Diagnostic accuracy of contrast-enhanced mammography (CEM) for the evaluation of mammographic asymmetries: A systematic review and meta-analysis.
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TL;DR
CEM demonstrates high sensitivity and excellent overall accuracy in the evaluation of mammographic asymmetries, making it a valuable tool for ruling out malignancy.
OpenAlex 토픽 ·
Digital Radiography and Breast Imaging
Breast Lesions and Carcinomas
Global Cancer Incidence and Screening
CEM demonstrates high sensitivity and excellent overall accuracy in the evaluation of mammographic asymmetries, making it a valuable tool for ruling out malignancy.
- 95% CI 87-99
- Sensitivity 97%
- Specificity 80%
- 연구 설계 meta-analysis
APA
Filipe Ramos Barra, Victor Arthur Ohannesian, et al. (2026). Diagnostic accuracy of contrast-enhanced mammography (CEM) for the evaluation of mammographic asymmetries: A systematic review and meta-analysis.. European journal of radiology, 199, 112806. https://doi.org/10.1016/j.ejrad.2026.112806
MLA
Filipe Ramos Barra, et al.. "Diagnostic accuracy of contrast-enhanced mammography (CEM) for the evaluation of mammographic asymmetries: A systematic review and meta-analysis.." European journal of radiology, vol. 199, 2026, pp. 112806.
PMID
41861612 ↗
Abstract 한글 요약
[BACKGROUND] Mammographic asymmetries present a significant diagnostic challenge, often leading to unnecessary biopsies due to the limitations of conventional imaging. Contrast-enhanced mammography (CEM) has emerged as a promising modality that combines anatomical detail with functional information on tumor vascularity. However, its specific role and accuracy in evaluating asymmetries have not been systematically synthesized. This meta-analysis aims to determine the diagnostic accuracy of CEM for classifying mammographic asymmetries and its potential to reduce unnecessary interventions.
[METHOD] A systematic review and meta-analysis was conducted following PRISMA-DTA guidelines. The PubMed, Embase, and Web of Science databases were searched for studies published up to April 2025 that evaluated CEM for breast asymmetries using histopathology or long-term follow-up as the reference standard. A bivariate random-effects model was employed to calculate pooled estimates of sensitivity, specificity, likelihood ratios, and the area under the summary ROC curve (AUC).
[RESULTS] Seven studies involving 1,266 women with 1,328 asymmetries met the inclusion criteria. The pooled analysis showed that CEM has a high sensitivity of 97% (95% CI: 87-99) and a specificity of 80% (95% CI: 65-89) for detecting malignancy in asymmetries. The combined positive and negative likelihood ratios were 6.6 and 0.03, respectively. The overall diagnostic accuracy was excellent, with an AUC of 0.96 (95% CI: 0.94-0.97).
[CONCLUSION] CEM demonstrates high sensitivity and excellent overall accuracy in the evaluation of mammographic asymmetries, making it a valuable tool for ruling out malignancy. Its implementation in clinical practice has the potential to reduce unnecessary biopsies and optimize diagnostic pathways, offering an accessible and effective alternative, particularly in settings where MRI is unavailable.
[METHOD] A systematic review and meta-analysis was conducted following PRISMA-DTA guidelines. The PubMed, Embase, and Web of Science databases were searched for studies published up to April 2025 that evaluated CEM for breast asymmetries using histopathology or long-term follow-up as the reference standard. A bivariate random-effects model was employed to calculate pooled estimates of sensitivity, specificity, likelihood ratios, and the area under the summary ROC curve (AUC).
[RESULTS] Seven studies involving 1,266 women with 1,328 asymmetries met the inclusion criteria. The pooled analysis showed that CEM has a high sensitivity of 97% (95% CI: 87-99) and a specificity of 80% (95% CI: 65-89) for detecting malignancy in asymmetries. The combined positive and negative likelihood ratios were 6.6 and 0.03, respectively. The overall diagnostic accuracy was excellent, with an AUC of 0.96 (95% CI: 0.94-0.97).
[CONCLUSION] CEM demonstrates high sensitivity and excellent overall accuracy in the evaluation of mammographic asymmetries, making it a valuable tool for ruling out malignancy. Its implementation in clinical practice has the potential to reduce unnecessary biopsies and optimize diagnostic pathways, offering an accessible and effective alternative, particularly in settings where MRI is unavailable.
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