Diagnostic performance of 3D automated breast ultrasound (3D-ABUS) in a clinical screening setting—a retrospective study

Objectives: To assess the diagnostic performance of 3D automated breast ultrasound (3D-ABUS) in breast cancer screening in a clinical setting. Materials and methods: All patients who had 3D-ABUS between January 2014 and January 2022 for screening were included in this retrospective study. The images...

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Published in:European Radiology
Main Author: Klein Wolterink F.; Ab Mumin N.; Appelman L.; Derks-Rekers M.; Imhof-Tas M.; Lardenoije S.; van der Leest M.; Mann R.M.
Format: Article
Language:English
Published: Springer Science and Business Media Deutschland GmbH 2024
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182645730&doi=10.1007%2fs00330-023-10568-5&partnerID=40&md5=dbeaed018aa741b60725fb9bb4960aa2
id 2-s2.0-85182645730
spelling 2-s2.0-85182645730
Klein Wolterink F.; Ab Mumin N.; Appelman L.; Derks-Rekers M.; Imhof-Tas M.; Lardenoije S.; van der Leest M.; Mann R.M.
Diagnostic performance of 3D automated breast ultrasound (3D-ABUS) in a clinical screening setting—a retrospective study
2024
European Radiology
34
8
10.1007/s00330-023-10568-5
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182645730&doi=10.1007%2fs00330-023-10568-5&partnerID=40&md5=dbeaed018aa741b60725fb9bb4960aa2
Objectives: To assess the diagnostic performance of 3D automated breast ultrasound (3D-ABUS) in breast cancer screening in a clinical setting. Materials and methods: All patients who had 3D-ABUS between January 2014 and January 2022 for screening were included in this retrospective study. The images were reported by 1 of 6 breast radiologists based on the Breast Imaging Reporting and Data Systems (BI-RADS). The 3D-ABUS was reviewed together with the digital breast tomosynthesis (DBT). Recall rate, biopsy rate, positive predictive value (PPV) and cancer detection yield were calculated. Results: In total, 3616 studies were performed in 1555 women (breast density C/D 95.5% (n = 3455/3616), breast density A/B 4.0% (n = 144/3616), density unknown (0.5% (n = 17/3616)). A total of 259 lesions were detected on 3D-ABUS (87.6% (n = 227/259) masses and 12.4% (n = 32/259) architectural distortions). The recall rate was 5.2% (n = 188/3616) (CI 4.5–6.0%) with only 36.7% (n = 69/188) cases recalled to another date. Moreover, recall declined over time. There were 3.4% (n = 123/3616) biopsies performed, with 52.8% (n = 65/123) biopsies due to an abnormality detected in 3D-ABUS alone. Ten of 65 lesions were malignant, resulting in a positive predictive value (PPV) of 15.4% (n = 10/65) (CI 7.6–26.5%)). The cancer detection yield of 3D-ABUS is 2.77 per 1000 screening tests (CI 1.30–5.1). Conclusion: The cancer detection yield of 3D-ABUS in a real clinical screening setting is comparable to the results reported in previous prospective studies, with lower recall and biopsy rates. 3D-ABUS also may be an alternative for screening when mammography is not possible or declined. Clinical relevance statement: 3D automated breast ultrasound screening performance in a clinical setting is comparable to previous prospective studies, with better recall and biopsy rates. Key Points: • 3D automated breast ultrasound is a reliable and reproducible tool that provides a three-dimensional representation of the breast and allows image visualisation in axial, coronal and sagittal. • The diagnostic performance of 3D automated breast ultrasound in a real clinical setting is comparable to its performance in previously published prospective studies, with improved recall and biopsy rates. • 3D automated breast ultrasound is a useful adjunct to mammography in dense breasts and may be an alternative for screening when mammography is not possible or declined. © The Author(s) 2024.
Springer Science and Business Media Deutschland GmbH
09387994
English
Article
All Open Access; Hybrid Gold Open Access
author Klein Wolterink F.; Ab Mumin N.; Appelman L.; Derks-Rekers M.; Imhof-Tas M.; Lardenoije S.; van der Leest M.; Mann R.M.
spellingShingle Klein Wolterink F.; Ab Mumin N.; Appelman L.; Derks-Rekers M.; Imhof-Tas M.; Lardenoije S.; van der Leest M.; Mann R.M.
