Standalone AI for Breast Cancer Detection at Screening Digital Mammography and Digital Breast Tomosynthesis: A Systematic Review and Meta-Analysis

Background There is considerable interest in the potential use of artificial intelligence (AI) systems in mammographic screening. However, it is essential to critically evaluate the performance of AI before it can become a modality used for independent mammographic interpretation. Purpose To evaluat...

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Published in:Radiology Vol. 307; no. 5; p. e222639
Main Authors: Yoon, Jung Hyun, Strand, Fredrik, Baltzer, Pascal A T, Conant, Emily F, Gilbert, Fiona J, Lehman, Constance D, Morris, Elizabeth A, Mullen, Lisa A, Nishikawa, Robert M, Sharma, Nisha, Vejborg, Ilse, Moy, Linda, Mann, Ritse M
Format: Journal Article
Language:English
Published: United States 01.06.2023
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ISSN:1527-1315, 1527-1315
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Abstract Background There is considerable interest in the potential use of artificial intelligence (AI) systems in mammographic screening. However, it is essential to critically evaluate the performance of AI before it can become a modality used for independent mammographic interpretation. Purpose To evaluate the reported standalone performances of AI for interpretation of digital mammography and digital breast tomosynthesis (DBT). Materials and Methods A systematic search was conducted in PubMed, Google Scholar, Embase (Ovid), and Web of Science databases for studies published from January 2017 to June 2022. Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) values were reviewed. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 and Comparative (QUADAS-2 and QUADAS-C, respectively). A random effects meta-analysis and meta-regression analysis were performed for overall studies and for different study types (reader studies vs historic cohort studies) and imaging techniques (digital mammography vs DBT). Results In total, 16 studies that include 1 108 328 examinations in 497 091 women were analyzed (six reader studies, seven historic cohort studies on digital mammography, and four studies on DBT). Pooled AUCs were significantly higher for standalone AI than radiologists in the six reader studies on digital mammography (0.87 vs 0.81, = .002), but not for historic cohort studies (0.89 vs 0.96, = .152). Four studies on DBT showed significantly higher AUCs in AI compared with radiologists (0.90 vs 0.79, < .001). Higher sensitivity and lower specificity were seen for standalone AI compared with radiologists. Conclusion Standalone AI for screening digital mammography performed as well as or better than radiologists. Compared with digital mammography, there is an insufficient number of studies to assess the performance of AI systems in the interpretation of DBT screening examinations. © RSNA, 2023 See also the editorial by Scaranelo in this issue.
AbstractList Background There is considerable interest in the potential use of artificial intelligence (AI) systems in mammographic screening. However, it is essential to critically evaluate the performance of AI before it can become a modality used for independent mammographic interpretation. Purpose To evaluate the reported standalone performances of AI for interpretation of digital mammography and digital breast tomosynthesis (DBT). Materials and Methods A systematic search was conducted in PubMed, Google Scholar, Embase (Ovid), and Web of Science databases for studies published from January 2017 to June 2022. Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) values were reviewed. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 and Comparative (QUADAS-2 and QUADAS-C, respectively). A random effects meta-analysis and meta-regression analysis were performed for overall studies and for different study types (reader studies vs historic cohort studies) and imaging techniques (digital mammography vs DBT). Results In total, 16 studies that include 1 108 328 examinations in 497 091 women were analyzed (six reader studies, seven historic cohort studies on digital mammography, and four studies on DBT). Pooled AUCs were significantly higher for standalone AI than radiologists in the six reader studies on digital mammography (0.87 vs 0.81, P = .002), but not for historic cohort studies (0.89 vs 0.96, P = .152). Four studies on DBT showed significantly higher AUCs in AI compared with radiologists (0.90 vs 0.79, P < .001). Higher sensitivity and lower specificity were seen for standalone AI compared with radiologists. Conclusion Standalone AI for screening digital mammography performed as well as or better than radiologists. Compared with digital mammography, there is an insufficient number of studies to assess the performance of AI systems in the interpretation of DBT screening examinations. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Scaranelo in this issue.Background There is considerable interest in the potential use of artificial intelligence (AI) systems in mammographic screening. However, it is essential to critically evaluate the performance of AI before it can become a modality used for independent mammographic interpretation. Purpose To evaluate the reported standalone performances of AI for interpretation of digital mammography and digital breast tomosynthesis (DBT). Materials and Methods A systematic search was conducted in PubMed, Google Scholar, Embase (Ovid), and Web of Science databases for studies published from January 2017 to June 2022. Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) values were reviewed. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 and Comparative (QUADAS-2 and QUADAS-C, respectively). A random effects meta-analysis and meta-regression analysis were performed for overall studies and for different study types (reader studies vs historic cohort studies) and imaging techniques (digital mammography vs DBT). Results In total, 16 studies that include 1 108 328 examinations in 497 091 women were analyzed (six reader studies, seven historic cohort studies on digital mammography, and four studies on DBT). Pooled AUCs were significantly higher for standalone AI than radiologists in the six reader studies on digital mammography (0.87 vs 0.81, P = .002), but not for historic cohort studies (0.89 vs 0.96, P = .152). Four studies on DBT showed significantly higher AUCs in AI compared with radiologists (0.90 vs 0.79, P < .001). Higher sensitivity and lower specificity were seen for standalone AI compared with radiologists. Conclusion Standalone AI for screening digital mammography performed as well as or better than radiologists. Compared with digital mammography, there is an insufficient number of studies to assess the performance of AI systems in the interpretation of DBT screening examinations. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Scaranelo in this issue.
Background There is considerable interest in the potential use of artificial intelligence (AI) systems in mammographic screening. However, it is essential to critically evaluate the performance of AI before it can become a modality used for independent mammographic interpretation. Purpose To evaluate the reported standalone performances of AI for interpretation of digital mammography and digital breast tomosynthesis (DBT). Materials and Methods A systematic search was conducted in PubMed, Google Scholar, Embase (Ovid), and Web of Science databases for studies published from January 2017 to June 2022. Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) values were reviewed. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 and Comparative (QUADAS-2 and QUADAS-C, respectively). A random effects meta-analysis and meta-regression analysis were performed for overall studies and for different study types (reader studies vs historic cohort studies) and imaging techniques (digital mammography vs DBT). Results In total, 16 studies that include 1 108 328 examinations in 497 091 women were analyzed (six reader studies, seven historic cohort studies on digital mammography, and four studies on DBT). Pooled AUCs were significantly higher for standalone AI than radiologists in the six reader studies on digital mammography (0.87 vs 0.81, = .002), but not for historic cohort studies (0.89 vs 0.96, = .152). Four studies on DBT showed significantly higher AUCs in AI compared with radiologists (0.90 vs 0.79, < .001). Higher sensitivity and lower specificity were seen for standalone AI compared with radiologists. Conclusion Standalone AI for screening digital mammography performed as well as or better than radiologists. Compared with digital mammography, there is an insufficient number of studies to assess the performance of AI systems in the interpretation of DBT screening examinations. © RSNA, 2023 See also the editorial by Scaranelo in this issue.
Author Baltzer, Pascal A T
Sharma, Nisha
Yoon, Jung Hyun
Conant, Emily F
Strand, Fredrik
Mann, Ritse M
Morris, Elizabeth A
Lehman, Constance D
Nishikawa, Robert M
Gilbert, Fiona J
Moy, Linda
Vejborg, Ilse
Mullen, Lisa A
Author_xml – sequence: 1
  givenname: Jung Hyun
  orcidid: 0000-0002-2100-3513
  surname: Yoon
  fullname: Yoon, Jung Hyun
  organization: From the Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University, College of Medicine, 50 Yonsei-ro, Seodaemun-gu, 03722 Seoul, Korea (J.H.Y.); Department of Oncology and Pathology, Karolinska Institute, Stockholm, Sweden (F.S.); Department of Radiology, Unit of Breast Imaging, Karolinska University Hospital, Stockholm, Sweden (F.S.); Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (P.A.T.B.); Department of Radiology, University of Pennsylvania, Philadelphia, Pa (E.F.C.); Department of Radiology, University of Cambridge, Cambridge, UK (F.J.G.); Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Boston, Mass (C.D.L.); Department of Radiology, University of California Davis, Davis, Calif (E.A.M.); Department of Radiology, Breast Imaging Division, Johns Hopkins Medicine, Baltimore, Md (L.A.M.); Department of Radiology, University of Pittsburgh, UPMC Magee-Womens Hospital, Pittsburgh, Pa (R.M.N.); Department of Radiology, St James Hospital, Leeds, UK (N.S.); Department of Breast Examinations, Copenhagen University Hospital Herlev-Gentofte, Copenhagen, Denmark (I.V.); Department of Radiology, Laura and Isaac Perlmutter Cancer Center, Center for Biomedical Imaging, Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York, NY (L.M.); Department of Medical Imaging, Radboud University Medical Center, Nijmegen, the Netherlands (R.M.M.); and Department of Radiology, Netherlands Cancer Institute, Amsterdam, the Netherlands (R.M.M.)
