Machine learning–based diagnostic evaluation of shear-wave elastography in BI-RADS category 4 breast cancer screening: a multicenter, retrospective study

Abstract

Background: Ultrasound is commonly used in breast cancer screening but lacks quantification ability and diagnostic power due to its low specificity, which can lead to overdiagnosis and unnecessary biopsies. This study evaluated the diagnostic efficacy and clinical utility of adding shear-wave elastography (SWE) to the screening of the Breast Imaging Reporting and Data System (BI-RADS) category 4 breast cancer.Methods: A machine learning-based diagnostic model was constructed using data retrospectively collected from 3 independent cohorts with features selected using lasso regression and support vector machine-recursive feature elimination algorithms. Propensity score matching (PSM) was used to preclude confounding baseline characteristics between malignant and benign lesions. A decision curve analysis (DCA) was used to evaluate the clinical benefit of the diagnostic model in identifying high-risk tumor patients for intervention while simultaneously avoiding overtreatment of low-risk patients with integrative evaluation using a net benefit value and treatment reduction rate.Results: In our training center, a total of 122 patients were enrolled, and 577 breast tumors were collected.The comparison between malignant and benign lesions revealed significant differences in patient age, tumor size, resistance index (RI), and elasticity values. The maximum elasticity value (Emax) was identified as an independent diagnostic feature and was included in the diagnostic model. The combination of Emax with BI-RADS category 4 demonstrated a significantly better diagnostic efficacy than the BI-RADS category alone [BI-RADS+Emax: AUC: 0.908, 95% confidence interval (CI), 0.842−0.974; BI-RADS: AUC =0.862, 95% CI, 0.784−0.94; P=0.024] and significantly increased the clinical benefit for patients and policy makers by effectively reducing overdiagnosis and biopsy rates. In the BI-RADS category 4A subgroup, adding Emax to breast cancer screening benefited patients and showed a greater absolute benefit than did the BI-RADS category alone when used for patients with a higher probability of cancer (>0.403), demonstrating a 50% overtreatment reduction.Conclusions: Adding Emax to BI-RADS category 4 breast cancer screening using SWE significantly reduced overdiagnosis and biopsy rates compared with the BI-RADS category alone, especially for BI-RADS 4A patients. 2 Tang et al. SWE for BI-RADS 4 breast cancer screening

Comparative study of pathological response evaluation systems after neoadjuvant chemotherapy for breast cancer: developing predictive models of multimodal ultrasound features including shear wave elastography combined with puncture pathology

“…Recent research reported that the maximum area of stiffness in malignant tumors was consistently found in the peritumoral stroma rather than inside the tumor (29,30). Potential causes of the "stiff rim" sign have been suggested to be a desmoplastic response and infiltration of tumor cells into the peritumoral stroma (2,31). As a consequence, the tissues surrounding the tumor's edge or periphery are often stiffer (referred to as the "stiff rim") (32), increasing their stiffness by a factor of 2-10 or more (33).…”

Use of shear-wave elastography to distinguish complex and complicated fibroadenomas from simple fibroadenomas

“…In the literature, various studies have discussed the diagnostic performance of additional SWE findings for differentiating malignant and benign breast lesions and for evaluating fibroepithelial lesions, including fibroadenomas. 2 , 23 , 27 , 28 , 29 , 30 , 31 Two studies have evaluated the contribution of SWE findings to the diagnosis of fibroadenomas. 2 , 29 Evans et al 2 evaluated both B-mode US and SWE features for diagnosing fibroadenomas in the absence of biopsy, concluding that, because clinically benign solid breast lesions with benign B-mode US and SWE findings exhibited no malignant transformation, biopsy and follow-up procedures were unnecessary.…”

Clinical use and adjustment of ultrasound elastography for breast lesions followed WFUMB guidelines and recommendations in the real world

“…However, the role of SWE in the diagnosis, differentiation, efficacy evaluation and prediction of breast cancer was obvious ( 13 , 14 , 27 ). One study demonstrated the superior predictive value of Emax in combination with BI-RADS category 4a in breast cancer screening ( 28 ). Another research found that Emax was the best parameter for classifying breast lesions, with a maximum AUC of 0.90 (95%CI: 0.77-1.00) ( 29 ).…”