Section for Biomedical Physic, Department for Radiation Oncology, University Hospital Tübingen, Hoppe-Seyler-Str. 3, 72076 Tübingen, Germany.
Section for Biomedical Physic, Department for Radiation Oncology, University Hospital Tübingen, Hoppe-Seyler-Str. 3, 72076 Tübingen, Germany.
Phys Med. 2020 Jan;69:101-109. doi: 10.1016/j.ejmp.2019.12.007. Epub 2019 Dec 17.
To investigate the potential of Particle Swarm Optimization (PSO) for fully automatic VMAT radiotherapy (RT) treatment planning.
In PSO a solution space of planning constraints is searched for the best possible RT plan in an iterative, statistical method, optimizing a population of candidate solutions. To identify the best candidate solution and for final evaluation a plan quality score (PQS), based on dose volume histogram (DVH) parameters, was introduced. Automatic PSO-based RT planning was used for N = 10 postoperative prostate cancer cases, retrospectively taken from our clinical database, with a prescribed dose of EUD = 66 Gy in addition to two constraints for rectum and one for bladder. Resulting PSO-based plans were compared dosimetrically to manually generated VMAT plans.
PSO successfully proposed treatment plans comparable to manually optimized ones in 9/10 cases. The median (range) PTV EUD was 65.4 Gy (64.7-66.0) for manual and 65.3 Gy (62.5-65.5) for PSO plans, respectively. However PSO plans achieved significantly lower doses in rectum D 67.0 Gy (66.5-67.5) vs. 66.1 Gy (64.7-66.5, p = 0.016). All other evaluated parameters (PTV D and D, rectum V and V, bladder D and V) were comparable in both plans. Manual plans had lower PQS compared to PSO plans with -0.82 (-16.43-1.08) vs. 0.91 (-5.98-6.25).
PSO allows for fully automatic generation of VMAT plans with plan quality comparable to manually optimized plans. However, before clinical implementation further research is needed concerning further adaptation of PSO-specific parameters and the refinement of the PQS.
研究粒子群优化（PSO）在全自动 VMAT 放射治疗（RT）计划中的潜力。
在 PSO 中，通过迭代的、统计学的方法，在规划约束的解空间中搜索最佳 RT 计划，优化候选解的种群。为了确定最佳候选解并进行最终评估，引入了基于剂量体积直方图（DVH）参数的计划质量评分（PQS）。使用自动 PSO 方法对 10 例回顾性前列腺癌术后病例进行了研究，这些病例来自我们的临床数据库，处方剂量为 EUD=66 Gy，此外还有直肠和膀胱的两个约束条件。生成的 PSO 计划与手动生成的 VMAT 计划进行了剂量学比较。
PSO 成功地为 9/10 例患者提出了与手动优化相当的治疗计划。PTV 的 EUD 的中位数（范围）分别为手动计划的 65.4 Gy（64.7-66.0）和 PSO 计划的 65.3 Gy（62.5-65.5）。然而，PSO 计划在直肠 D67.0 Gy（66.5-67.5）方面的剂量明显较低，而在直肠 D66.1 Gy（64.7-66.5，p=0.016）方面的剂量明显较低。在两个计划中，所有其他评估的参数（PTV D 和 D、直肠 V 和 V、膀胱 D 和 V）都是可比的。与 PSO 计划相比，手动计划的 PQS 较低，为-0.82（-16.43-1.08），而 PSO 计划为 0.91（-5.98-6.25）。
PSO 允许全自动生成与手动优化计划质量相当的 VMAT 计划。然而，在临床实施之前，需要进一步研究 PSO 特定参数的进一步适应性和 PQS 的细化。
Zotero 插件