Reducing Unnecessary Biopsies Using Digital Breast Tomosynthesis and Ultrasound in Dense and Nondense Breasts.


Journal

Current oncology (Toronto, Ont.)
ISSN: 1718-7729
Titre abrégé: Curr Oncol
Pays: Switzerland
ID NLM: 9502503

Informations de publication

Date de publication:
04 08 2022
Historique:
received: 21 06 2022
revised: 29 07 2022
accepted: 02 08 2022
entrez: 25 8 2022
pubmed: 26 8 2022
medline: 27 8 2022
Statut: epublish

Résumé

Aim: To compare digital breast tomosynthesis (DBT) and ultrasound in women recalled for assessment after a positive screening mammogram and assess the potential for each of these tools to reduce unnecessary biopsies. Methods: This data linkage study included 538 women recalled for assessment from January 2017 to December 2019. The association between the recalled mammographic abnormalities and breast density was analysed using the chi-square independence test. Relative risks and the number of recalled cases requiring DBT and ultrasound assessment to prevent one unnecessary biopsy were compared using the McNemar test. Results: Breast density significantly influenced recall decisions (p < 0.001). Ultrasound showed greater potential to decrease unnecessary biopsies than DBT: in entirely fatty (21% vs. 5%; p = 0.04); scattered fibroglandular (23% vs. 10%; p = 0.003); heterogeneously dense (34% vs. 7%; p < 0.001) and extremely dense (39% vs. 9%; p < 0.001) breasts. The number of benign cases needing assessment to prevent one unnecessary biopsy was significantly lower with ultrasound than DBT in heterogeneously dense (1.8 vs. 7; p < 0.001) and extremely dense (1.9 vs. 5.1; p = 0.03) breasts. Conclusion: Women with dense breasts are more likely to be recalled for assessment and have a false-positive biopsy. Women with dense breasts benefit more from ultrasound assessment than from DBT.

Identifiants

pubmed: 36005173
pii: curroncol29080435
doi: 10.3390/curroncol29080435
pmc: PMC9406307
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

5508-5516

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Auteurs

Ibrahim Hadadi (I)

Medical Image Optimisation and Perception Group, Discipline of Medical Imaging Science, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW 2006, Australia.
Department of Radiological Sciences, Faculty of Applied Medical Sciences, King Khalid University, Abha 62529, Saudi Arabia.

Jillian Clarke (J)

Medical Image Optimisation and Perception Group, Discipline of Medical Imaging Science, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW 2006, Australia.

William Rae (W)

Medical Image Optimisation and Perception Group, Discipline of Medical Imaging Science, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW 2006, Australia.
Medical Imaging Department, Prince of Wales Hospital, Sydney, NSW 2031, Australia.

Mark McEntee (M)

Medical Image Optimisation and Perception Group, Discipline of Medical Imaging Science, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW 2006, Australia.
Discipline of Diagnostic Radiography, UGF 12 ASSERT, Brookfield Health Sciences, University College Cork, College Road, T12 AK54 Cork, Ireland.

Wendy Vincent (W)

Royal Prince Alfred Hospital, Sydney Local Health District, Camperdown, NSW 2050, Australia.

Ernest Ekpo (E)

Medical Image Optimisation and Perception Group, Discipline of Medical Imaging Science, Faculty of Medicine and Health, The University of Sydney, Camperdown, NSW 2006, Australia.
Orange Radiology, Laboratories and Research Centre, Calabar 540281, Nigeria.

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