Background: Here, we investigated the relationship between clinical parameters, including the site of surgical anastomosis and radiation dose to the anastomotic region, and anastomotic complications in esophageal cancer patients treated with trimodality therapy.
Methods: Between 2007 and 2016, esophageal cancer patients treated with trimodality therapy at a tertiary academic cancer center were identified. Patient, treatment, and outcome parameters were collected.
Purpose: Early identification of patients who may be at high risk of significant weight loss (SWL) is important for timely clinical intervention in lung cancer radiotherapy (RT). A clinical decision support system (CDSS) for SWL prediction was implemented within the routine clinical workflow and assessed on a prospective cohort of patients.
Materials And Methods: CDSS incorporated a machine learning prediction model on the basis of radiomics and dosiomics image features and was connected to a web-based dashboard for streamlined patient enrollment, feature extraction, SWL prediction, and physicians' evaluation processes.
Purpose: We investigate whether esophageal dose-length parameters (L) can robustly predict significant weight loss-≥5% weight loss during radiation therapy (RT) compared with the weight before RT-in patients with lung cancer treated with definitive intent.
Methods And Materials: Patients with lung cancer treated with conventionally fractionated RT between 2010 and 2018 were retrospectively identified. L and L, the length of full- and partial-circumferential esophagus receiving greater than a threshold dose in Gy, respectively, were created.