Effect of Dosimetric Outliers on the Performance of a Commercial Knowledge-Based Planning Solution
Purpose: RapidPlan, a commercial knowledge-based planning solution, uses a model library containing the geometry and associated dosimetry of existing plans. This model predicts achievable dosimetry for prospective patients that can be used to guide plan optimization. However, it is unknown how suboptimal model plans (outliers) influence the predictions or resulting plans. We investigated the effect of, first, removing outliers from the model (cleaning it) and subsequently adding deliberate dosimetric outliers. Methods and Materials: Clinical plans from 70 head and neck cancer patients comprised the uncleaned (UC) Model{sub UC}, from which outliers were cleaned (C) to create Model{sub C}. The last 5 to 40 patients of Model{sub C} were replanned with no attempt to spare the salivary glands. These substantial dosimetric outliers were reintroduced to the model in increments of 5, creating Model{sub 5} to Model{sub 40} (Model{sub 5-40}). These models were used to create plans for a 10-patient evaluation group. Plans from Model{sub UC} and Model{sub C}, and Model{sub C} and Model{sub 5-40} were compared on the basis of boost (B) and elective (E) target volume homogeneity indexes (HI{sub B}/HI{sub E}) and mean doses to oral cavity, composite salivary glands (comp{sub sal}) and swallowing (comp{sub swal}) structures. Results: On average, outlier removal (Model{sub C} vs Model{sub UC}) had minimal effects on HI{sub B}/HI{sub E} (0%-0.4%) and sparing of organs at risk (mean dose difference to oral cavity and comp{sub sal}/comp{sub swal} were ≤0.4 Gy). Model{sub 5-10} marginally improved comp{sub sal} sparing, whereas adding a larger number of outliers (Model{sub 20-40}) led to deteriorations in comp{sub sal} up to 3.9 Gy, on average. These increases are modest compared to the 14.9 Gy dose increases in the added outlier plans, due to the placement of optimization objectives below the inferior boundary of the dose-volume histogram-predicted range. Conclusions: Overall, dosimetric outlier removal from or addition of 5 to 10 outliers to a 70-patient model had marginal effects on resulting plan quality. Although the addition of >20 outliers deteriorated plan quality, the effect was modest. In this study, RapidPlan demonstrated robustness for moderate proportions of salivary gland dosimetric outliers.