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Multiparametric breast MRI to problem-solve mammographically detected suspicious calcifications

Authors
 Park, Vivian Y.  ;  Hippe, Daniel S.  ;  Kazerouni, Anum S.  ;  Biswas, Debosmita  ;  Bryant, Mary Lynn  ;  Li, Isabella  ;  Javid, Sara H.  ;  Kilgore, Mark  ;  Kim, Janice  ;  Kim, Andrew G.  ;  Scheel, John R.  ;  Lowry, Kathryn P.  ;  Lam, Diana L.  ;  Partridge, Savannah  ;  Rahbar, Habib 
Citation
 EUROPEAN JOURNAL OF RADIOLOGY, Vol.194, 2026-01 
Article Number
 112467 
Journal Title
EUROPEAN JOURNAL OF RADIOLOGY
ISSN
 0720-048X 
Issue Date
2026-01
MeSH
Adult ; Aged ; Breast / diagnostic imaging ; Breast Neoplasms* / diagnostic imaging ; Breast Neoplasms* / pathology ; Calcinosis* / diagnostic imaging ; Carcinoma, Intraductal, Noninfiltrating / diagnostic imaging ; Contrast Media ; Female ; Humans ; Mammography* / methods ; Middle Aged ; Multiparametric Magnetic Resonance Imaging* / methods ; Prospective Studies ; Sensitivity and Specificity
Keywords
Breast MRI ; Mammography ; Calcifications ; Diagnostic imaging ; Ductal carcinoma in situ
Abstract
Objective: To evaluate the performance of multiparametric breast MRI to problem-solve mammographicallydetected suspicious calcifications. Materials and methods: Participants with mammographically-detected suspicious calcifications were prospectively enrolled between August 2017 to May 2023. Pre-biopsy multiparametric MRI (standard and high-temporal resolution dynamic contrast enhanced [DCE]-MRI acquisitions and diffusion-weighted imaging [DWI]) was performed. The associations of MRI features with outcomes - (1) any malignancy and (2) invasive or high-grade ductal carcinoma in situ [DCIS] only - were analyzed using univariable logistic regression. Multivariable models, sequentially incorporating clinical/mammographic, qualitative, and quantitative features, were developed using penalized logistic regression with the least absolute shrinkage and selection operator. Area under the receiver operating characteristic curves (AUC) were estimated via cross-validation and compared between models using bootstrap methods. Results: 81 women (mean age, 55 years +/- 10 [standard deviation]) with 86 calcifications were included; 29 % (25/86) were malignant. Malignancy rates for non-enhancing mammographic Breast Imaging Reporting and Data System (BI-RADS) category 4a and 4b calcifications were 3.8 % (1/26) and 8.7 % (2/23), respectively, with no invasive cancer or high-grade DCIS. Mammographic BI-RADS category, MRI BI-RADS category, visibility on DWI, peak percent enhancement, functional tumor volume, and Ktrans values were associated with both outcomes (all p < 0.05). Multivariable models, including qualitative DCE-MRI assessments, showed higher AUCs (malignancy: 0.71-0.76; invasive cancer or high-grade DCIS: 0.78-0.91) than when including only clinical and mammographic features (malignancy: 0.57; invasive cancer or high-grade DCIS: 0.61, all p < 0.05). Further incorporation of DWI or quantitative MRI features did not improve AUCs (all Delta AUC <= 0). Conclusion: Breast DCE-MRI aids in evaluating mammographic BI-RADS category 4a/4b calcifications without biopsy. DWI or quantitative MRI features may not further improve diagnostic performance.
Full Text
https://www.sciencedirect.com/science/article/pii/S0720048X25005534
DOI
10.1016/j.ejrad.2025.112467
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers
Yonsei Authors
Park, Vivian Youngjean(박영진) ORCID logo https://orcid.org/0000-0002-5135-4058
URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/209653
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