Development and clinical validation of a robust knowledge‐based planning model for stereotactic body radiotherapy treatment of centrally located lung tumors

Purpose To develop a robust and adaptable knowledge‐based planning (KBP) model with commercially available RapidPlanTM for early stage, centrally located non‐small‐cell lung tumors (NSCLC) treated with stereotactic body radiotherapy (SBRT) and improve a patient's“simulation to treatment” time. Methods The KBP model was trained using 86 clinically treated high‐quality non‐coplanar volumetric modulated arc therapy (n‐VMAT) lung SBRT plans with delivered prescriptions of 50 or 55 Gy in 5 fractions. Another 20 independent clinical n‐VMAT plans were used for validation of the model. KBP and n‐VMAT plans were compared via Radiation Therapy Oncology Group (RTOG)–0813 protocol compliance criteria for conformity (CI), gradient index (GI), maximal dose 2 cm away from the target in any direction (D2cm), dose to organs‐at‐risk (OAR), treatment delivery efficiency, and accuracy. KBP plans were re‐optimized with larger calculation grid size (CGS) of 2.5 mm to assess feasibility of rapid adaptive re‐planning. Results Knowledge‐based plans were similar or better than n‐VMAT plans based on a range of target coverage and OAR metrics. Planning target volume (PTV) for validation cases was 30.5 ± 19.1 cc (range 7.0–71.7 cc). KBPs provided an average CI of 1.04 ± 0.04 (0.97–1.11) vs. n‐VMAT plan'saverage CI of 1.01 ± 0.04 (0.97–1.17) (P