Snyder Jeffrey E, St-Aubin Joël, Yaddanapudi Sridhar, Marshall Spencer, Strand Sarah, Kruger Stanley, Flynn Ryan, Hyer Daniel E
Department of Radiation Oncology, University of Iowa Hospitals and Clinics, 200 Hawkins Drive, Iowa City, IA 52242, United States of America.
Elekta AB, Stockholm, Sweden.
Phys Med Biol. 2022 Feb 24;67(5). doi: 10.1088/1361-6560/ac5299.
Extended treatment session times are an operational limitation in magnetic resonance imaging guided adaptive radiotherapy (MRIgRT). In this study a novel leaf sequencing algorithm called optimal fluence levels (OFL) and an optimization algorithm called pseudo gradient descent (PGD) are evaluated with respect to plan quality, beam complexity, and the ability to reduce treatment session times on the Elekta Unity MRIgRT system.Ten total patients were evaluated on this Institutional Review Board approved study: three with prostate cancer, three with oligometastases, two with pancreatic cancer, and two with liver cancer. Plans were generated using the clinical Monaco Hyperion optimizer and leaf sequencer and then re-optimized using OFL and PGD (OFL + PGD) while holding all IMRT constraints and planning parameters constant. All plans were normalized to ensure 95% of the PTV received the prescription dose. A paired t-test was used to evaluate statistical significance.Plan quality in terms of dosimetric OAR sparing was found to be equivalent between the OFL + PGD and conventional Monaco Hyperion optimizer plans. The OFL + PGD plans had a reduction in optimization time of 51.4% ± 5.0% ( = 0.002) and reduction in treatment delivery time of 10.6% ± 7.5% ( = 0.005). OFL + PGD generated plans had on average 13.2% ± 12.6% fewer multi-leaf collimator (MLC) segments ( = 0.009) and 0.1 ± 0.1 lower plan averaged beam modulation (PM) ( = 0.004) relative to the Monaco Hyperion plans.The OFL + PGD algorithms more quickly generate Unity treatment plans that are faster to deliver than with the conventional approach and without compromising dosimetric plan quality. This is likely due to a delivery complexity reduction enabled by OFL + PGD relative to the Monaco Hyperion plans.
在磁共振成像引导的自适应放射治疗（MRIgRT）中，延长治疗时段时间是一个操作限制因素。在本研究中，针对计划质量、射束复杂性以及在医科达Unity MRIgRT系统上减少治疗时段时间的能力，对一种名为最佳注量水平（OFL）的新型叶片排序算法和一种名为伪梯度下降（PGD）的优化算法进行了评估。在这项经机构审查委员会批准的研究中，共评估了10名患者：3名前列腺癌患者、3名寡转移患者、2名胰腺癌患者和2名肝癌患者。使用临床Monaco Hyperion优化器和叶片排序器生成计划，然后在保持所有调强放疗（IMRT）约束和计划参数不变的情况下，使用OFL和PGD（OFL + PGD）重新优化。所有计划均进行归一化处理，以确保95%的计划靶体积（PTV）接受处方剂量。采用配对t检验评估统计学显著性。
在剂量学上对危及器官（OAR）的保护方面，发现OFL + PGD计划与传统的Monaco Hyperion优化器计划相当。OFL + PGD计划的优化时间减少了51.4% ± 5.0%（P = 0.002），治疗执行时间减少了10.6% ± 7.5%（P = 0.005）。相对于Monaco Hyperion计划，OFL + PGD生成的计划平均多叶准直器（MLC）段数减少了13.2% ± 12.6%（P = 0.009），计划平均射束调制（PM）降低了0.1 ± 0.1（P = 0.004）。
OFL + PGD算法能更快地生成Unity治疗计划，且与传统方法相比，治疗执行速度更快，同时不影响剂量学计划质量。这可能是由于相对于Monaco Hyperion计划，OFL + PGD降低了治疗执行的复杂性。
