Predictive value of contrast-enhanced ultrasound combined with conventional ultrasound in solid renal parenchymal lesions

Abstract

Objective: This study aimed to develop a model to predict the risk of malignancy in solid renal parenchymal lesions based on the imaging features of combined conventional and contrast-enhanced ultrasound (CEUS). Methods: A retrospective review was performed among patients with focal solid renal parenchymal lesions on ultrasound images. Ultrasound features were characterized by two experienced radiologists independently. A multiple logistic regression analysis was performed to determine the most relevant features and to estimate the risk of malignancy. Scoring and counting methods were developed based on the most relevant features. The diagnostic performance was evaluated by the sensitivity, specificity, positive predictive value, negative predictive value and area under the receiver operating characteristic curve (AUC). Results: A total of 519 renal lesions were included in this study. The conventional ultrasound features of diameter, echogenicity, hypoechoic rim and the CEUS feature of heterogeneity were identified as the most relevant features for prediction of malignancy. The sensitivity and specificity for the logistic regression model, the scoring method and the counting method were 95.3 and 93.4%, 93.8 and 87.8%, 88.8 and 93.9%, respectively. The logistic model had the best performance for diagnosing malignant renal lesions with AUC of 0.978, compared with the scoring method and the counting method with AUCs of 0.958 and 0.965. Conclusion: The combination of contrast-enhanced ultrasound with conventional ultrasound improved the diagnostic performance of solid renal lesions based on the logistic regression model. Advances in knowledge: In this study, we revealed that the combination of CEUS and conventional ultrasound provided higher accuracy for diagnosing malignant renal tumors.