Automatic optimization of treatment dosimetry to improve visual outcomes in episcleral plaque brachytherapy.

PURPOSE:The aim of this study was to develop an automated dose optimization algorithm, powered by simulated annealing, for inverse planning of ocular plaque brachytherapy treatments, to improve tumor coverage and critical structure sparing for reduced treatment-related morbidity. METHODS AND MATERIALS:A simulated annealing based algorithm was built and evaluated by finding variable seed strengths that maximized dose uniformity across tumor base for model cases of various tumor heights and plaque sizes. This problem assessed its potential to find the minima in the energy function using differential loading. The algorithm was further developed to decrease doses to critical structures while maintaining desired tumor coverage. Doses to the optic disc and fovea were compared to those using uniform seed strengths for various model cases. Finally, 10 retrospective patient cases treated with uniform seed strengths were replanned with the developed algorithm to evaluate effectiveness for clinical application. RESULTS:The developed algorithm achieved dose reductions of up to 37.3% and 39.6% to the optic disc and fovea, respectively, compared to those using uniform seed strengths, depending on the tumor and plaque size used for the model cases. Applying the algorithm to 10 clinical scenarios resulted in dose reductions of 14% to the optic disc and fovea relative to clinical treatments performed with uniform seed strengths. CONCLUSIONS:The developed automatic dose optimization routine was able to achieve significant dose reductions to the critical structures relative to using uniformly loaded plaques both in the model and in the clinical cases.