title: Effect of Dosimetric Outliers on the Performance of a Commercial Knowledge-Based Planning Solution.
abstract: OBJECTIVE
  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
  Clinical plans from 70 head and neck cancer patients comprised the uncleaned (UC) ModelUC, from which outliers were cleaned (C) to create ModelC. The last 5 to 40 patients of ModelC were replanned with no attempt to spare the salivary glands. These substantial dosimetric outliers were reintroduced to the model in increments of 5, creating Model5 to Model40 (Model5-40). These models were used to create plans for a 10-patient evaluation group. Plans from ModelUC and ModelC, and ModelC and Model5-40 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 (ModelC vs ModelUC) 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). Model5-10 marginally improved compsal sparing, whereas adding a larger number of outliers (Model20-40) 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.
authors: Department of Radiotherapy, VU University Medical Center, Amsterdam, The Netherlands. Electronic address: a.delaney@vumc.nl.
authors: Alexander R
authors: AR
authors: Delaney
authors: Department of Radiotherapy, VU University Medical Center, Amsterdam, The Netherlands.
authors: Jim P
authors: JP
authors: Tol
authors: Department of Radiotherapy, VU University Medical Center, Amsterdam, The Netherlands.
authors: Max
authors: M
authors: Dahele
authors: Department of Radiotherapy, VU University Medical Center, Amsterdam, The Netherlands.
authors: Johan
authors: J
authors: Cuijpers
authors: Department of Radiotherapy, VU University Medical Center, Amsterdam, The Netherlands.
authors: Ben J
authors: BJ
authors: Slotman
authors: Department of Radiotherapy, VU University Medical Center, Amsterdam, The Netherlands.
authors: Wilko F A R
authors: WF
authors: Verbakel
mesh_terms: D006258:Head and Neck Neoplasms / Q000532:radiotherapy*; D006801:Humans; D015233:Models, Statistical; D009055:Mouth; D059351:Organ Sparing Treatments / Q000379:methods; D058958:Organs at Risk; D011879:Radiotherapy Dosage; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods* / Q000592:standards; D012044:Regression Analysis; D012469:Salivary Glands