Improving plan quality in cervical brachytherapy using a simple knowledge-based prediction tool for OAR dose (D2cm).

PURPOSE

Toxicity from cervical brachytherapy has been demonstrated to correlate with the D2cm of the bladder, rectum, and bowel. This suggests a simplified version of knowledge-based planning investigating the relationship of the overlap distance for 2cm and the D2cm from planning may be possible. This work demonstrates the feasibility of simple knowledge-based planning to predict the D2cm, detect suboptimal plans, and improve plan quality.

METHODS AND MATERIALS

The overlap volume histogram (OVH) method was used to determine the distance for 2cm of overlap between the OAR and CTV_HR. Linear plots modeled the OAR D2cm and 2cm overlap distance. Two datasets of 20 patients (plans from 43 insertions in each dataset) were used to create two independent models, and the performance of each model was compared using cross-validation. Doses were scaled to ensure consistent CTV_HR D90 values. The predicted D2cm is entered as the maximum constraint in the inverse planning algorithm.

RESULTS

Mean bladder D2cm decreased by 2.9% for the models from each dataset, mean rectal D2cm decreased 14.9% for the model from dataset 1 and 6.0% for the model from dataset 2, mean sigmoid D2cm decreased 10.7% for the model from dataset 1 and 6.1% for the model from dataset 2, mean bowel D2cm decreased 4.1% for the model from dataset 1 but no statistically significant difference was observed for the model from dataset 2.

CONCLUSIONS

A simplified knowledge-based planning method was used to predict D2cm and was able to automate optimization of brachytherapy plans for locally advanced cervical cancer.