Abstract
PurposeKnowledge-based planning (KBP) clinical implementation necessitates significant upfront effort, even within a single disease site. The purpose of this study was to demonstrate an efficient method for clinicians to assess the noninferiority of KBP across multiple disease sites and estimate any systematic dosimetric differences after implementation. We sought to establish these endpoints in a plurality of previously treated patients (validation set) with both closed-loop (training set overlapping validation set) and open-loop (independent training set) KBP routines. Methods and MaterialsWe identified 53 prostate, 24 prostatic fossa, 54 hypofractionated lung, and 52 head and neck patients treated with volumetric modulated arc therapy in the year directly preceding our clinic's broad adoption of RapidPlan (Varian Medical Systems, Palo Alto, CA). Using the Varian Eclipse Scripting API, our program takes as input a list of patients, then performs semiautomated structure matching, fully automated RapidPlan-driven optimization, and plan comparison. All plans were normalized to the planning target volume (PTV) D95% = 100%. Dose metric differences (ΔDx = Dx,clinical − Dx,KBP) were computed for standard PTV and organ-at-risk (OAR) dose-volume histogram parameters across disease sites. A 2-tailed paired t test quantified statistical significance (P < .001). ResultsStatistically significant organ dose-volume histogram improvements were observed in the KBP cohort: the rectum, bladder, and penile bulb in prostate/prostatic fossa; and the larynx, esophagus, cricopharyngeus, parotid glands, and cochlea in head and neck. No OAR dose metric was statistically worse in any KBP sample. PTV ΔD1% increases in prostatic fossa were deemed acceptable given organ-sparing gains. PTV ΔD1% and internal target volume ΔD99% increase for the lung was by design owing to the prescription normalization variance in the pre-KBP lung sample. ConclusionsOur automated method showed multiple disease sites' KBP routines to be noninferior to manual planning, with statistically significant superiority in some aspects of OAR sparing. This method is applicable to any institution implementing either closed-loop or open-loop KBP autoplanning routines.
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