Contrast-enhanced Mammography: A Systematic Review and Meta-Analysis of Diagnostic Performance.


Journal

Radiology
ISSN: 1527-1315
Titre abrégé: Radiology
Pays: United States
ID NLM: 0401260

Informations de publication

Date de publication:
03 2022
Historique:
pubmed: 15 12 2021
medline: 5 3 2022
entrez: 14 12 2021
Statut: ppublish

Résumé

Background Contrast-enhanced mammography (CEM) is a promising technique for breast cancer detection, but conflicting results have been reported in previous meta-analyses. Purpose To perform a systematic review and meta-analysis of CEM diagnostic performance considering different interpretation methods and clinical settings. Materials and Methods The MEDLINE, EMBASE, Web of Science, and Cochrane Library databases were systematically searched up to July 15, 2021. Prospective and retrospective studies evaluating CEM diagnostic performance with histopathology and/or follow-up as the reference standard were included. Study quality was assessed with the Quality Assessment of Diagnostic Accuracy Studies 2 tool. Summary diagnostic odds ratio and area under the receiver operating characteristic curve were estimated with the hierarchical summary receiver operating characteristic (HSROC) model. Summary estimates of sensitivity and specificity were obtained with the hierarchical bivariate model, pooling studies with the same image interpretation approach or focused on the same findings. Heterogeneity was investigated through meta-regression and subgroup analysis. Results Sixty studies (67 study parts, 11 049 CEM examinations in 10 605 patients) were included. The overall area under the HSROC curve was 0.94 (95% CI: 0.91, 0.96). Pooled diagnostic odds ratio was 55.7 (95% CI: 42.7, 72.7) with high heterogeneity (τ

Identifiants

pubmed: 34904875
doi: 10.1148/radiol.211412
doi:

Substances chimiques

Contrast Media 0

Types de publication

Journal Article Meta-Analysis Systematic Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

568-581

Commentaires et corrections

Type : CommentIn

Auteurs

Andrea Cozzi (A)

From the Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Luigi Mangiagalli 31, 20133 Milan, Italy (A.C., V.M., M.Z., F.S.); and Unit of Radiology, IRCCS Policlinico San Donato, San Donato Milanese, Italy (S.S., F.S.).

Veronica Magni (V)

From the Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Luigi Mangiagalli 31, 20133 Milan, Italy (A.C., V.M., M.Z., F.S.); and Unit of Radiology, IRCCS Policlinico San Donato, San Donato Milanese, Italy (S.S., F.S.).

Moreno Zanardo (M)

From the Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Luigi Mangiagalli 31, 20133 Milan, Italy (A.C., V.M., M.Z., F.S.); and Unit of Radiology, IRCCS Policlinico San Donato, San Donato Milanese, Italy (S.S., F.S.).

Simone Schiaffino (S)

From the Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Luigi Mangiagalli 31, 20133 Milan, Italy (A.C., V.M., M.Z., F.S.); and Unit of Radiology, IRCCS Policlinico San Donato, San Donato Milanese, Italy (S.S., F.S.).

Francesco Sardanelli (F)

From the Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Luigi Mangiagalli 31, 20133 Milan, Italy (A.C., V.M., M.Z., F.S.); and Unit of Radiology, IRCCS Policlinico San Donato, San Donato Milanese, Italy (S.S., F.S.).

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Classifications MeSH