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Bergan MB, Larsen M, Moshina N, Bartsch H, Koch HW, Aase HS, Satybaldinov Z, Haldorsen IHS, Lee CI, Hofvind S. AI performance by mammographic density in a retrospective cohort study of 99,489 participants in BreastScreen Norway. Eur Radiol 2024:10.1007/s00330-024-10681-z. [PMID: 38528136 DOI: 10.1007/s00330-024-10681-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 01/19/2024] [Accepted: 02/10/2024] [Indexed: 03/27/2024]
Abstract
OBJECTIVE To explore the ability of artificial intelligence (AI) to classify breast cancer by mammographic density in an organized screening program. MATERIALS AND METHOD We included information about 99,489 examinations from 74,941 women who participated in BreastScreen Norway, 2013-2019. All examinations were analyzed with an AI system that assigned a malignancy risk score (AI score) from 1 (lowest) to 10 (highest) for each examination. Mammographic density was classified into Volpara density grade (VDG), VDG1-4; VDG1 indicated fatty and VDG4 extremely dense breasts. Screen-detected and interval cancers with an AI score of 1-10 were stratified by VDG. RESULTS We found 10,406 (10.5% of the total) examinations to have an AI risk score of 10, of which 6.7% (704/10,406) was breast cancer. The cancers represented 89.7% (617/688) of the screen-detected and 44.6% (87/195) of the interval cancers. 20.3% (20,178/99,489) of the examinations were classified as VDG1 and 6.1% (6047/99,489) as VDG4. For screen-detected cancers, 84.0% (68/81, 95% CI, 74.1-91.2) had an AI score of 10 for VDG1, 88.9% (328/369, 95% CI, 85.2-91.9) for VDG2, 92.5% (185/200, 95% CI, 87.9-95.7) for VDG3, and 94.7% (36/38, 95% CI, 82.3-99.4) for VDG4. For interval cancers, the percentages with an AI score of 10 were 33.3% (3/9, 95% CI, 7.5-70.1) for VDG1 and 48.0% (12/25, 95% CI, 27.8-68.7) for VDG4. CONCLUSION The tested AI system performed well according to cancer detection across all density categories, especially for extremely dense breasts. The highest proportion of screen-detected cancers with an AI score of 10 was observed for women classified as VDG4. CLINICAL RELEVANCE STATEMENT Our study demonstrates that AI can correctly classify the majority of screen-detected and about half of the interval breast cancers, regardless of breast density. KEY POINTS • Mammographic density is important to consider in the evaluation of artificial intelligence in mammographic screening. • Given a threshold representing about 10% of those with the highest malignancy risk score by an AI system, we found an increasing percentage of cancers with increasing mammographic density. • Artificial intelligence risk score and mammographic density combined may help triage examinations to reduce workload for radiologists.
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Affiliation(s)
- Marie Burns Bergan
- Section for Breast Cancer Screening, Cancer Registry of Norway, Norwegian Institute of Public Health, P.O. Box 5313, 0304, Oslo, Norway
| | - Marthe Larsen
- Section for Breast Cancer Screening, Cancer Registry of Norway, Norwegian Institute of Public Health, P.O. Box 5313, 0304, Oslo, Norway
| | - Nataliia Moshina
- Section for Breast Cancer Screening, Cancer Registry of Norway, Norwegian Institute of Public Health, P.O. Box 5313, 0304, Oslo, Norway
| | - Hauke Bartsch
- Department of Radiology, Mohn Medical Imaging and Visualization Centre (MMIV), Haukeland University Hospital, Bergen, Norway
| | - Henrik Wethe Koch
- Department of Radiology, Stavanger University Hospital, Stavanger, Norway
- Faculty of Health Sciences, University of Stavanger, Stavanger, Norway
| | | | - Zhanbolat Satybaldinov
- Department of Radiology, Mohn Medical Imaging and Visualization Centre (MMIV), Haukeland University Hospital, Bergen, Norway
| | - Ingfrid Helene Salvesen Haldorsen
- Department of Radiology, Mohn Medical Imaging and Visualization Centre (MMIV), Haukeland University Hospital, Bergen, Norway
- Section for Radiology, Department of Clinical Medicine, University of Bergen, Bergen, Norway
| | - Christoph I Lee
- Department of Radiology, University of Washington School of Medicine, Seattle, WA, USA
- Department of Health Systems and Population Health, University of Washington School of Public Health, Seattle, WA, USA
| | - Solveig Hofvind
- Section for Breast Cancer Screening, Cancer Registry of Norway, Norwegian Institute of Public Health, P.O. Box 5313, 0304, Oslo, Norway.
