Diagnostic value of multimodal ultrasound for breast cancer and prediction of sentinel lymph node metastases - Li, Hui; Chen, Lixia; Liu, Meikuai; Bao, Meng; Zhang, Quanbo; Xu, Shihao (Frontiers in Cell and Developmental Biology, 2024)
Background: Sentinel lymph node metastasis (SLNM) is a critical factor in the prognosis and treatment planning for breast cancer (BC), as it indicates the potential spread of cancer to other parts of the body. Accurate prediction and diagnosis of SLNM are essential for improving clinical outcomes and guiding treatment decisions. Objective: This study aimed to construct a Lasso regression model by integrating multimodal ultrasound techniques, including ultrasound (US), shear-wave elastography (SWE), and contrast-enhanced ultrasound (CEUS), to improve the predictive accuracy of SLNM in BC and provide more precise guidance for clinical treatment. Results: A total of 253 eligible samples were screened, of which 148 were Group benign and 105 were Group malignant. There were statistically significant differences (P<0. 05) between Group malignant patients in terms of Age, Palpable mass, BMI, Distance to nipple, maximum diameter, Blood flow, Echogenicity, 2D Border, 2D morphology and Internal homogeneity were statistically different compared with Group benign (P<0. 05). The Lasso regression model was useful in the diagnosis of benign and malignant BC nodules. with an AUC of 0. 968 and in diagnosing SLNM with an AUC of 0. 832. Conclusion: In this study, we successfully constructed and validated a Lasso regression model based on the multimodal ultrasound technique for predicting whether LNM occurs in BCS, showing high diagnostic accuracy.