– sequence: 2
  givenname: Fredrik
  orcidid: 0000-0003-3910-7086
  surname: Strand
  fullname: Strand, Fredrik
  organization: From the Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University, College of Medicine, 50 Yonsei-ro, Seodaemun-gu, 03722 Seoul, Korea (J.H.Y.); Department of Oncology and Pathology, Karolinska Institute, Stockholm, Sweden (F.S.); Department of Radiology, Unit of Breast Imaging, Karolinska University Hospital, Stockholm, Sweden (F.S.); Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (P.A.T.B.); Department of Radiology, University of Pennsylvania, Philadelphia, Pa (E.F.C.); Department of Radiology, University of Cambridge, Cambridge, UK (F.J.G.); Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Boston, Mass (C.D.L.); Department of Radiology, University of California Davis, Davis, Calif (E.A.M.); Department of Radiology, Breast Imaging Division, Johns Hopkins Medicine, Baltimore, Md (L.A.M.); Department of Radiology, University of Pittsburgh, UPMC Magee-Womens Hospital, Pittsburgh, Pa (R.M.N.); Department of Radiology, St James Hospital, Leeds, UK (N.S.); Department of Breast Examinations, Copenhagen University Hospital Herlev-Gentofte, Copenhagen, Denmark (I.V.); Department of Radiology, Laura and Isaac Perlmutter Cancer Center, Center for Biomedical Imaging, Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York, NY (L.M.); Department of Medical Imaging, Radboud University Medical Center, Nijmegen, the Netherlands (R.M.M.); and Department of Radiology, Netherlands Cancer Institute, Amsterdam, the Netherlands (R.M.M.)
– sequence: 3
  givenname: Pascal A T
  orcidid: 0000-0002-3755-5398
  surname: Baltzer
  fullname: Baltzer, Pascal A T
  organization: From the Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University, College of Medicine, 50 Yonsei-ro, Seodaemun-gu, 03722 Seoul, Korea (J.H.Y.); Department of Oncology and Pathology, Karolinska Institute, Stockholm, Sweden (F.S.); Department of Radiology, Unit of Breast Imaging, Karolinska University Hospital, Stockholm, Sweden (F.S.); Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (P.A.T.B.); Department of Radiology, University of Pennsylvania, Philadelphia, Pa (E.F.C.); Department of Radiology, University of Cambridge, Cambridge, UK (F.J.G.); Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Boston, Mass (C.D.L.); Department of Radiology, University of California Davis, Davis, Calif (E.A.M.); Department of Radiology, Breast Imaging Division, Johns Hopkins Medicine, Baltimore, Md (L.A.M.); Department of Radiology, University of Pittsburgh, UPMC Magee-Womens Hospital, Pittsburgh, Pa (R.M.N.); Department of Radiology, St James Hospital, Leeds, UK (N.S.); Department of Breast Examinations, Copenhagen University Hospital Herlev-Gentofte, Copenhagen, Denmark (I.V.); Department of Radiology, Laura and Isaac Perlmutter Cancer Center, Center for Biomedical Imaging, Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York, NY (L.M.); Department of Medical Imaging, Radboud University Medical Center, Nijmegen, the Netherlands (R.M.M.); and Department of Radiology, Netherlands Cancer Institute, Amsterdam, the Netherlands (R.M.M.)
