A hybrid planning strategy for stereotactic body radiation therapy of early stage non-small-cell lung cancer.

Currently dynamic conformal arcs (DCA) and volumetric modulated arc therapy (VMAT) are two popular planning techniques to treat lung stereotactic body radiation therapy (SBRT) patients. Of the two, DCA has advantages in terms of multi-leaf collimator (MLC) motion, positioning error, and delivery efficiency. However, VMAT is often the choice when critical organ sparing becomes important. We developed a hybrid strategy to incorporate DCA component into VMAT planning, results were compared with DCA and VMAT plans. Four planning techniques were retrospectively simulated for 10 lung SBRT patients: DCA, Hybrid-DCA (2/3 of the doses from DCA beams), Hybrid-VMAT (2/3 of the doses from VMAT beams) and VMAT. Plan complexity was accessed by modulation complexity score (MCS). Conformity index (CI) for the planning target volume (PTV), V20 and V5 for the lung, V30 for the chestwall, and maximum dose to all other critical organs were calculated. Plans were compared with regard to these metrics and measured agreement between the planned and delivered doses. DCA technique did not result in acceptable plan quality due to target location for five patients. Hybrid-DCA produced one unacceptable plan, and Hybrid-VMAT and VMAT produced no unacceptable plans. The CI improved with increasing VMAT usage, as did the dose sparing to critical structures. Compared to the VMAT technique, a total MU reduction of 14%, 25% and 37% were found for Hybrid-VMAT, Hybrid-DCA and DCA techniques for 54 Gy patient group, and 9%, 23% and 34% for 50 Gy patient group, suggesting improvement in delivery efficiency with increasing DCA usage. No significant variations of plan complexity were observed between Hybrid-DCA and Hybrid-VMAT (P = 0.46 from Mann-Whitney U-test), but significant differences were found among DCA, Hybrid and VMAT (P < 0.05). Better agreements between the planned and delivered doses were found with more DCA contributions. By adding DCA components to VMAT planning, hybrid technique offers comparable dosimetry to full VMAT, while increasing delivery efficiency and minimizing MLC complexity.

Comparison of the progressive resolution optimizer and photon optimizer in VMAT optimization for stereotactic treatments.

The photon optimization (PO) algorithm was recently released by Varian Medical Systems to improve volumetric modulated arc therapy (VMAT) optimization within Eclipse (Version 13.5). The purpose of this study is to compare the PO algorithm with its predecessor, progressive resolution optimizer (PRO) for lung SBRT and brain SRS treatments. A total of 30 patients were selected retrospectively. Previously, all the plans were generated with the PRO algorithm within Eclipse Version 13.6. In the new version of PO algorithm (Version 15), dynamic conformal arcs (DCA) were first conformed to the target, then VMAT inverse planning was performed to achieve the desired dose distributions. PTV coverages were forced to be identical for the same patient for a fair comparison. SBRT plan quality was assessed based on selected dose-volume parameters, including the conformity index, V20 for lung, V30 Gy for chest wall, and D0.035 cc for other critical organs. SRS plan quality was evaluated based on the conformity index and normal tissue volumes encompassed by the 12 and 6 Gy isodose lines (V12 and V6 ). The modulation complexity score (MCS) was used to compare plan complexity of two algorithms. No statistically significant differences between the PRO and PO algorithms were found for any of the dosimetric parameters studied, which indicates both algorithms produce comparable plan quality. Significant improvements in the gamma passing rate (increased from 97.0% to 99.2% for SBRT and 96.1% to 98.4% for SRS), MCS (average increase of 0.15 for SBRT and 0.10 for SRS), and delivery efficiency (MU reduction of 29.8% for SBRT and 28.3% for SRS) were found for the PO algorithm. MCS showed a strong correlation with the gamma passing rate, and an inverse correlation with total MUs used. The PO algorithm offers comparable plan quality to the PRO, while minimizing MLC complexity, thereby improving the delivery efficiency and accuracy.