Society of Thoracic Radiology Annual Meeting

ABSTRACT

The proceedings contain 111 papers. The topics discussed include implementation of a chest CT educational module for COVID-19 using RedCap software outcomes and applicability for future thoracic imaging education;concurrent biopsy and microwave ablation of suspicious FDG-avid pulmonary nodules a retrospective analysis;coronary artery calcification in COVID-19 patients an imaging biomarker for adverse clinical outcomes;deep convolutional neural networks for detection of cardiomegaly through calculation of cardiothoracic ratio from chest radiographs;clearing the congestion comparison of chest radiography and BNP in the diagnosis of heart failure;human and deep learning quantification of COVID-19 severity on chest X-ray prognosticates hospitalization, intubation, and survival;performance of an artificial intelligence-based platform against clinical radiology reports for the evaluation of non-contrast chest CT;and development of a 3D U-net deep-learning model for automated detection of lung nodules on chest CT images internal and external validation using LIDC and Japanese datasets.