Search

Background and purpose: Bioselection with induction chemotherapy in larynx cancer is associated with excellent larynx preservation and disease-specific survival but requires visual inspection of the primary tumor. We retrospectively compare clinical and imaging response in bioselected patients to develop predictive models of surgeon-assessed response (SR), laryngectomy-free survival (LFS), and overall survival (OS) in bioselected patients. Materials and methods: In a secondary analysis of patients on two single-institution bioselection trials, model building used a regularized regression model (elastic-net) and applied nested cross-validation. Logistic regression-based model was used to predict SR and Cox proportional hazard-based models were used to predict LFS and OS. Results: In 115 patients with a median age of 57 years, most patients had supraglottic tumors (73.0%) and T3/T4 disease (94.8%). Definitive treatment was chemoradiation in 76.5% and laryngectomy in 23.5%. Change in primary tumor (OR = 5.78, p

Purpose: Head and neck (HN) radiation (RT) treatment planning is complex and resource intensive. Deviations and inconsistent plan quality significantly affect clinical outcomes. We sought to develop a novel automated virtual integrative (AVI) knowledge-based planning application to reduce planning time, increase consistency, and improve baseline quality. Methods and Materials: An in-house write-enabled script was developed from a library of 668 previously treated HN RT plans. Prospective hazard analysis was performed, and mitigation strategies were implemented before clinical release. The AVI-planner software was retrospectively validated in a cohort of 52 recent HN cases. A physician panel evaluated planning limitations during initial deployment, and feedback was enacted via software refinements. A final second set of plans was generated and evaluated. Kolmogorov-Smirnov test in addition to generalized evaluation metric and weighted experience score were used to compare normal tissue sparing between final AVI planner versus respective clinically treated and historically accepted plans. A t test was used to compare the interactive time, complexity, and monitor units for AVI planner versus manual optimization. Results: Initially, 86% of plans were acceptable to treat, with 10% minor and 4% major revisions or rejection recommended. Variability was noted in plan quality among HN subsites, with high initial quality for oropharynx and oral cavity plans. Plans needing revisions were comprised of sinonasal, nasopharynx, P-16 negative squamous cell carcinoma unknown primary, or cutaneous primary sites. Normal tissue sparing varied within subsites, but AVI planner significantly lowered mean larynx dose (median, 18.5 vs 19.7 Gy; P < .01) compared with clinical plans. AVI planner significantly reduced interactive optimization time (mean, 2 vs 85 minutes; P < .01). Conclusions: AVI planner reliably generated clinically acceptable RT plans for oral cavity, salivary, oropharynx, larynx, and hypopharynx cancers. Physician-driven iterative learning processes resulted in favorable evolution in HN RT plan quality with significant time savings and improved consistency using AVI planner.