Abstract
PurposeIn automated treatment planning, configuration of the underlying algorithm to generate high‐quality plans for all patients of a particular tumor type can be a major challenge. Often, a time‐consuming trial‐and‐error tuning procedure is required. The purpose of this paper is to automatically configure an automated treatment planning algorithm for oropharyngeal cancer patients.MethodsRecently, we proposed a new procedure to automatically configure the reference point method (RPM), a fast automatic multi‐objective treatment planning algorithm. With a well‐tuned configuration, the RPM generates a single Pareto optimal treatment plan with clinically favorable trade‐offs for each patient. The automatic configuration of the RPM requires a set of computed tomography (CT) scans with corresponding dose distributions for training. Previously, we demonstrated for prostate cancer planning with 12 objectives that training with only 9 patients resulted in high‐quality configurations. This paper further develops and explores the new automatic RPM configuration procedure for head and neck cancer planning with 22 objectives. Investigations were performed with planning CT scans of 105 previously treated unilateral or bilateral oropharyngeal cancer patients together with corresponding Pareto optimal treatment plans. These plans were generated with our clinically applied two‐phase ε‐constraint method (Erasmus‐iCycle) for automated multi‐objective treatment planning, ensuring consistent high quality and Pareto optimality of all plans. Clinically relevant, nonconvex criteria, such as dose‐volume parameters and NTCPs, were included to steer the RPM configuration.ResultsTraining sets with 20–50 patients were investigated. Even with 20 training plans, high‐quality configurations of the RPM were feasible. Automated plan generation with the automatically configured RPM resulted in Pareto optimal plans with overall similar or better quality than that of the Pareto optimal database plans.ConclusionsAutomatic configuration of the RPM for automated treatment planning is feasible and drastically reduces the time and workload required when compared to manual tuning of an automated treatment planning algorithm.
Highlights
Reference point method[5] (LRPM)
A high dose is to be delivered to the planning target volume (PTV), which is in close proximity to many critical method are faster plan generation with average relative speedup factors of 12 for prostate[5] and 22 for head and neck cancer,[8] and that trade-offs between all planning objectives are surrounding organs-at-risk (OARs) such as salivary glands, balanced simultaneously (LRPM) instead of pairwise (2pec oral cavity, swallowing muscles, larynx, esophagus, spinal method), allowing for large gains for some objectives at the cord, and brainstem
This paper further develops and investigates the proposed automatic reference point method (RPM) configuration for a heterogeneous group of oropharyngeal cancer patients, with 22 objectives used in automatic plan generation
Summary
Reference point method[5] (LRPM). Previous studies[6,7] have demonstrated that the quality of plans generated with the Generating high-quality intensity-modulated radiation ther- 2pec method is generally superior to that of manually generapy (IMRT) or volumetric modulated arc therapy (VMAT) ated plans. Two algorithms for automated multi-objective optimization of Pareto optimal plans have been developed in our center: (a) the two-phase e-constraint (2pec) method[3] which is part of the clinically applied ErasmusiCycle optimizer,[4] and (b) the fast and fuzzy lexicographic load-intensive procedure for both the 2pec method (“wishlist” creation4,7) and the LRPM.[5,8] Recently, we proposed a new automatic procedure[9] to configure the reference point method[10,11,12] (RPM), a special case of the LRPM.[5] The procedure was successfully applied to prostate IMRT,[9] and adaptive prostate and cervix IMPT.[13,14].
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