背景:在Accuray®的Precision®治疗计划系统中比较了两种优化算法VOLO™和顺序优化算法(SEQU),用于立体定向放射外科和立体定向身体放射治疗(SBRT)治疗计划。目的是比较两种算法以评估VOLO™在某些治疗部位是否优于SEQU。
方法:对60例临床治疗病例进行比较。实体包括听神经瘤(AN),肺转移瘤,和肝转移。在每个实体中,优化了10个SEQU和10个VOLO™治疗计划。光线追踪计算算法用于所有治疗计划,并且仅使用固定锥体(5-50mm)计划治疗。节点数,梁,总MU,并对治疗时间进行比较。符合性指数(CI),新一致性指数(NCI),同质性指数(HI),梯度指数(GI),和目标覆盖率进行了一致性检查。Dmin,Dmean,Dmax,D100%,D98%,检查目标体积中的D2%剂量以及对有风险器官的暴露。为了确定外周剂量,评估了从V10%到V98%的等剂量体积.
结果:AN治疗计划显示出节点数量的显着差异,梁,总MU,治疗时间,D98%,目标卷的D100%,以及所有危险器官的剂量。VOLO™平均取得了更好的结果。总MU,治疗时间,覆盖范围,和D98%对于VOLO™的肺转移明显更好。对于肝转移,节点数量的显著减少,总MU,VOLO™计划观察治疗时间。VOLO™的平均目标覆盖率略有增加,而meanCI略有恶化。Dmin的平均值,Dmean,D98%,D100%,和V80%导致VOLO™的显著增加。
结论:本研究的结果表明,应使用VOLO™代替SEQU作为AN病例向前发展的标准。尽管在肺部和肝脏病例中缺乏意义,建议进行VOLO™优化,因为OAR保留相似,但是覆盖范围,Dmin,Dmean增加了,因此可以预期更好的肿瘤控制。
BACKGROUND: Two optimization algorithms VOLO™ and sequential optimization algorithm (SEQU) are compared in the Precision® treatment planning system from Accuray® for stereotactic radiosurgery and stereotactic body radiotherapy (SBRT) treatment plans. The aim is to compare the two algorithms to assess if VOLO™ is better of SEQU in certain treatment site.
METHODS: Sixty clinical treatment cases were compared. Entities include Acoustic neuroma (AN), lung metastases, and liver metastases. In each entity, 10 SEQU and 10 VOLO™ treatment plans were optimized. The Ray-Tracing calculation algorithm was used for all treatment plans and the treatments were planned exclusively with fixed cones (5-50 mm). The number of nodes, beams, total MU, and treatment time were compared. Conformity index (CI), new conformity index (nCI), homogeneity index (HI), gradient index (GI), and target coverage were examined for agreement. Dmin , Dmean , Dmax , D100%, D98%, and D2% dose in the target volume as well as exposure to organs at risk was checked. To determine peripheral doses, the isodose volumes from V10% to V98% were evaluated.
RESULTS: AN treatment plans showed significant differences for the number of nodes, beams, total MU, treatment time, D98%, D100% for the target volume, and the doses for all organs at risk. VOLO™ achieved better results on average. Total MU, treatment time, coverage, and D98% are significantly better for VOLO™ for lung metastases. For liver metastases, a significant reduction in number of nodes, total MU, and treatment time was observed for VOLO™ plans. The mean target coverage increased slightly with VOLO™, while the mean CI deteriorated slightly. The averages of Dmin , Dmean , D98%, D100%, and V80% resulted in a significant increase for VOLO™.
CONCLUSIONS: The results of the present study indicate that VOLO™ should be used in place of SEQU as a standard for AN cases moving forward. Despite the lack of significance in the lung and liver cases, VOLO™ optimization is recommended because OAR sparing was similar, but coverage, Dmin , and Dmean were increased, and thus better tumor control can be expected.