Brachytherapy (BT) consists in the insertion of radioactive implants directly into the tissue through an applicator, in order to kill tumor cells. This is for the tumor tissue to receive a higher dose, whereas the surrounding normal tissues receive a lower dose of radiation because of the rapid fall of the dose. Because of the special anatomical position of the cervix, smaller organ mobility, and higher tolerable doses of radiotherapy in the vagina and uterus, BT has been most widely used to treat cervical cancer and is an important part of radical radiotherapy for this type of cancer. Furthermore, it is closely related to the prognosis of patients. However, the treatment process, including target area delineation, applicator reconstruction, plan design, and optimization, is time-consuming, which may lead to changes in patient's bladder filling or gastrointestinal peristalsis. Therefore, this not only yields a poor patient experience, but may also affect the accuracy of the treatment and prognosis. With the development of computer hardware, deep learning has been gradually applied in different fields and different networks have been developed to solve various problems. By combining deep learning technology with three-dimensional BT technology, the automation of BT planning can be realized, which, in turn, can significantly shorten the treatment time, alleviate the pain of the patient, and improve treatment efficacy. This article summarizes and gives the prospects of the application of artificial intelligence in the context of BT for cervical cancer.
Keywords: Artificial Intelligence; brachytherapy; cervical cancer.