– sequence: 4
  givenname: Emily F
  orcidid: 0000-0001-9331-644X
  surname: Conant
  fullname: Conant, Emily F
  organization: From the Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University, College of Medicine, 50 Yonsei-ro, Seodaemun-gu, 03722 Seoul, Korea (J.H.Y.); Department of Oncology and Pathology, Karolinska Institute, Stockholm, Sweden (F.S.); Department of Radiology, Unit of Breast Imaging, Karolinska University Hospital, Stockholm, Sweden (F.S.); Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (P.A.T.B.); Department of Radiology, University of Pennsylvania, Philadelphia, Pa (E.F.C.); Department of Radiology, University of Cambridge, Cambridge, UK (F.J.G.); Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Boston, Mass (C.D.L.); Department of Radiology, University of California Davis, Davis, Calif (E.A.M.); Department of Radiology, Breast Imaging Division, Johns Hopkins Medicine, Baltimore, Md (L.A.M.); Department of Radiology, University of Pittsburgh, UPMC Magee-Womens Hospital, Pittsburgh, Pa (R.M.N.); Department of Radiology, St James Hospital, Leeds, UK (N.S.); Department of Breast Examinations, Copenhagen University Hospital Herlev-Gentofte, Copenhagen, Denmark (I.V.); Department of Radiology, Laura and Isaac Perlmutter Cancer Center, Center for Biomedical Imaging, Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York, NY (L.M.); Department of Medical Imaging, Radboud University Medical Center, Nijmegen, the Netherlands (R.M.M.); and Department of Radiology, Netherlands Cancer Institute, Amsterdam, the Netherlands (R.M.M.)
– sequence: 5
  givenname: Fiona J
  surname: Gilbert
  fullname: Gilbert, Fiona J
  organization: From the Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University, College of Medicine, 50 Yonsei-ro, Seodaemun-gu, 03722 Seoul, Korea (J.H.Y.); Department of Oncology and Pathology, Karolinska Institute, Stockholm, Sweden (F.S.); Department of Radiology, Unit of Breast Imaging, Karolinska University Hospital, Stockholm, Sweden (F.S.); Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (P.A.T.B.); Department of Radiology, University of Pennsylvania, Philadelphia, Pa (E.F.C.); Department of Radiology, University of Cambridge, Cambridge, UK (F.J.G.); Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Boston, Mass (C.D.L.); Department of Radiology, University of California Davis, Davis, Calif (E.A.M.); Department of Radiology, Breast Imaging Division, Johns Hopkins Medicine, Baltimore, Md (L.A.M.); Department of Radiology, University of Pittsburgh, UPMC Magee-Womens Hospital, Pittsburgh, Pa (R.M.N.); Department of Radiology, St James Hospital, Leeds, UK (N.S.); Department of Breast Examinations, Copenhagen University Hospital Herlev-Gentofte, Copenhagen, Denmark (I.V.); Department of Radiology, Laura and Isaac Perlmutter Cancer Center, Center for Biomedical Imaging, Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York, NY (L.M.); Department of Medical Imaging, Radboud University Medical Center, Nijmegen, the Netherlands (R.M.M.); and Department of Radiology, Netherlands Cancer Institute, Amsterdam, the Netherlands (R.M.M.)
– sequence: 6
  givenname: Constance D
  orcidid: 0000-0001-5839-6675
  surname: Lehman
  fullname: Lehman, Constance D
  organization: From the Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University, College of Medicine, 50 Yonsei-ro, Seodaemun-gu, 03722 Seoul, Korea (J.H.Y.); Department of Oncology and Pathology, Karolinska Institute, Stockholm, Sweden (F.S.); Department of Radiology, Unit of Breast Imaging, Karolinska University Hospital, Stockholm, Sweden (F.S.); Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (P.A.T.B.); Department of Radiology, University of Pennsylvania, Philadelphia, Pa (E.F.C.); Department of Radiology, University of Cambridge, Cambridge, UK (F.J.G.); Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Boston, Mass (C.D.L.); Department of Radiology, University of California Davis, Davis, Calif (E.A.M.); Department of Radiology, Breast Imaging Division, Johns Hopkins Medicine, Baltimore, Md (L.A.M.); Department of Radiology, University of Pittsburgh, UPMC Magee-Womens Hospital, Pittsburgh, Pa (R.M.N.); Department of Radiology, St James Hospital, Leeds, UK (N.S.); Department of Breast Examinations, Copenhagen University Hospital Herlev-Gentofte, Copenhagen, Denmark (I.V.); Department of Radiology, Laura and Isaac Perlmutter Cancer Center, Center for Biomedical Imaging, Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York, NY (L.M.); Department of Medical Imaging, Radboud University Medical Center, Nijmegen, the Netherlands (R.M.M.); and Department of Radiology, Netherlands Cancer Institute, Amsterdam, the Netherlands (R.M.M.)
