Artificial Intelligence Improves Radiologist Performance for Predicting Malignancy at Chest CT

HomeRadiologyVol. 304, No. 3 PreviousNext Reviews and CommentaryEditorialArtificial Intelligence Improves Radiologist Performance for Predicting Malignancy at Chest CTMasahiro Yanagawa Masahiro Yanagawa Author AffiliationsFrom the Department of Radiology, Osaka University Graduate School of Medicine, Yamadaoka, 2-2 Suita, Osaka 565-0871, Japan.Address correspondence to the author (email: [email protected]).Masahiro Yanagawa Published Online:May 24 2022https://doi.org/10.1148/radiol.220571MoreSectionsFull textPDF ToolsImage ViewerAdd to favoritesCiteTrack CitationsPermissionsReprints ShareShare onFacebookTwitterLinked In References1. National Lung Screening Trial Research TeamAberle DR, Adams AM; et al. Reduced lung-cancer mortality with low-dose computed tomographic screening. N Engl J Med 2011;365(5):395–409. Crossref, Medline, Google Scholar2. de Koning HJ, van der Aalst CM, de Jong PA, et al. Reduced Lung-Cancer Mortality with Volume CT Screening in a Randomized Trial. N Engl J Med 2020;382(6):503–513. Crossref, Medline, Google Scholar3. Ost DE, Gould MK . Decision making in patients with pulmonary nodules. Am J Respir Crit Care Med 2012;185(4):363–372. Crossref, Medline, Google Scholar4. Gould MK, Donington J, Lynch WR, et al. Evaluation of individuals with pulmonary nodules: when is it lung cancer? Diagnosis and management of lung cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines. Chest 2013;143(5 Suppl):e93S–e120S. Crossref, Medline, Google Scholar5. Chelala L, Hossain R, Kazerooni EA, Christensen JD, Dyer DS, White CS . Lung-RADS Version 1.1: Challenges and a Look Ahead, From the AJR Special Series on Radiology Reporting and Data Systems. AJR Am J Roentgenol 2021;216(6):1411–1422. Crossref, Medline, Google Scholar6. van Riel SJ, Jacobs C, Scholten ET, et al. Observer variability for Lung-RADS categorisation of lung cancer screening CTs: impact on patient management. Eur Radiol 2019;29(2):924–931. Crossref, Medline, Google Scholar7. Ohno Y, Aoyagi K, Yaguchi A, et al. Differentiation of Benign from Malignant Pulmonary Nodules by Using a Convolutional Neural Network to Determine Volume Change at Chest CT. Radiology 2020;296(2):432–443. Link, Google Scholar8. Dotson TL, Filippini C, Arteta C, Declerck J, Kadir T, Pickup LC, et al. AI-Based Computer-Aided Diagnosis (CADx) Improves Stratification Decisions on Indeterminate Pulmonary Nodules: An MRMC Reader Study. Am J Respir Crit Care Med 2020;201:A7691. Google Scholar9. Kim RY, Oke JL, Pickup LC, et al. Artificial Intelligence Tool for Assessment of Indeterminate Pulmonary Nodules Detected with CT. Radiology 2022;304(3):683–691. Link, Google Scholar10. Ardila D, Kiraly AP, Bharadwaj S, et al. End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography. Nat Med 2019;25(6):954–961 [Published correction appears in Nat Med 2019;25(8):1319.]. Crossref, Medline, Google ScholarArticle HistoryReceived: Mar 10 2022Revision requested: Mar 18 2022Revision received: Mar 19 2022Accepted: Mar 24 2022Published online: May 24 2022Published in print: Sept 2022 FiguresReferencesRelatedDetailsAccompanying This ArticleArtificial Intelligence Tool for Assessment of Indeterminate Pulmonary Nodules Detected with CTMay 24 2022RadiologyRecommended Articles Artificial Intelligence Tool for Assessment of Indeterminate Pulmonary Nodules Detected with CTRadiology2022Volume: 304Issue: 3pp. 683-691Doing Too Much or Not Enough: Striking a BalanceRadiology2021Volume: 300Issue: 1pp. 207-208Low-Dose CT Screening for Lung Cancer: Evidence from 2 Decades of StudyRadiology: Imaging Cancer2020Volume: 2Issue: 2Assessing Pulmonary Nodules by Using Lower Dose at CTRadiology2020Volume: 297Issue: 3pp. 708-709CT Diagnosis of Lung Adenocarcinoma: Radiologic-Pathologic Correlation and Growth RateRadiology2020Volume: 297Issue: 1pp. 199-200See More RSNA Education Exhibits Management of Solitary Pulmonary Nodules: Pushing the Limits Beyond the GuidelinesDigital Posters2019Introduction to Artificial Intelligence and Big Data Research in Chest RadiologyDigital Posters2019Evaluation and Management of Subsolid Nodules (SSNs): From Lung Cancer Screening to Everyday Clinical PracticeDigital Posters2018 RSNA Case Collection Thoracic splenosisRSNA Case Collection2020Granulomatous lymphocytic interstitial lung disease RSNA Case Collection2021Lipoid PneumoniaRSNA Case Collection2021 Vol. 304, No. 3 Metrics Altmetric Score PDF download