ArticleBreast cancer (Dove Medical Press)2023
Radiomics Analysis of Breast Lesions in Combination with Coronal Plane of ABVS and Strain Elastography.
Article in Breast cancer (Dove Medical Press), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- A Systematic Review and Meta-analysis of Two-Dimensional Breast Ultrasound Radiomics: Implications for Lesion Characterization and Diagnostic Accuracy.Journal of imaging informatics in medicine · 2026Review
- Deep learning-based multimodal integration of imaging and clinical data for predicting surgical approach in percutaneous transforaminal endoscopic discectomy.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2025Article
- Advances and innovations in ultrasound-based tumor management: current applications and emerging directions.The ultrasound journal · 2025Review
- Artificial intelligence-based automated breast ultrasound radiomics for breast tumor diagnosis and treatment: a narrative review.Frontiers in oncology · 2025Review
- Article
- Integrating multimodal ultrasound imaging and machine learning for predicting luminal and non-luminal breast cancer subtypes.Frontiers in oncology · 2025Article
- Application Value of A Clinical Radiomic Nomogram for Identifying Diabetic Nephropathy and Nondiabetic Renal DiseaseCurrent medical imaging · 2025Article
- Deep learning radiomics on grayscale ultrasound images assists in diagnosing benign and malignant of BI-RADS 4 lesions.Scientific reports · 2024Article
- A clinical-radiomics nomogram based on multimodal ultrasound for predicting the malignancy risk in solid hypoechoic breast lesions.Frontiers in oncology · 2023Article
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Abstract
Background: Breast cancer is the most common tumor globally. Automated Breast Volume Scanner (ABVS) and strain elastography (SE) can provide more useful breast information. The use of radiomics combined with ABVS and SE images to predict breast cancer has become a new focus. Therefore, this study developed and validated a radiomics analysis of breast lesions in combination with coronal plane of ABVS and SE to improve the differential diagnosis of benign and malignant breast diseases. Patients and Methods: 620 pathologically confirmed breast lesions from January 2017 to August 2021 were retrospectively analyzed and randomly divided into a training set (n=434) and a validation set (n=186). Radiomic features of the lesions were extracted from ABVS, B-ultrasound, and strain elastography (SE) images, respectively. These were then filtered by Gradient Boosted Decision Tree (GBDT) and multiple logistic regression. The ABVS model is based on coronal plane features for the breast, B+SE model is based on features of B-ultrasound and SE, and the multimodal model is based on features of three examinations. The evaluation of the predicted performance of the three models used the receiver operating characteristic (ROC) and decision curve analysis (DCA). Results: The area under the curve, accuracy, specificity, and sensitivity of the multimodal model in the training set are 0.975 (95% CI:0.959-0.991),93.78%, 92.02%, and 96.49%, respectively, and 0.946 (95% CI:0.913 -0.978), 87.63%, 83.93%, and 93.24% in the validation set, respectively. The multimodal model outperformed the ABVS model and B+SE model in both the training ( Conclusion: Radiomics from the coronal plane of the breast lesion provide valuable information for identification. A multimodal model combination with radiomics from ABVS, B-ultrasound, and SE could improve the diagnostic efficacy of breast masses.
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