The Use of the Artificial Neural Network for the Treatment Outcomes of Single-channel and Tri-channel Applicator Used in Cervical Cancer Based on High Dose Rate Brachytherapy

Abstract

\n The study aimed to evaluate the treatment outcomes of single-channel and tri-channel applicators for cervical cancer patients based on high dose rate brachytherapy using an artificial neural network. An artificial neural network (ANNs) model is proposed to predict the treatment outcomes for the single-channel applicator and tri-channel applicator in cervical cancer for high dose rate brachytherapy. Fifty-four patients of cervical cancer who were receiving external beam radiation therapy (EBRT) of 40-50 cGy, with chemotherapy, were selected in this study from 37 patients with cervical cancer being used to train and 17 for testing in this model. A model was developed for intracavitary brachytherapy to estimate the comparison of\u3000treatment outcomes for the single-channel applicator and tri-channel applicators, demonstrating the sensitivity 100% and specificity 100 % and accuracy 100% for training and 87.5%, 77.8%, and 82.4% for testing, respectively, including AUC= 0.961. The survival rate was 85% and 95% for single-channel and tri-channel applicators at 2 years, respectively. A model approach for artificial neural networks based on gynecological brachytherapy is a promising method for patient s treatment, resulting in the dosimetry output of applicators; medical physicists can be decided the appropriate applicator for cervical cancer. The proposed model has the potential accuracy in judging the treatment outcomes for the single-channel applicator and tri-channel applicator in cervical cancer based on survival analysis.