Radiol Imaging Cancer 2021 Jul;3(4):e210010
From the Department of Medical Imaging (P.T.C., K.L.L.) and Division of Gastroenterology and Hepatology, Department of Internal Medicine (M.S.W., W.C.L.), National Taiwan University Hospital, National Taiwan University College of Medicine, No. 7, Chung-Shan South Road, Taipei 10002, Taiwan; Institute of Applied Mathematical Sciences, National Taiwan University, Taipei, Taiwan (D.C., W.W.); Graduate Program of Data Science, National Taiwan University and Academia Sinica, Taipei, Taiwan (H.Y.); Institute of Statistical Science, Academia Sinica, Taipei, Taiwan (S.Y.H.); NVIDIA, Bethesda, Md (H.R.); and Department of Medical Imaging, National Taiwan University Cancer Center, Taipei, Taiwan (K.L.L.).
Purpose To identify distinguishing CT radiomic features of pancreatic ductal adenocarcinoma (PDAC) and to investigate whether radiomic analysis with machine learning can distinguish between patients who have PDAC and those who do not. Materials and Methods This retrospective study included contrast material-enhanced CT images in 436 patients with PDAC and 479 healthy controls from 2012 to 2018 from Taiwan that were randomly divided for training and testing. Another 100 patients with PDAC (enriched for small PDACs) and 100 controls from Taiwan were identified for testing (from 2004 to 2011). Read More