ABSTRACT
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.
ABSTRACT
This study aims to demonstrate a specific treatment planning method and its effectiveness of sparing high dose to superficial skin for head and neck volumetric-modulated arc therapy (VMAT) treatments. A total of 10 patients with bilateral disease encompassing superficial neck nodes were planned as VMAT. Standard VMAT plans were created for each patient per written directive from physician, including target prescriptions, normal structure goals, and plan parameters. After these plans were created, low isodose levels were converted into dose structures, which are used to create a new skin sparing (SS) structure. With the new SS structure made, the original plan was copied to create a new SS plan. The new SS plan was re-optimized utilizing the newly created SS structure to help in decreasing dose to the superficial regions on the skin surface. The result of this treatment planning technique, comparing SS plans to original nonskin sparing (NSS) plans, provides a reduced dose of 10% to 15% to the skin surface in all cases. Although this technique reduces the dose to the skin, it can also reduce the dose to treatment volumes. Depending on physician intent, diagnosis, and disease, this method should only be used when the skin is not at risk, otherwise it could potentially cause underdosing to the disease site. All SS plans were considered clinically acceptable and provided adequate coverage to planning target volume (PTV), while reducing unwarranted high dose to superficial skin tissue.