放射治疗治疗计划的多目标、多剂量优化

Multiobjective, Multidelivery Optimization for Radiation Therapy Treatment Planning.

作者信息

Watkins William Tyler, Nourzadeh Hamidreza, Siebers Jeffrey V

机构信息

Department of Radiation Oncology, University of Virginia, Charlottesville, Virginia.

出版信息

Adv Radiat Oncol. 2019 Sep 27;5(2):279-288. doi: 10.1016/j.adro.2019.09.003. eCollection 2020 Mar-Apr.

DOI:10.1016/j.adro.2019.09.003

PMID:32280828

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7136667/

Abstract

PURPOSE

To introduce multiobjective, multidelivery optimization (MODO), which generates alternative patient-specific plans emphasizing dosimetric trade-offs and conformance to quasi-constrained (QC) conditions for multiple delivery techniques.

METHODS AND MATERIALS

For delivery techniques and organs at risk (OARs), MODO generates ( + 1) alternative treatment plans per patient. For 30 locally advanced lung cancer cases, the algorithm was investigated based on dosimetric trade-offs to 4 OARs: each lung, heart, and esophagus (N = 4) and 4 delivery techniques (4-field coplanar intensity modulated radiation therapy [IMRT], 9-field coplanar IMRT, 27-field noncoplanar IMRT, and noncoplanar arc IMRT) and conformance to QC conditions, including dose to 95% (D95) of the planning target volume (PTV), maximum dose (Dmax) to PTV (PTV-Dmax), and spinal cord Dmax. The MODO plan set was evaluated for conformance to QC conditions while simultaneously revealing dosimetric trade-offs. Statistically significant dosimetric trade-offs were defined such that the coefficient of determination was >0.8 with dosimetric indices that varied by at least 5 Gy.

RESULTS

Plans varied mean dose by >5 Gy to ipsilateral lung for 24 of 30 patients, contralateral lung for 29 of 30 patients, esophagus for 29 of 30 patients, and heart for 19 of 30 patients. In the 600 plans, average PTV-D95 = 67.6 ± 2.1 Gy, PTV-Dmax = 79.8 ± 5.2 Gy, and spinal cord Dmax among all plans was 51.4 Gy. Statistically significant dosimetric trade-offs reducing OAR mean dose by >5 Gy were evident in 19 of 30 patients, including multiple OAR trade-offs of at least 5 Gy in 7 of 30 cases. The most common statistically significant trade-off was increasing PTV-Dmax to reduce dose to OARs (15 of 30). The average 4-field plan reduced total lung V20 by 10.4% ± 8.3% compared with 9-field plans, 7.7% ± 7.9% compared with 27-field noncoplanar plans, and 11.7% ± 10.3% compared with 2-arc noncoplanar plans, with corresponding increases in PTV-Dmax of 5.3 ± 5.9 Gy, 4.6 ± 5.6 Gy, and 9.3 ± 7.3 Gy.

CONCLUSIONS

The proposed optimization method produces clinically relevant treatment plans that meet QC conditions and demonstrate variations in OAR doses.

摘要

目的

介绍多目标、多射野优化（MODO），它能生成针对特定患者的替代计划，强调剂量权衡以及符合多种射野技术的准约束（QC）条件。

方法和材料

对于多种射野技术和危及器官（OARs），MODO为每位患者生成（射野数 + 1）个替代治疗计划。对于30例局部晚期肺癌病例，基于对4个OARs（双侧肺、心脏和食管，各4个）的剂量权衡以及符合QC条件，对该算法进行了研究，4种射野技术包括：4野共面调强放射治疗（IMRT）、9野共面IMRT、27野非共面IMRT和非共面弧形IMRT，QC条件包括计划靶区（PTV）95%体积的剂量（D95）、PTV的最大剂量（Dmax）（PTV - Dmax）以及脊髓Dmax。对MODO计划集进行QC条件符合度评估，同时揭示剂量权衡情况。定义具有统计学意义的剂量权衡为决定系数>0.8，且剂量指标变化至少5 Gy。

结果

30例患者中，24例患者同侧肺、29例患者对侧肺、29例患者食管以及19例患者心脏的计划平均剂量变化>5 Gy。在600个计划中，平均PTV - D95 = 67.6 ± 2.1 Gy，PTV - Dmax = 79.8 ± 5.2 Gy，所有计划中脊髓Dmax为51.4 Gy。30例患者中有19例出现了使OAR平均剂量降低>5 Gy的具有统计学意义的剂量权衡，其中30例中有7例出现了至少5 Gy的多个OAR之间的权衡。最常见的具有统计学意义的权衡是增加PTV - Dmax以降低OARs的剂量（30例中有15例）。与9野计划相比，平均4野计划使全肺V20降低了10.4% ± 8.3%，与27野非共面计划相比降低了7.7% ± 7.9%，与2弧非共面计划相比降低了11.7% ± 10.3%，相应地PTV - Dmax分别增加了5.3 ± 5.9 Gy、4.6 ± 5.6 Gy和9.3 ± 7.3 Gy。