Diagnostic performance of 3D automated breast ultrasound (3D-ABUS) in a clinical screening setting—a retrospective study
author_facet Klein Wolterink F.; Ab Mumin N.; Appelman L.; Derks-Rekers M.; Imhof-Tas M.; Lardenoije S.; van der Leest M.; Mann R.M.
author_sort Klein Wolterink F.; Ab Mumin N.; Appelman L.; Derks-Rekers M.; Imhof-Tas M.; Lardenoije S.; van der Leest M.; Mann R.M.
title Diagnostic performance of 3D automated breast ultrasound (3D-ABUS) in a clinical screening setting—a retrospective study
title_short Diagnostic performance of 3D automated breast ultrasound (3D-ABUS) in a clinical screening setting—a retrospective study
title_full Diagnostic performance of 3D automated breast ultrasound (3D-ABUS) in a clinical screening setting—a retrospective study
title_fullStr Diagnostic performance of 3D automated breast ultrasound (3D-ABUS) in a clinical screening setting—a retrospective study
title_full_unstemmed Diagnostic performance of 3D automated breast ultrasound (3D-ABUS) in a clinical screening setting—a retrospective study
title_sort Diagnostic performance of 3D automated breast ultrasound (3D-ABUS) in a clinical screening setting—a retrospective study
publishDate 2024
container_title European Radiology
container_volume 34
container_issue 8
doi_str_mv 10.1007/s00330-023-10568-5
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85182645730&doi=10.1007%2fs00330-023-10568-5&partnerID=40&md5=dbeaed018aa741b60725fb9bb4960aa2
description Objectives: To assess the diagnostic performance of 3D automated breast ultrasound (3D-ABUS) in breast cancer screening in a clinical setting. Materials and methods: All patients who had 3D-ABUS between January 2014 and January 2022 for screening were included in this retrospective study. The images were reported by 1 of 6 breast radiologists based on the Breast Imaging Reporting and Data Systems (BI-RADS). The 3D-ABUS was reviewed together with the digital breast tomosynthesis (DBT). Recall rate, biopsy rate, positive predictive value (PPV) and cancer detection yield were calculated. Results: In total, 3616 studies were performed in 1555 women (breast density C/D 95.5% (n = 3455/3616), breast density A/B 4.0% (n = 144/3616), density unknown (0.5% (n = 17/3616)). A total of 259 lesions were detected on 3D-ABUS (87.6% (n = 227/259) masses and 12.4% (n = 32/259) architectural distortions). The recall rate was 5.2% (n = 188/3616) (CI 4.5–6.0%) with only 36.7% (n = 69/188) cases recalled to another date. Moreover, recall declined over time. There were 3.4% (n = 123/3616) biopsies performed, with 52.8% (n = 65/123) biopsies due to an abnormality detected in 3D-ABUS alone. Ten of 65 lesions were malignant, resulting in a positive predictive value (PPV) of 15.4% (n = 10/65) (CI 7.6–26.5%)). The cancer detection yield of 3D-ABUS is 2.77 per 1000 screening tests (CI 1.30–5.1). Conclusion: The cancer detection yield of 3D-ABUS in a real clinical screening setting is comparable to the results reported in previous prospective studies, with lower recall and biopsy rates. 3D-ABUS also may be an alternative for screening when mammography is not possible or declined. Clinical relevance statement: 3D automated breast ultrasound screening performance in a clinical setting is comparable to previous prospective studies, with better recall and biopsy rates. Key Points: • 3D automated breast ultrasound is a reliable and reproducible tool that provides a three-dimensional representation of the breast and allows image visualisation in axial, coronal and sagittal. • The diagnostic performance of 3D automated breast ultrasound in a real clinical setting is comparable to its performance in previously published prospective studies, with improved recall and biopsy rates. • 3D automated breast ultrasound is a useful adjunct to mammography in dense breasts and may be an alternative for screening when mammography is not possible or declined. © The Author(s) 2024.
publisher Springer Science and Business Media Deutschland GmbH
issn 09387994
language English
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accesstype All Open Access; Hybrid Gold Open Access
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