– sequence: 7
  givenname: Elizabeth A
  orcidid: 0000-0001-5069-0992
  surname: Morris
  fullname: Morris, Elizabeth A
  organization: From the Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University, College of Medicine, 50 Yonsei-ro, Seodaemun-gu, 03722 Seoul, Korea (J.H.Y.); Department of Oncology and Pathology, Karolinska Institute, Stockholm, Sweden (F.S.); Department of Radiology, Unit of Breast Imaging, Karolinska University Hospital, Stockholm, Sweden (F.S.); Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (P.A.T.B.); Department of Radiology, University of Pennsylvania, Philadelphia, Pa (E.F.C.); Department of Radiology, University of Cambridge, Cambridge, UK (F.J.G.); Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Boston, Mass (C.D.L.); Department of Radiology, University of California Davis, Davis, Calif (E.A.M.); Department of Radiology, Breast Imaging Division, Johns Hopkins Medicine, Baltimore, Md (L.A.M.); Department of Radiology, University of Pittsburgh, UPMC Magee-Womens Hospital, Pittsburgh, Pa (R.M.N.); Department of Radiology, St James Hospital, Leeds, UK (N.S.); Department of Breast Examinations, Copenhagen University Hospital Herlev-Gentofte, Copenhagen, Denmark (I.V.); Department of Radiology, Laura and Isaac Perlmutter Cancer Center, Center for Biomedical Imaging, Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York, NY (L.M.); Department of Medical Imaging, Radboud University Medical Center, Nijmegen, the Netherlands (R.M.M.); and Department of Radiology, Netherlands Cancer Institute, Amsterdam, the Netherlands (R.M.M.)
– sequence: 8
  givenname: Lisa A
  orcidid: 0000-0003-3191-2865
  surname: Mullen
  fullname: Mullen, Lisa A
  organization: From the Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University, College of Medicine, 50 Yonsei-ro, Seodaemun-gu, 03722 Seoul, Korea (J.H.Y.); Department of Oncology and Pathology, Karolinska Institute, Stockholm, Sweden (F.S.); Department of Radiology, Unit of Breast Imaging, Karolinska University Hospital, Stockholm, Sweden (F.S.); Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (P.A.T.B.); Department of Radiology, University of Pennsylvania, Philadelphia, Pa (E.F.C.); Department of Radiology, University of Cambridge, Cambridge, UK (F.J.G.); Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Boston, Mass (C.D.L.); Department of Radiology, University of California Davis, Davis, Calif (E.A.M.); Department of Radiology, Breast Imaging Division, Johns Hopkins Medicine, Baltimore, Md (L.A.M.); Department of Radiology, University of Pittsburgh, UPMC Magee-Womens Hospital, Pittsburgh, Pa (R.M.N.); Department of Radiology, St James Hospital, Leeds, UK (N.S.); Department of Breast Examinations, Copenhagen University Hospital Herlev-Gentofte, Copenhagen, Denmark (I.V.); Department of Radiology, Laura and Isaac Perlmutter Cancer Center, Center for Biomedical Imaging, Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York, NY (L.M.); Department of Medical Imaging, Radboud University Medical Center, Nijmegen, the Netherlands (R.M.M.); and Department of Radiology, Netherlands Cancer Institute, Amsterdam, the Netherlands (R.M.M.)
