ArticleQuantitative imaging in medicine and surgery2026
The value of multi-parametric ultrasonography nomogram in predicting nipple-areolar complex involvement in breast cancer.
Article in Quantitative imaging in medicine and surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Accurate assessment of nipple-areolar complex (NAC) involvement in breast cancer (BC) plays a key role in guiding preoperative surgical strategy. This study developed and evaluated a multi-parametric ultrasonography nomogram, incorporating conventional ultrasound (CUS), strain elastography (SE), and contrast-enhanced ultrasound (CEUS) to predict NAC involvement in BC. Methods: In this prospective study, consecutive patients were enrolled if they had a preoperative biopsy confirming primary BC and were scheduled for surgical treatment. All patients underwent CUS, SE, and CEUS examinations preoperatively. Histopathological findings of NAC after surgical resection served as the gold standard. Least absolute shrinkage and selection operator (LASSO) regression was applied to identify the predictors most strongly associated with NAC involvement. The diagnostic performance of different model combinations (CUS, CUS + SE, CUS + SE + CEUS) was compared using receiver operating characteristic (ROC) analysis with the DeLong test. A multi-parametric ultrasonography nomogram was developed and internally validated by 500 bootstrap resamples, with calibration curve analysis assessing its predictive accuracy and decision curve analysis (DCA) evaluating its clinical utility. Results: A total of 166 lesions were enrolled from 164 patients, comprising 33 (19.9%) lesions with NAC involvement and 133 (80.1%) lesions with NAC non-involvement. LASSO regression identified four independent predictors: ductal echo extending from the lesion on CUS, the mean elastography strain value of nipple on SE, and ductal enhancement extending to the nipple and focal nipple enhancement on CEUS. The combined CUS + SE + CEUS model demonstrated the highest diagnostic efficacy with an area under the curve (AUC) of 0.917, a sensitivity of 90.91%, and a negative predictive value (NPV) of 97.32%. Its performance was significantly better than that of CUS alone (AUC =0.732, P<0.001) and CUS + SE (AUC =0.859, P=0.009). The nomogram based on multi-parametric ultrasonography showed good calibration and internal validation (bias corrected AUC =0.916). DCA confirmed net benefit across clinically relevant thresholds. Conclusions: The multi-parametric ultrasonography nomogram demonstrated excellent performance in predicting NAC involvement and offers a valuable, non-invasive tool for preoperative surgical planning.
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