PDF(Pubmed)
Abstract：
Radiotherapy (RT) doses to cardiac substructures from the definitive treatment of locally advanced non-small cell lung cancers (NSCLC) have been linked to post-RT cardiac toxicities. With modern treatment delivery techniques, it is possible to focus radiation doses to the planning target volume while reducing cardiac substructure doses. However, it is often challenging to design such treatment plans due to complex tradeoffs involving numerous cardiac substructures. Here, we built a cardiac-substructure-based knowledge-based planning (CS-KBP) model and retrospectively evaluated its performance against a cardiac-based KBP (C-KBP) model and manually optimized patient treatment plans. CS-KBP/C-KBP models were built with 27 previously-treated plans that preferentially spare the heart. While the C-KBP training plans were created with whole heart structures, the CS-KBP model training plans each have 15 cardiac substructures (coronary arteries, valves, great vessels, and chambers of the heart). CS-KBP training plans reflect cardiac-substructure sparing preferences. We evaluated both models on 28 additional patients. Three sets of treatment plans were compared: (1) manually optimized, (2) C-KBP model-generated, and (3) CS-KBP model-generated. Plans were normalized to receive the prescribed dose to at least 95% of the PTV. A two-tailed paired-sample t-test was performed for clinically relevant dose-volume metrics to evaluate the performance of the CS-KBP model against the C-KBP model and clinical plans, respectively. Overall results show significantly improved cardiac substructure sparing by CS-KBP in comparison to C-KBP and the clinical plans. For instance, the average left anterior descending artery volume receiving 15 Gy (V15 Gy) was significantly lower (p < 0.01) for CS-KBP (0.69 ± 1.57 cc) compared to the clinical plans (1.23 ± 1.76 cc) and C-KBP plans (1.05 ± 1.68 cc). In conclusion, the CS-KBP model significantly improved cardiac-substructure sparing without exceeding the tolerances of other OARs or compromising PTV coverage.
摘要：
来自局部晚期非小细胞肺癌（NSCLC）的确定性治疗的心脏亚结构的放射治疗（RT）剂量与RT后的心脏毒性有关。有了现代治疗技术，可以将辐射剂量集中到计划目标体积，同时减少心脏子结构剂量。然而,由于涉及众多心脏亚结构的复杂权衡,设计此类治疗计划通常具有挑战性.这里,我们构建了基于心脏子结构的基于知识的计划(CS-KBP)模型,并根据基于心脏的KBP(C-KBP)模型和手动优化的患者治疗计划对其性能进行了回顾性评估.CS-KBP/C-KBP模型建立了27种优先保留心脏的先前治疗计划。虽然C-KBP训练计划是用整个心脏结构制定的，CS-KBP模型训练计划每个都有15个心脏亚结构(冠状动脉，阀门,伟大的船只，和心室）。CS-KBP训练计划反映了心脏子结构的保留偏好。我们评估了另外28名患者的两种模型。比较了三套治疗方案：（1）手动优化，(2)C-KBP模型生成,(3)CS-KBP模型生成。将计划标准化以接受至少95%的PTV的处方剂量。对临床相关剂量体积指标进行双尾配对样本t检验，评价CS-KBP模型对C-KBP模型和临床计划的性能，分别。总体结果表明，与C-KBP和临床计划相比，CS-KBP保留的心脏亚结构明显改善。例如,与临床计划（1.23±1.76cc）和C-KBP计划（1.05±1.68cc）相比，CS-KBP（0.69±1.57cc）接受15Gy（V15Gy）的平均左前降支体积显着降低（p<0.01）。总之,CS-KBP模型在不超过其他OAR的容差或影响PTV覆盖率的情况下,显著改善了心脏亚结构的保留.
