ReviewCureus2026
Accuracy of Contrast-Enhanced Mammography (CEM) Compared With Breast MRI in Detecting Residual Disease After Neoadjuvant Therapy: A Systematic Review.
Review in Cureus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accurate assessment of residual tumor burden following neoadjuvant therapy (NAT) is critical for predicting patient outcomes and guiding surgical decision-making in breast cancer management. While breast MRI remains the reference standard for posttreatment evaluation, contrast-enhanced mammography (CEM) has emerged as a promising alternative because MRI is often limited by its high cost, limited accessibility, prolonged examination time, and contraindications in certain patient populations. This study aims to evaluate the diagnostic precision of breast MRI and CEM in identifying residual disease in patients with breast cancer following neoadjuvant treatment. Using PubMed/MEDLINE, Embase, Cochrane CENTRAL, and Web of Science, a systematic review was carried out between January 2021 and January 2026 in accordance with the PRISMA standards. Included studies were prospective or retrospective head-to-head comparative studies reporting sufficient information to create 2 × 2 contingency tables for precise diagnosis, with histopathology as the reference standard. Six studies met the eligibility criteria, comprising 349 participants. The Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool was used to assess quality. MRI sensitivity varied from 44.4% to 100%, whereas CEM sensitivity ranged from 77.8% to 100%. MRI specificity varied from 47% to 94.4%, whereas CEM specificity ranged from 50% to 83.3%. CEM demonstrated a tendency toward higher sensitivity but lower specificity compared with MRI. The remaining tumor size was consistently overestimated by both modalities by approximately 1-3 mm. False-negative rates were notably low for CEM (0-22.2%) but reached 55.6% for MRI in one small study. Identification of residual ductal carcinoma in situ remained challenging for both techniques, with improved detection when incorporating mammographic calcification assessment. The QUADAS-2 assessment indicated a low risk of bias for most studies. When identifying residual disease following neoadjuvant treatment, CEM and MRI exhibit similar diagnostic accuracy, with MRI having better specificity and CEM having higher sensitivity. When MRI is unavailable or contraindicated, CEM is a dependable substitute because of its practical benefits, which include reduced cost, shorter examination times, greater availability, and the lack of gadolinium-related contraindications. Tumor subtype, patient features, and institutional resources should all be taken into consideration when selecting a modality.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.