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CE-MRI rules out malignancy in 13.1% pretest probability for high-risk breast lesions with 91.3% sensitivity

CE-MRI rules out malignancy in 13.1% pretest probability for high-risk breast lesions with 91.3%…
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Key Takeaway
Consider CE-MRI for high-risk lesions if pretest probability is below 13.1% to rule out malignancy.

This systematic review and meta-analysis examines the utility of contrast-enhanced breast MRI (CE-MRI) in assessing high-risk lesions diagnosed at image-guided biopsy. The analysis included 479 patients with 493 high-risk lesions. The primary outcome focused on the ability to rule out malignancy in this specific population.

The pooled sensitivity for CE-MRI was 91.3% with a 95% confidence interval of 82.8% to 95.8%. The pooled specificity was 68.8% with a 95% confidence interval of 50.3% to 82.8%. The breast cancer prevalence among the lesions was 17% (88 of 493 cases).

Six missed malignancies were identified, all classified as small low-grade ductal carcinoma in situ. The maximum pretest probability at which a negative MRI matched the 2% malignancy threshold was 13.1%. Safety data, including adverse events and tolerability, were not reported. The authors note that prospective studies are suggested for confirmation.

The practice relevance indicates that CE-MRI may help identify patients who can safely avoid surgery. This approach could potentially reduce morbidity, anxiety, and healthcare resource use. However, the certainty is limited by the need for further prospective validation.

Study Details

Study typeMeta analysis
Sample sizen = 479
EvidenceLevel 1
PublishedJun 2026
View Original Abstract ↓
OBJECTIVE: This systematic review and meta-analysis investigate the added value of contrast-enhanced breast MRI (CE-MRI) to rule out malignancy in patients with high-risk (B3) lesions diagnosed at image-guided biopsy. MATERIALS AND METHODS: A systematic review and meta-analysis were performed using predefined criteria. Eligible English-language articles published until August 2024 focused on CE-MRI in high-risk lesions. Two reviewers extracted data on true positives (TP), false positives (FP), true negatives (TN), and false negatives (FN). Sensitivity, specificity, negative and positive likelihood ratios were calculated using a bivariate random-effects model. Fagan nomograms identified the maximum pretest probability at which post-test probabilities of a negative MRI matched the 2% malignancy threshold used for downgrading BI-RADS 4 to 3. I² statistics and meta-regression explored heterogeneity. p-values < 0.05 were considered significant. RESULTS: Seven studies comprising 479 patients with 493 high-risk lesions undergoing CE-MRI were included. The average breast cancer prevalence was 17% (88/493). Pooled sensitivity was 91.3% (95% CI: 82.8-95.8%) and pooled specificity was 68.8% (95% CI: 50.3-82.8%). Only 6/493 malignancies were missed by CE-MRI; all were small low-grade ductal carcinoma in situ (DCIS). Fagan nomograms indicated that CE-MRI could rule out malignancy in lesions with pretest probabilities up to 13.1%. CONCLUSIONS: CE-MRI in assessing high-risk lesions may help identify patients who can safely avoid surgery, potentially reducing morbidity, anxiety, and healthcare resource use. Malignancy can be reliably ruled out in lesions with pretest probabilities ≤ 13.1%, although prospective studies are suggested for confirmation. KEY POINTS: Question Can contrast-enhanced breast MRI help to rule out malignancy in patients with high-risk lesions at imaging-guided biopsy, thereby supporting more tailored decisions and potentially reducing unnecessary surgical excisions? Findings Contrast-enhanced breast MRI may reduce unnecessary surgical or vacuum excisions in high-risk (B3) lesions. Missed cancers were limited to small low-grade DCIS. Clinical relevance Contrast-enhanced breast MRI may support the identification of patients with high-risk lesions who could potentially avoid surgery. This non-invasive approach has the potential to reduce overtreatment, healthcare costs, and patient anxiety, while maintaining a high negative predictive value.
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