ArticleQuantitative imaging in medicine and surgery2023
Role of combined clinical-radiomics model based on contrast-enhanced MRI in predicting the malignancy of breast non-mass enhancements without an additional diffusion-weighted imaging sequence.
Article in Quantitative imaging in medicine and surgery, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Multiparametric MRI for non-mass enhancement breast lesions: a prospective diagnostic accuracy study.European radiology · 2026Article
- A radiomics-based nomogram for preoperatively predicting the invasiveness of nodular lung adenocarcinoma: a multicenter study.Translational lung cancer research · 2026Article
- An Updated Systematic Review and Meta-Analysis of Diagnostic Accuracy of Dynamic Contrast Enhancement and Diffusion-Weighted MRI in Differentiating Benign and Malignant Non-Mass Enhancement Lesions.Journal of clinical medicine · 2025Review
- The value of contrast-enhanced energy-spectrum mammography combined with clinical indicators in detecting breast cancer in Breast Imaging Reporting and Data System (BI-RADS) 4 lesions.Quantitative imaging in medicine and surgery · 2024Article
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9 authors.
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Abstract
Background: In our previous study, we developed a combined diagnostic model based on time-intensity curve (TIC) types and radiomics signature on contrast-enhanced magnetic resonance imaging (CE-MRI) for non-mass enhancement (NME). The model had a high diagnostic ability for differentiation without the additional diffusion-weighted imaging (DWI) sequence. In this study, we aimed to compare the diagnostic performance of the combined clinical-radiomics model based on CE-MRI and DWI in discriminating Breast Imaging-Reporting and Data System (BI-RADS) 4 NME breast lesions, ductal carcinoma in situ (DCIS), and invasive carcinoma. Methods: This retrospective study enrolled 364 NME lesions (343 patients). Of these, 183 malignant and 84 benign breast lesions classified as BI-RADS 4 NMEs by the initial diagnosis were reclassified based on the combined clinical-radiomics model and DWI, respectively. The nomogram score (NS) values for malignancy risk derived from the combined clinical-radiomics model and the minimal apparent diffusion coefficient (ADC) values from DWI were calculated and compared. The percentage of false positives were estimated in comparison with the original classification. Receiver operating characteristic (ROC) curve analysis was performed to determine the diagnostic value of the NS and minimal ADC values in distinguishing benign and malignant lesions, DCIS, and invasive breast carcinoma. An ablation experiment was used to test the value of the additional DWI sequence. Results: The diagnostic value of the NS values [area under curve (AUC) =0.843; 95% CI: 0.789-0.896] for discriminating the 267 NME breast lesions categorized as BI-RADS 4 was significantly higher than the minimal ADC values (AUC =0.662; 95% CI: 0.590-0.735). The NS values showed higher sensitivity, specificity, and accuracy compared with the minimal ADC values (sensitivity: 80.3% Conclusions: The combined clinical-radiomics model based on CE-MRI could improve the diagnostic performance in discriminating the BI-RADS 4 NME lesions without an additional DWI sequence. However, DWI may improve the diagnostic performance in discriminating DCIS from invasive cancer.
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