– sequence: 9
  givenname: Robert M
  orcidid: 0000-0001-7720-9951
  surname: Nishikawa
  fullname: Nishikawa, Robert M
  organization: From the Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University, College of Medicine, 50 Yonsei-ro, Seodaemun-gu, 03722 Seoul, Korea (J.H.Y.); Department of Oncology and Pathology, Karolinska Institute, Stockholm, Sweden (F.S.); Department of Radiology, Unit of Breast Imaging, Karolinska University Hospital, Stockholm, Sweden (F.S.); Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (P.A.T.B.); Department of Radiology, University of Pennsylvania, Philadelphia, Pa (E.F.C.); Department of Radiology, University of Cambridge, Cambridge, UK (F.J.G.); Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Boston, Mass (C.D.L.); Department of Radiology, University of California Davis, Davis, Calif (E.A.M.); Department of Radiology, Breast Imaging Division, Johns Hopkins Medicine, Baltimore, Md (L.A.M.); Department of Radiology, University of Pittsburgh, UPMC Magee-Womens Hospital, Pittsburgh, Pa (R.M.N.); Department of Radiology, St James Hospital, Leeds, UK (N.S.); Department of Breast Examinations, Copenhagen University Hospital Herlev-Gentofte, Copenhagen, Denmark (I.V.); Department of Radiology, Laura and Isaac Perlmutter Cancer Center, Center for Biomedical Imaging, Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York, NY (L.M.); Department of Medical Imaging, Radboud University Medical Center, Nijmegen, the Netherlands (R.M.M.); and Department of Radiology, Netherlands Cancer Institute, Amsterdam, the Netherlands (R.M.M.)
– sequence: 10
  givenname: Nisha
  orcidid: 0000-0003-3991-0768
  surname: Sharma
  fullname: Sharma, Nisha
  organization: From the Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University, College of Medicine, 50 Yonsei-ro, Seodaemun-gu, 03722 Seoul, Korea (J.H.Y.); Department of Oncology and Pathology, Karolinska Institute, Stockholm, Sweden (F.S.); Department of Radiology, Unit of Breast Imaging, Karolinska University Hospital, Stockholm, Sweden (F.S.); Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (P.A.T.B.); Department of Radiology, University of Pennsylvania, Philadelphia, Pa (E.F.C.); Department of Radiology, University of Cambridge, Cambridge, UK (F.J.G.); Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Boston, Mass (C.D.L.); Department of Radiology, University of California Davis, Davis, Calif (E.A.M.); Department of Radiology, Breast Imaging Division, Johns Hopkins Medicine, Baltimore, Md (L.A.M.); Department of Radiology, University of Pittsburgh, UPMC Magee-Womens Hospital, Pittsburgh, Pa (R.M.N.); Department of Radiology, St James Hospital, Leeds, UK (N.S.); Department of Breast Examinations, Copenhagen University Hospital Herlev-Gentofte, Copenhagen, Denmark (I.V.); Department of Radiology, Laura and Isaac Perlmutter Cancer Center, Center for Biomedical Imaging, Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York, NY (L.M.); Department of Medical Imaging, Radboud University Medical Center, Nijmegen, the Netherlands (R.M.M.); and Department of Radiology, Netherlands Cancer Institute, Amsterdam, the Netherlands (R.M.M.)
– sequence: 11
  givenname: Ilse
  orcidid: 0000-0002-2329-203X
  surname: Vejborg
  fullname: Vejborg, Ilse
  organization: From the Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University, College of Medicine, 50 Yonsei-ro, Seodaemun-gu, 03722 Seoul, Korea (J.H.Y.); Department of Oncology and Pathology, Karolinska Institute, Stockholm, Sweden (F.S.); Department of Radiology, Unit of Breast Imaging, Karolinska University Hospital, Stockholm, Sweden (F.S.); Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (P.A.T.B.); Department of Radiology, University of Pennsylvania, Philadelphia, Pa (E.F.C.); Department of Radiology, University of Cambridge, Cambridge, UK (F.J.G.); Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Boston, Mass (C.D.L.); Department of Radiology, University of California Davis, Davis, Calif (E.A.M.); Department of Radiology, Breast Imaging Division, Johns Hopkins Medicine, Baltimore, Md (L.A.M.); Department of Radiology, University of Pittsburgh, UPMC Magee-Womens Hospital, Pittsburgh, Pa (R.M.N.); Department of Radiology, St James Hospital, Leeds, UK (N.S.); Department of Breast Examinations, Copenhagen University Hospital Herlev-Gentofte, Copenhagen, Denmark (I.V.); Department of Radiology, Laura and Isaac Perlmutter Cancer Center, Center for Biomedical Imaging, Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York, NY (L.M.); Department of Medical Imaging, Radboud University Medical Center, Nijmegen, the Netherlands (R.M.M.); and Department of Radiology, Netherlands Cancer Institute, Amsterdam, the Netherlands (R.M.M.)