- Department of Health and Care Sciences, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway.
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Holen ÅS, Bergan MB, Lee CI, Zackrisson S, Moshina N, Aase HS, Haldorsen IS, Hofvind S. Early screening outcomes before, during, and after a randomized controlled trial with digital breast tomosynthesis. Eur J Radiol 2023; 167:111069. [PMID: 37708674 DOI: 10.1016/j.ejrad.2023.111069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 07/31/2023] [Accepted: 08/28/2023] [Indexed: 09/16/2023]
Abstract
PURPOSE To describe and compare early screening outcomes before, during and after a randomized controlled trial with digital breast tomosynthesis (DBT) including synthetic 2D mammography versus standard digital mammography (DM) (To-Be 1) and a follow-up cohort study using DBT (To-Be 2). METHODS Retrospective results of 125,020 screening examinations from four consecutive screening rounds performed in 2014-2021 were described and compared for pre-To-Be 1 (DM), To-Be 1 (DM or DBT), To-Be 2 (DBT), and post-To-Be 2 (DM) cohorts. Descriptive analyses of rates of recall, biopsy, screen-detected and interval cancer, distribution of histopathologic tumor characteristics and time spent on image interpretation and consensus were presented for the four rounds including five cohorts, one cohort in each screening round except for the To-Be 1 trail, which included a DBT and a DM cohort. Odds ratios (OR) with 95% CIs was calculated for recall and cancer detection rates. RESULTS Rate of screen-detected cancer was 0.90% for women screened with DBT in To-Be 2 and 0.64% for DM in pre-To-Be 1. The rates did not differ for the To-Be 1 DM (0.61%), To-Be 1 DBT (0.66%) and post-To-Be 2 DM (0.67%) cohorts. The interval cancer rates ranged between 0.13% and 0.20%. The distribution of histopathologic tumor characteristics did not differ between the cohorts. CONCLUSIONS Screening all women with DBT following a randomized controlled trial in an organized, population-based screening program showed a temporary increase in the rate of screen-detected cancer.
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Affiliation(s)
- Åsne Sørlien Holen
- Section for Breast Cancer Screening, Cancer Registry of Norway, Oslo, Norway.
| | - Marie Burns Bergan
- Section for Breast Cancer Screening, Cancer Registry of Norway, Oslo, Norway.
| | - Christoph I Lee
- Department of Radiology, University of Washington School of Medicine, Seattle, WA, USA; Department of Health Systems and Population Health, University of Washington School of Public Health, Seattle, WA, USA.
| | - Sophia Zackrisson
- Department of Translational Medicine, Diagnostic Radiology, Lund University, Malmö, Sweden; Department of Imaging and Functional Medicine, Skåne University Hospital, Malmö, Sweden.
| | - Nataliia Moshina
- Section for Breast Cancer Screening, Cancer Registry of Norway, Oslo, Norway.
| | | | - Ingfrid Salvesen Haldorsen
- Mohn Medical Imaging and Visualization Center, Department of Radiology, Haukeland University Hospital, Bergen, Norway; Department of Clinical Medicine, University of Bergen, Bergen, Norway.
| | - Solveig Hofvind
- Section for Breast Cancer Screening, Cancer Registry of Norway, Oslo, Norway; Department of Health and Care Sciences, Faculty of Health Sciences, UiT, The Arctic University of Norway, Tromsø, Norway.
