Objective To explore the value of BI-RADS scoring system based on the sonographic features in the breast nodules.Methods In order to build a Logistic regression model,regression was made to analyse 401 patients ' sonographic features of breast nodules.A scoring system was developed based on the results of regression's filter and the weight of each factor,used to score and classify the other 243 patients.It's diagnostic value was evaluated through comparing all types of theoretic risk ranges of BI-RADS.Results Age,morphology,orientation,margin,echo pattern and microcalcifications in a mass were selected in the final step of the logistic regression analysis.By means of scoring system,the scores corresponding to BI-RADS 3,4a,4b,4c,5 classes are 6,7-8,9-15,16-22 and ≥23 respectively.Case study comprehensive score of BI-RADS 3-5 classification' s positive predictive values were 0,4.17％,21.43％,84.85％,1 00％,and the area under the ROC curve scoring system was 0.947.Conclusions The scoring system can objectively score and classify breast nodules,and therefore provide an effective reference for clinical evaluation of benign and malignant breast.

Objective:To investigate the value of multimodal ultrasound features combined with peripheral blood inflammatory cell ratios in evaluating the efficacy of neoadjuvant chemotherapy (NAC) in breast cancer.Methods:A total of 106 breast cancer patients diagnosed and treated with NAC at the Second Affiliated Hospital of Anhui Medical University from May 2021 to April 2024 were retrospectively collected, resulting in the conclusion of 61 patients (61 masses) in the study. All patients underwent multimodal ultrasound and peripheral blood routine examinations before NAC and after two cycles of NAC treatment. The patients were divided into a major histological response (MHR) group and a non-major histological response (NMHR) group as indicators for evaluating NAC efficacy. The differences in multimodal ultrasound features and inflammatory cell ratios before NAC and after two cycles of NAC treatment between the MHR and NMHR groups were compared. Binary logistic multivariate regression analysis was performed to determine the independent predictors of NAC efficacy in breast cancer. ROC curves were plotted to evaluate the diagnostic efficacy of predicting NAC efficacy.Results:Among the 61 breast masses, 25 (40.98%) were in the MHR group, and 36 (59.02%) were in the NMHR group.Multivariate binary logistic regression analysis showed that the change rate of maximum tumor diameter after the second cycle (ΔD 2), change rate of vascular index after the second cycle (ΔVI 2), change rate of elastic strain ratio after the second cycle (ΔE-Strain 2), change rate of reverse imaging score after the second cycle (ΔI-imaging score 2), and platelet-to-lymphocyte ratio (PLR) before NAC were independent predictors of NAC efficacy ( OR=1.145, P=0.019; OR=1.055, P=0.016; OR=1.036, P=0.033; OR=1.276, P=0.016; OR=1.054, P=0.047). The area under the ROC curve (AUC) for the combined diagnosis of the above parameters was 0.928 (95% CI=0.866~0.990), with a sensitivity of 80.0% and a specificity of 91.7%. Conclusions:The combination of ΔD 2, ΔVI 2, ΔE-Strain 2, ΔI-imaging score 2 and PLR before NAC has high clinical application value for early prediction of NAC efficacy in breast cancer.