Comparison of contrast-enhanced mammography and breast MRI in tumour extent assessment: A systematic review and meta-analysis

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Authors: Sven J.E. Ermans, Romy Maas, T. Martyn Hill, SASHA I. USISKIN, Lejla Alić, M. Douek
Cited by: 2
References: 53

Abstract

Introduction Accurate estimation of tumour extent is crucial for breast cancer treatment and achieving tumour-free surgical margins. Breast MRI is a widely used imaging modality; however, the high cost and limited availability of MRI have increased interest in contrast-enhanced mammography (CEM) as a potential alternative. This meta-analysis compares the accuracy of tumour extent estimation between MRI and CEM, using histopathological size as the reference standard. Method Literature up to October 2024 was reviewed. Two independent reviewers extracted relevant data. For both modalities in comparison with pathology, mean differences in tumour size and pooled correlation coefficients were calculated. A direct comparison of tumour size estimates between both modalities was conducted using R 2 and a two-sample t-test. The I 2 -statistic was used to assess between-study heterogeneity. Results Twenty-one studies involving 1,060 patients were included. Both modalities showed a mean overestimation of tumour size by ∼3 mm, with no statistical significance (P=0.345 and P=0.308). Correlation coefficients with pathology were 0.78 for MRI and 0.79 for CEM. Direct comparison demonstrated strong agreement (R 2 =0.81) between the two modalities, and no significant difference (P=0.65). Limited data suggested higher sensitivity but reduced specificity for MRI in the detection of multifocal/multicentric disease. Conclusion MRI and CEM showed comparable performance in tumour size estimation, with no significant differences compared to pathology or each other. These findings suggest CEM could potentially be an alternative for MRI, especially in resource-limited settings or for patients contraindicated for MRI. However, small study sizes and limited subgroup data highlight the need for large-scale prospective research.

Fields of Study & Subjects

MRI in cancer diagnosis Breast Cancer Treatment Studies Radiomics and Machine Learning in Medical Imaging

Publication details

Journal / source
European Journal of Surgical Oncology
Publisher
Elsevier BV
Volume
52
Issue
3
Pages
111410–111410
Publication date
16 January 2026
Language
EN