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Aase HS, Danielsen AS, Hoff SR, Holen ÅS, Haldorsen IS, Hovda T, Hanestad B, Sandvik CK, Hofvind S. Mammographic features and screening outcome in a randomized controlled trial comparing digital breast tomosynthesis and digital mammography. Eur J Radiol 2021; 141:109753. [PMID: 34053786 DOI: 10.1016/j.ejrad.2021.109753] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Revised: 04/17/2021] [Accepted: 04/30/2021] [Indexed: 11/16/2022]
Abstract
PURPOSE To compare the distribution of mammographic features among women recalled for further assessment after screening with digital breast tomosynthesis (DBT) versus digital mammography (DM), and to assess associations between features and final outcome of the screening, including immunohistochemical subtypes of the tumour. METHODS This randomized controlled trial was performed in Bergen, Norway, and included 28,749 women, of which 1015 were recalled due to mammographic findings. Mammographic features were classified according to a modified BI-RADS-scale. The distribution were compared using 95 % confidence intervals (CI). RESULTS Asymmetry was the most common feature of all recalls, 24.3 % (108/444) for DBT and 38.9 % (222/571) for DM. Spiculated mass was most common for breast cancer after screening with DBT (36.8 %, 35/95, 95 %CI: 27.2-47.4) while calcifications (23.0 %, 20/87, 95 %CI: 14.6-33.2) was the most frequent after DM. Among women screened with DBT, 0.13 % (95 %CI: 0.08-0.21) had benign outcome after recall due to indistinct mass while the percentage was 0.28 % (95 %CI: 0.20-0.38) for DM. The distributions were 0.70 % (95 %CI: 0.57-0.85) versus 1.46 % (95 %CI: 1.27-1.67) for asymmetry and 0.24 % (95 %CI: 0.16-0.33) versus 0.54 % (95 %CI: 0.43-0.68) for obscured mass, among women screened with DBT versus DM, respectively. Spiculated mass was the most common feature among women diagnosed with non-luminal A-like cancer after DBT and after DM. CONCLUSIONS Spiculated mass was the dominant feature for breast cancer among women screened with DBT while calcifications was the most frequent feature for DM. Further studies exploring the clinical relevance of mammographic features visible particularly on DBT are warranted.
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Affiliation(s)
- H S Aase
- Department of Radiology, Haukeland University Hospital, Bergen, Norway; Department of Clinical Medicine, University of Bergen, 5020, Bergen, Norway.
| | - A S Danielsen
- Section for Breast Cancer Screening, Cancer Registry of Norway, Oslo, Norway; Norwegian Institute of Public Health, Oslo, Norway.
| | - S R Hoff
- Department of Radiology, Møre and Romsdal Hospital Trust, Ålesund, Norway.
| | - Å S Holen
- Section for Breast Cancer Screening, Cancer Registry of Norway, Oslo, Norway.
| | - I S Haldorsen
- Department of Radiology, Haukeland University Hospital, Bergen, Norway; Department of Clinical Medicine, University of Bergen, 5020, Bergen, Norway; Centre for Medical Imaging and Visualization, Haukeland University Hospital, Bergen, Norway.
| | - T Hovda
- Department of Radiology, Vestre Viken Hospital Trust, Drammen, Norway.
| | - B Hanestad
- Department of Radiology, Haukeland University Hospital, Bergen, Norway.
| | - C K Sandvik
- Department of Radiology, Haukeland University Hospital, Bergen, Norway.
| | - S Hofvind
- Section for Breast Cancer Screening, Cancer Registry of Norway, Oslo, Norway; Faculty of Health Sciences, Oslo Metropolitan University, Oslo, Norway.
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Hjerkind KV, Ellingjord-Dale M, Johansson AL, Aase HS, Hoff SR, Hofvind S, Fagerheim S, dos-Santos-Silva I, Ursin G. Volumetric Mammographic Density, Age-Related Decline, and Breast Cancer Risk Factors in a National Breast Cancer Screening Program. Cancer Epidemiol Biomarkers Prev 2018; 27:1065-1074. [DOI: 10.1158/1055-9965.epi-18-0151] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2018] [Revised: 04/25/2018] [Accepted: 06/15/2018] [Indexed: 11/16/2022] Open
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