ArticleBMC medical imaging2025
Diagnostic performance of ultrasound elastography in differentiating malignant from benign breast microcalcifications: a case-control study.
Article in BMC medical imaging, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- Predictive value of elastography (Shear-Wave and Elasticity Index) in differentiating benign from malignant breast lesions: a retrospective study in Peru.Radiology and oncology · 2026Observational
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo evaluate the sensitivity and specificity of ultrasound elastography in differentiating between malignant and benign breast microcalcifications through a case-control study.
methodsA total of 300 female patients were enrolled in this study, equally divided between malignant (n = 150) and benign (n = 150) microcalcification groups. The malignant cases were histologically confirmed as ductal carcinoma in situ or invasive breast cancer, while benign cases were confirmed through histology or follow-up as fibroadenoma, fibrocystic changes, or benign calcifications. Ultrasound elastography parameters, including elastic modulus (kPa), strain ratio, and elasticity scores, were measured and compared between groups. Multiple logistic regression analysis was performed to identify independent predictors, and diagnostic performance was evaluated using ROC curve analysis.
resultsMalignant lesions demonstrated significantly higher mean elasticity values compared to benign lesions (88.3 ± 16.2 kPa vs. 45.7 ± 9.8 kPa, P < 0.001). The strain ratio and elasticity scores were also significantly elevated in the malignant group (both P < 0.001). Multivariate analysis identified elastic modulus (OR = 1.09, 95%CI: 1.06-1.12, P < 0.001) and strain ratio (OR = 2.50, 95%CI: 1.70-3.80, P < 0.001) as independent predictors of malignancy. Using an optimal cutoff value of 62 kPa for elasticity, the diagnostic sensitivity was 88.0% (95%CI: 81.5-92.8%) and specificity was 86.7% (95%CI: 79.5-91.9%), with an accuracy of 89.0%. The area under the ROC curve (AUC) for elasticity alone was 0.95 (95%CI: 0.92-0.98), which improved to 0.97 (95%CI: 0.94-0.99) when combined with strain ratio (P = 0.018). High interobserver agreement was demonstrated (Kappa = 0.84, 95%CI: 0.79-0.88), and Bland-Altman analysis confirmed excellent measurement reliability.
conclusionUltrasound elastography demonstrates high diagnostic accuracy in differentiating between malignant and benign breast microcalcifications, with excellent reproducibility and reliability. The combination of elasticity values and strain ratio provides superior diagnostic performance compared to single parameters alone, suggesting its potential as a valuable tool in clinical practice for the evaluation of breast microcalcifications.
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.