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(UC), from which outliers were cleaned (C) to create Model(C). The last 5 to 40 patients of Model(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(5) to Model(40) (Model(5-40)). These models were used to create plans for a 10-patient evaluation group. Plans from Model(UC) and Model(C), and Model(C) and Model(5-40) were compared on the basis of boost (B) and elective (E) target volume homogeneity indexes (HIB/HIE) and mean doses to oral cavity, composite salivary glands (compsal) and swallowing (compswal) structures. Results: On average, outlier removal (Model(C) vs Model(UC)) had minimal effects on HIB/HIE (0%-0.4%) and sparing of organs at risk (mean dose difference to oral cavity and compsal/compswal were <= 0.4 Gy). Model(5-10) marginally improved compsal sparing, whereas adding a larger number of outliers (Model(20-40)) led to deteriorations in compsal 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. (C) 2016 Elsevier Inc. All rights reserved.