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HomeRadiologyVol. 306, No. 1 PreviousNext Reviews and CommentaryEditorialArtificial Intelligence Outperforms Radiologists for Pancreatic Cancer Lymph Node Metastasis Prediction at CTLinda C. Chu , Elliot K. FishmanLinda C. Chu , Elliot K. FishmanAuthor AffiliationsFrom the Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Hal B168, 600 N Wolfe St, Baltimore, MD 21287.Address correspondence to L.C.C. (email: [email protected]).Linda C. Chu Elliot K. FishmanPublished Online:Sep 6 2022https://doi.org/10.1148/radiol.222012MoreSectionsFull textPDF ToolsImage ViewerAdd to favoritesCiteTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinked In References1. Grossberg AJ, Chu LC, Deig CR, et al. Multidisciplinary standards of care and recent progress in pancreatic ductal adenocarcinoma. CA Cancer J Clin 2020;70(5):375–403. Crossref, Medline, Google Scholar2. Groot VP, Rezaee N, Wu W, et al. Patterns, Timing, and Predictors of Recurrence Following Pancreatectomy for Pancreatic Ductal Adenocarcinoma. Ann Surg 2018;267(5):936–945. Crossref, Medline, Google Scholar3. Tseng DS, van Santvoort HC, Fegrachi S, et al. Diagnostic accuracy of CT in assessing extra-regional lymphadenopathy in pancreatic and peri-ampullary cancer: a systematic review and meta-analysis. Surg Oncol 2014;23(4):229–235. Crossref, Medline, Google Scholar4. Bian Y, Guo S, Jiang H, et al. Relationship Between Radiomics and Risk of Lymph Node Metastasis in Pancreatic Ductal Adenocarcinoma. Pancreas 2019;48(9):1195–1203. Crossref, Medline, Google Scholar5. Li K, Yao Q, Xiao J, et al. Contrast-enhanced CT radiomics for predicting lymph node metastasis in pancreatic ductal adenocarcinoma: a pilot study. Cancer Imaging 2020;20(1):12. Crossref, Medline, Google Scholar6. Shi L, Wang L, Wu C, Wei Y, Zhang Y, Chen J. Preoperative Prediction of Lymph Node Metastasis of Pancreatic Ductal Adenocarcinoma Based on a Radiomics Nomogram of Dual-Parametric MRI Imaging. Front Oncol 2022;12:927077. Crossref, Medline, Google Scholar7. Bian Y, Guo S, Jiang H, et al. Radiomics nomogram for the preoperative prediction of lymph node metastasis in pancreatic ductal adenocarcinoma. Cancer Imaging 2022;22(1):4. Crossref, Medline, Google Scholar8. Bian Y, Zheng Z, Fang X, et al. Artificial Intelligence to Predict Lymph Node Metastasis at CT in Pancreatic Ductal Adenocarcinoma. Radiology 2023;306(1):160–169. Abstract, Google Scholar9. Yao J, Cao K, Hou Y, et al. Deep Learning for Fully Automated Prediction of Overall Survival in Patients Undergoing Resection for Pancreatic Cancer: A Retrospective Multicenter Study. Ann Surg 2022.https://doi.org/10.1097/SLA.0000000000005465. Published online July 4, 2022. Crossref, Google Scholar10. Mukherjee S, Patra A, Khasawneh H, et al. Radiomics-Based Machine-Learning Models Can Detect Pancreatic Cancer on Prediagnostic CTs at a Substantial Lead Time Prior to Clinical Diagnosis. Gastroenterology 2022.https://doi.org/10.1053/j.gastro.2022.06.066. Published online July 1, 2022. Crossref, Google ScholarArticle HistoryReceived: Aug 9 2022Revision requested: Aug 15 2022Revision received: Aug 17 2022Accepted: Aug 19 2022Published online: Sept 06 2022Published in print: Jan 2023 FiguresReferencesRelatedDetailsAccompanying This ArticleArtificial Intelligence to Predict Lymph Node Metastasis at CT in Pancreatic Ductal AdenocarcinomaSep 6 2022RadiologyRecommended Articles Artificial Intelligence to Predict Lymph Node Metastasis at CT in Pancreatic Ductal AdenocarcinomaRadiology2022Volume: 306Issue: 1pp. 160-169Imaging-based Risk Scores for Treatment Selection in Early Pancreatic Cancer: A Step Forward for Tailored TreatmentRadiology2020Volume: 296Issue: 3pp. 552-553Percutaneous Irreversible Electroporation in Locally Advanced and Recurrent Pancreatic Cancer (PANFIRE-2): A Multicenter, Prospective, Single-Arm, Phase II StudyRadiology2019Volume: 294Issue: 1pp. 212-220Radiomics for CT Assessment of Vascular Contact in Pancreatic AdenocarcinomaRadiology2021Volume: 301Issue: 3pp. 623-624Preoperative CT Classification of the Resectability of Pancreatic Cancer: Interobserver AgreementRadiology2019Volume: 293Issue: 2pp. 343-349See More RSNA Education Exhibits Artificial Intelligence for Early Detection of Pancreatic Cancer: Preliminary Observations and ChallengesDigital Posters2019Pancreatic Cancer Imaging: A New Look at an Old ProblemDigital Posters2019A Multidisciplinary Approach for Program Development with Artificial Intelligence in Pancreatic Cancer: How We Fit InDigital Posters2019 RSNA Case Collection Krukenberg TumorsRSNA Case Collection2021Pancreatic lymphomaRSNA Case Collection2020Secondary Angiosarcoma of the BreastRSNA Case Collection2021 Vol. 306, No. 1 Metrics Altmetric Score PDF download