SU‐E‐T‐340: Predictive Models for Dosimetry of the Organs‐At‐Risk in Interstitial Gynecologic Brachytherapy

Purpose: In this work, mathematical models for the prediction of the D2cc of rectum and bladder in interstitial gynecologic brachytherapy based on geometric information, without the generation of a treatment plan, are discussed and validated. Methods: Previous plans were used to establish the relationship between D2cc and the overlapping volume of the organ‐at‐risk with the targeted area (C0) or a 1‐cm expansion of the target area (C1). Three mathematical models were evaluated: D2cc = a*C1+b (LIN); D2cc = a — exp(‐b*C0) (EXP); and a mixed approach (MIX), where both C0 and C1 were inputs of the model. The model's parameters were optimized on a training set, and the model predictive error (predicted D2cc — real D2cc) was calculated on a validation set. The data of 20 patients treated with interstitial gynecologic brachytherapy were used to perform a K‐fold cross validation analysis, with K = 2, 4, 6,8, 10, and 20. Results: MIX was associated with the smallest mean prediction error with error <6.4% for an 18‐patient training set; LIN had an error <8.5%; EXP had an error < 8.3%. Best‐case‐scenario analysis showed that an error <5% could be achieved for a 10‐patient training set with MIX, error <7.5% for LIN and error <7.0% for EXP. The error decreases with the increase in training set size, with the most marked decrease observed for MIX. Conclusion: Ten training cases allow the MIX model to predict D2cc for the organs‐at‐risk with an error <5%. While clearly specific to clinical practice, the model can be used in the development of quality assurance tools to identify treatment plans with sub‐optimal sparing of the organs‐at‐risk. It can also be used to improve preplanning and in the development of real‐time intra‐operative planning tools.