A Deep Learning Model for Predicting Xerostomia Due to Radiation Therapy for Head and Neck Squamous Cell Carcinoma in the RTOG 0522 Clinical Trial.

ABSTRACT:

Purpose

Xerostomia commonly occurs in patients who undergo head and neck radiation therapy and can seriously affect patients' quality of life. In this study, we developed a xerostomia prediction model with radiation treatment data using a 3-dimensional (3D) residual convolutional neural network (rCNN). The model can be used to guide radiation therapy to reduce toxicity.

Methods and materials

A total of 784 patients with head and neck squamous cell carcinoma enrolled in the Radiation Therapy Oncology Group 0522 clinical trial were included in this study. Late xerostomia is defined as xerostomia of grade ≥2 occurring in the 12th month of radiation therapy. The computed tomography (CT) planning images, 3D dose distributions, and contours of the parotid and submandibular glands

SUBMITTER: Men K 

PROVIDER: S-EPMC6732004 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature