Int J Radiat Oncol Biol Phys 2021 Mar 9;109(4):1096-1110. Epub 2020 Nov 9.
Department of Imaging Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas; Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas.
Purpose: This study investigated deep learning models for automatic segmentation to support the development of daily online dose optimization strategies, eliminating the need for internal target volume expansions and thereby reducing toxicity events of intensity modulated radiation therapy for cervical cancer.
Methods And Materials: The cervix-uterus, vagina, parametrium, bladder, rectum, sigmoid, femoral heads, kidneys, spinal cord, and bowel bag were delineated on 408 computed tomography (CT) scans from patients treated at MD Anderson Cancer Center (n = 214), Polyclinique Bordeaux Nord Aquitaine (n = 30), and enrolled in a Medical Image Computing & Computer Assisted Intervention challenge (n = 3). The data were divided into 255 training, 61 validation, 62 internal test, and 30 external test CT scans. Read More