Clinical impact of the VOLO optimizer on treatment plan quality and clinical treatment efficiency for CyberKnife. Journal of applied clinical medical physics Schuler, E., Lo, A., Chuang, C. F., Soltys, S. G., Pollom, E. L., Wang, L. 2020

Abstract

With the recent CyberKnife treatment planning system (TPS) upgrade from Precision 1.0 to Precision 2.0, the new VOLO optimizer was released for plan optimization. The VOLO optimizer sought to overcome some of the limitations seen with the Sequential optimizer from previous TPS versions. The purpose of this study was to investigate the clinical impact of the VOLO optimizer on treatment plan quality and clinical treatment efficiency as compared to the Sequential optimizer. Treatment plan quality was evaluated in four categories of patients: Brain Simple (BS), Brain Complex (BC), Spine Complex (SC), and Prostate (PC). A total of 60 treatment plans were compared using both the Sequential and VOLO optimizers with Iris and MLC collimation with the same clinical constraints. Metrics evaluated included estimated treatment time, monitor units (MUs) delivered, conformity index (CI), and gradient index (GI). Furthermore, the clinical impact of the VOLO optimizer was evaluated through statistical analysis of the patient population treated during the 4months before (n=297) and 4months after (n=285) VOLO introduction. Significant MU and time reductions were observed for all four categories planned. MU reduction ranged from -14% (BS Iris) to -52% (BC MLC), and time reduction ranged from -11% (BS Iris) to -22% (BC MLC). The statistical analysis of patient population before and after VOLO introduction for patients using 6D Skull tracking with fixed cone, 6D Skull tracking with Iris, and Xsight Spine tracking with Iris were -4.6%, -22.2%, and -17.8% for treatment time reduction, -1.1%, -22.0%, and -28.4% for beam reduction and -3.2%, -21.8%, and -28.1% for MU reduction, respectively. The VOLO optimizer maintains or improves the plan quality while decreases the plan complexity and improves treatment efficiency. We anticipate an increase in patient throughput with the introduction of the VOLO optimizer.

View details for DOI 10.1002/acm2.12851

View details for PubMedID 32212374