– sequence: 12
  givenname: Linda
  orcidid: 0000-0001-9564-9360
  surname: Moy
  fullname: Moy, Linda
  organization: From the Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University, College of Medicine, 50 Yonsei-ro, Seodaemun-gu, 03722 Seoul, Korea (J.H.Y.); Department of Oncology and Pathology, Karolinska Institute, Stockholm, Sweden (F.S.); Department of Radiology, Unit of Breast Imaging, Karolinska University Hospital, Stockholm, Sweden (F.S.); Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (P.A.T.B.); Department of Radiology, University of Pennsylvania, Philadelphia, Pa (E.F.C.); Department of Radiology, University of Cambridge, Cambridge, UK (F.J.G.); Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Boston, Mass (C.D.L.); Department of Radiology, University of California Davis, Davis, Calif (E.A.M.); Department of Radiology, Breast Imaging Division, Johns Hopkins Medicine, Baltimore, Md (L.A.M.); Department of Radiology, University of Pittsburgh, UPMC Magee-Womens Hospital, Pittsburgh, Pa (R.M.N.); Department of Radiology, St James Hospital, Leeds, UK (N.S.); Department of Breast Examinations, Copenhagen University Hospital Herlev-Gentofte, Copenhagen, Denmark (I.V.); Department of Radiology, Laura and Isaac Perlmutter Cancer Center, Center for Biomedical Imaging, Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York, NY (L.M.); Department of Medical Imaging, Radboud University Medical Center, Nijmegen, the Netherlands (R.M.M.); and Department of Radiology, Netherlands Cancer Institute, Amsterdam, the Netherlands (R.M.M.)
– sequence: 13
  givenname: Ritse M
  orcidid: 0000-0001-8111-1930
  surname: Mann
  fullname: Mann, Ritse M
  organization: From the Department of Radiology, Severance Hospital, Research Institute of Radiological Science, Yonsei University, College of Medicine, 50 Yonsei-ro, Seodaemun-gu, 03722 Seoul, Korea (J.H.Y.); Department of Oncology and Pathology, Karolinska Institute, Stockholm, Sweden (F.S.); Department of Radiology, Unit of Breast Imaging, Karolinska University Hospital, Stockholm, Sweden (F.S.); Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria (P.A.T.B.); Department of Radiology, University of Pennsylvania, Philadelphia, Pa (E.F.C.); Department of Radiology, University of Cambridge, Cambridge, UK (F.J.G.); Department of Radiology, Harvard Medical School, Massachusetts General Hospital, Boston, Mass (C.D.L.); Department of Radiology, University of California Davis, Davis, Calif (E.A.M.); Department of Radiology, Breast Imaging Division, Johns Hopkins Medicine, Baltimore, Md (L.A.M.); Department of Radiology, University of Pittsburgh, UPMC Magee-Womens Hospital, Pittsburgh, Pa (R.M.N.); Department of Radiology, St James Hospital, Leeds, UK (N.S.); Department of Breast Examinations, Copenhagen University Hospital Herlev-Gentofte, Copenhagen, Denmark (I.V.); Department of Radiology, Laura and Isaac Perlmutter Cancer Center, Center for Biomedical Imaging, Center for Advanced Imaging Innovation and Research, New York University Grossman School of Medicine, New York, NY (L.M.); Department of Medical Imaging, Radboud University Medical Center, Nijmegen, the Netherlands (R.M.M.); and Department of Radiology, Netherlands Cancer Institute, Amsterdam, the Netherlands (R.M.M.)
BackLink https://www.ncbi.nlm.nih.gov/pubmed/37219445$$D View this record in MEDLINE/PubMed
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References 37219442 - Radiology. 2023 Jun;307(5):e230935. doi: 10.1148/radiol.230935.
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Snippet Background There is considerable interest in the potential use of artificial intelligence (AI) systems in mammographic screening. However, it is essential to...
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SubjectTerms Artificial Intelligence
Breast - diagnostic imaging
Breast Neoplasms - diagnostic imaging
Early Detection of Cancer - methods
Female
Humans
Mammography - methods
Retrospective Studies
Title Standalone AI for Breast Cancer Detection at Screening Digital Mammography and Digital Breast Tomosynthesis: A Systematic Review and Meta-Analysis
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