Evaluation of a Knowledge-Based Planning Solution for Head and Neck Cancer

Purpose: Automated and knowledge-based planning techniques aim to reduce variations in plan quality. RapidPlan uses a library consisting of different patient plans to make a model that can predict achievable dose-volume histograms (DVHs) for new patients and uses those models for setting optimization objectives. We benchmarked RapidPlan versus clinical plans for 2 patient groups, using 3 different libraries. Methods and Materials: Volumetric modulated arc therapy plans of 60 recent head and neck cancer patients that included sparing of the salivary glands, swallowing muscles, and oral cavity were evenly divided between 2 models, Model_30A and Model_30B, and were combined in a third model, Model₆₀. Knowledge-based plans were created for 2 evaluation groups: evaluation group 1 (EG1), consisting of 15 recent patients, and evaluation group 2 (EG2), consisting of 15 older patients in whom only the salivary glands were spared. RapidPlan results were compared with clinical plans (CP) for boost and/or elective planning target volume homogeneity index, using HI_B/HI_E = 100 × (D2% − D98%)/D50%, and mean dose to composite salivary glands, swallowing muscles, and oral cavity (D_sal, D_swal, and D_oc, respectively). Results: For EG1, RapidPlan improved HI_B and HI_E values compared with CP by 1.0% to 1.3% and 1.0% to 0.6%, respectively. Comparable D_sal and D_swal values were seen in Model_30A, Model_30B, and Model₆₀, decreasing by an average of 0.1, 1.0, and 0.8 Gy and 4.8, 3.7, and 4.4 Gy, respectively. However, differences were noted between individual organs at risk (OARs), with Model_30B increasing D_oc by 0.1, 3.2, and 2.8 Gy compared with CP, Model_30A, and Model₆₀. Plan quality was less consistent when the patient was flagged as an outlier. For EG2, RapidPlan decreased D_sal by 4.1 to 4.9 Gy on average, whereas HI_B and HI_E decreased by 1.1% to 1.5% and 2.3% to 1.9%, respectively. Conclusions: RapidPlan knowledge-based treatment plans were comparable to CP if the patient's OAR-planning target volume geometry was within the range of those included in the models. EG2 results showed that a model including swallowing-muscle and oral-cavity sparing can be applied to patients with only salivary gland sparing. This may allow model library sharing between institutes. Optimal detection of inadequate plans and population of model libraries requires further investigation