Impact of Aperture Shape Controller on Knowledge-based VMAT Planning of Prostate Cancer

Abstract

Knowledge-based planning (KBP) has disadvantages of high monitor unit (MU) and complex multi-leaf collimator (MLC) motion. We investigated the optimal aperture shape controller (ASC) level for the KBP to reduce these factors in volumetric modulated arc therapy (VMAT) for prostate cancer. The KBP model was created based on 51 clinical plans (CPs) of patients who underwent the VMAT for prostate cancer. Another 10 CPs were selected randomly, and the KBPs with/without ASC, changed stepwise from very low (KBP-VL) to very high (KBP-VH), were performed with a single auto-optimization. The parameters of dose-volume histograms (DVHs) and MLC performance metrics were evaluated. We obtained the modulation complexity score for VMAT (MCSv), closed leaf score (CLS), small aperture score (SAS), leaf travel (LT), and total MU. The ASC did not affect the DVH parameters negatively. The following comparisons of MLC performance were obtained (KBP vs. KBP-VL vs. KBP-VH, respectively): 0.25 vs. 0.27 vs. 0.30 (MCSv), 0.19 vs. 0.18 vs. 0.16 (CLS), 0.50 vs. 0.45 vs. 0.40 (SAS10 mm), 0.73 vs. 0.68 vs. 0.63 (SAS20 mm), 768.35 mm vs. 671.50 mm vs. 551.32 mm (LT), and 672.87 vs. 642.36 vs. 607.59 (MU). There were significant differences between KBP and KBP-VH for MCSv and LT (p<0.05). The KBP using an ASC set to the very high level could reduce the complexity of MLC motion significantly more without deterioration of the DVH parameters compared with the KBP in VMAT for prostate cancer.