Abstract

ObjectiveBreast cancer has become one of the main diseases threatening women’s health and lives. Ultrasound (US) is the first diagnostic option for several patients because of its non-radiation, convenient, and low-cost features. Conventional US combined with contrast-enhanced US (CEUS) has improved diagnostic accuracy, while due to the presence of numerous parameters, no international consensus on diagnostic criteria could be attained. Therefore, it is necessary to develop a reliable diagnostic model with the involvement of a few parameters while increasing the diagnostic accuracy. MethodsData from 265 patients, including conventional US, CEUS, and postoperative pathological results, were collected. 21 parameters from the conventional US and both qualitative and quantitative aspects of CEUS were analyzed through univariate and multivariate logistic regression analyses. Specific parameters with independent influential factors were identified. A nomogram was subsequently developed to visually represent the contribution and linear weighting of each parameter. The effectiveness of the new model was assessed through calibration curves and the Hosmer-Lemeshow goodness-of-fit test. ResultsSix independent influential factors for breast malignant tumors were identified, including homogeneous echo, lesion vascularity, enhancement mode, enhancement shape, nourishing vessels, and slope. The area under the curve (AUC) values in the training and test datasets were 0.933 and 0.860, respectively. The modified model exhibited satisfactory diagnostic accuracy and operability. ConclusionThe modified model, despite incorporating fewer parameters, maintained diagnostic accuracy. It is exhibited as a convenient, effective, and easily deployable model for diagnosing malignant breast nodules.

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