导致 OAR 的剂量分布不同,但目标覆盖范围基本相似。不同的患者需要不同的弧形几何形状,以最大限度地减少 OAR 剂量。个性化计划与标准(2 个半弧)计划的比较显示肺 V 5(接受 5 Gy 的肺体积)、平均肺剂量和平均心脏剂量显着降低。肺V 20和心脏V 30的降低在统计学上不显着。计划复杂性和可交付性测量显示测试计划可以按计划交付。结论。我们的研究表明,根据个体患者的解剖结构对电弧参数进行个性化设置可显着降低肺部和心脏的剂量。减少剂量有望降低毒性并改善这些患者的生活质量。

更新日期:2021-09-22
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