دورية أكاديمية
AI-based Strategies to Reduce Workload in Breast Cancer Screening with Mammography and Tomosynthesis: A Retrospective Evaluation.
| العنوان: | AI-based Strategies to Reduce Workload in Breast Cancer Screening with Mammography and Tomosynthesis: A Retrospective Evaluation. |
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| المؤلفون: | Raya-Povedano JL; From the Breast Cancer Unit, Department of Radiology, Hospital Universitario Reina Sofía, Av Menéndez Pidal s/n, Córdoba 14004, Spain (J.L.R.P., S.R.M., E.E.C., M.Á.B.); Maimonides Institute for Biomedical Research of Córdoba, Córdoba, Spain (J.L.R.P., S.R.M., E.E.C., M.Á.B.); and Department of Clinical Science, ScreenPoint Medical, Nijmegen, the Netherlands (A.G.M., A.R.R.)., Romero-Martín S; From the Breast Cancer Unit, Department of Radiology, Hospital Universitario Reina Sofía, Av Menéndez Pidal s/n, Córdoba 14004, Spain (J.L.R.P., S.R.M., E.E.C., M.Á.B.); Maimonides Institute for Biomedical Research of Córdoba, Córdoba, Spain (J.L.R.P., S.R.M., E.E.C., M.Á.B.); and Department of Clinical Science, ScreenPoint Medical, Nijmegen, the Netherlands (A.G.M., A.R.R.)., Elías-Cabot E; From the Breast Cancer Unit, Department of Radiology, Hospital Universitario Reina Sofía, Av Menéndez Pidal s/n, Córdoba 14004, Spain (J.L.R.P., S.R.M., E.E.C., M.Á.B.); Maimonides Institute for Biomedical Research of Córdoba, Córdoba, Spain (J.L.R.P., S.R.M., E.E.C., M.Á.B.); and Department of Clinical Science, ScreenPoint Medical, Nijmegen, the Netherlands (A.G.M., A.R.R.)., Gubern-Mérida A; From the Breast Cancer Unit, Department of Radiology, Hospital Universitario Reina Sofía, Av Menéndez Pidal s/n, Córdoba 14004, Spain (J.L.R.P., S.R.M., E.E.C., M.Á.B.); Maimonides Institute for Biomedical Research of Córdoba, Córdoba, Spain (J.L.R.P., S.R.M., E.E.C., M.Á.B.); and Department of Clinical Science, ScreenPoint Medical, Nijmegen, the Netherlands (A.G.M., A.R.R.)., Rodríguez-Ruiz A; From the Breast Cancer Unit, Department of Radiology, Hospital Universitario Reina Sofía, Av Menéndez Pidal s/n, Córdoba 14004, Spain (J.L.R.P., S.R.M., E.E.C., M.Á.B.); Maimonides Institute for Biomedical Research of Córdoba, Córdoba, Spain (J.L.R.P., S.R.M., E.E.C., M.Á.B.); and Department of Clinical Science, ScreenPoint Medical, Nijmegen, the Netherlands (A.G.M., A.R.R.)., Álvarez-Benito M; From the Breast Cancer Unit, Department of Radiology, Hospital Universitario Reina Sofía, Av Menéndez Pidal s/n, Córdoba 14004, Spain (J.L.R.P., S.R.M., E.E.C., M.Á.B.); Maimonides Institute for Biomedical Research of Córdoba, Córdoba, Spain (J.L.R.P., S.R.M., E.E.C., M.Á.B.); and Department of Clinical Science, ScreenPoint Medical, Nijmegen, the Netherlands (A.G.M., A.R.R.). |
| المصدر: | Radiology [Radiology] 2021 Jul; Vol. 300 (1), pp. 57-65. Date of Electronic Publication: 2021 May 04. |
| نوع المنشور: | Journal Article; Research Support, Non-U.S. Gov't |
| اللغة: | English |
| بيانات الدورية: | Publisher: Radiological Society of North America Country of Publication: United States NLM ID: 0401260 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1527-1315 (Electronic) Linking ISSN: 00338419 NLM ISO Abbreviation: Radiology Subsets: MEDLINE |
| أسماء مطبوعة: | Publication: Easton, PA : Radiological Society of North America Original Publication: [Illinois?] : Radiological Society of North America, [1923]- |
| مواضيع طبية MeSH: | Artificial Intelligence*, Breast Neoplasms/*diagnostic imaging , Mammography/*methods , Radiographic Image Interpretation, Computer-Assisted/*methods , Workload/*statistics & numerical data, Aged ; Breast/diagnostic imaging ; Female ; Humans ; Middle Aged ; Retrospective Studies ; Workflow |
| مستخلص: | Background The workflow of breast cancer screening programs could be improved given the high workload and the high number of false-positive and false-negative assessments. Purpose To evaluate if using an artificial intelligence (AI) system could reduce workload without reducing cancer detection in breast cancer screening with digital mammography (DM) or digital breast tomosynthesis (DBT). Materials and Methods Consecutive screening-paired and independently read DM and DBT images acquired from January 2015 to December 2016 were retrospectively collected from the Córdoba Tomosynthesis Screening Trial. The original reading settings were single or double reading of DM or DBT images. An AI system computed a cancer risk score for DM and DBT examinations independently. Each original setting was compared with a simulated autonomous AI triaging strategy (the least suspicious examinations for AI are not human-read; the rest are read in the same setting as the original, and examinations not recalled by radiologists but graded as very suspicious by AI are recalled) in terms of workload, sensitivity, and recall rate. The McNemar test with Bonferroni correction was used for statistical analysis. Results A total of 15 987 DM and DBT examinations (which included 98 screening-detected and 15 interval cancers) from 15 986 women (mean age ± standard deviation, 58 years ± 6) were evaluated. In comparison with double reading of DBT images (568 hours needed, 92 of 113 cancers detected, 706 recalls in 15 987 examinations), AI with DBT would result in 72.5% less workload ( P < .001, 156 hours needed), noninferior sensitivity (95 of 113 cancers detected, P = .38), and 16.7% lower recall rate ( P < .001, 588 recalls in 15 987 examinations). Similar results were obtained for AI with DM. In comparison with the original double reading of DM images (222 hours needed, 76 of 113 cancers detected, 807 recalls in 15 987 examinations), AI with DBT would result in 29.7% less workload ( P < .001), 25.0% higher sensitivity ( P < .001), and 27.1% lower recall rate ( P < .001). Conclusion Digital mammography and digital breast tomosynthesis screening strategies based on artificial intelligence systems could reduce workload up to 70%. Published under a CC BY 4.0 license. |
| تواريخ الأحداث: | Date Created: 20210504 Date Completed: 20210910 Latest Revision: 20210910 |
| رمز التحديث: | 20221213 |
| DOI: | 10.1148/radiol.2021203555 |
| PMID: | 33944627 |
| قاعدة البيانات: | MEDLINE |
| تدمد: | 1527-1315 |
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| DOI: | 10.1148/radiol.2021203555 |