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

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.

Can diffusion-weighted magnetic resonance imaging of clear cell renal carcinoma predict low from high nuclear grade tumors

OBJECTIVE

To assess the diagnostic performance of the apparent diffusion coefficient (ADC) in predicting the Fuhrman nuclear grading of clear cell renal cell carcinomas (ccRCC).

MATERIALS AND METHODS

A total of 129 patients who underwent partial and radical nephrectomies with pathology-proven ccRCC were retrospectively evaluated. Histopathological characteristics and nuclear grades were analyzed. In addition, conventional magnetic resonance imaging (MRI) features were assessed in consensus by two radiologists to discriminate nuclear grading. ADC values were obtained from a region of interest (ROI) measurement in the ADC maps calculated from diffusion-weighted imaging (DWI) using b values of 50, 500, and 800 s/mm². The threshold values for predicting and differentiating low-grade cancers (Fuhrman I-II) from high grade (Fuhrman III-IV) was obtained using binary logistic regression. The ADC cut-off value for differentiating low- and high-grade tumors was determined using classification analysis.

RESULTS

Significant associations (P < 0.001) were found between nuclear grading, conventional MR features, and DWI. Hemorrhage, necrosis, perirenal fat invasion, enhancement homogeneity, and cystic component were identified as independent predictors of tumor grade. High-grade ccRCC had significantly lower mean ADC values compared to low-grade tumors. An ADC cut-off value of 1.6 × 10^-3 mm²/s had an optimal predictive percentage of 65.5% for low-grade tumors above this threshold and 81% for high-grade ccRCC below this threshold. Overall predictive accuracy was 70.5%.

CONCLUSION

The addition of ADC values to a model based on MRI conventional features demonstrates increased sensitivity and high specificity improving the distinguishing accuracy between both high-grade and low-grade ccRCC.

Renal paraganglioma: report of a case managed by robotic assisted laparoscopic partial nephrectomy and review of the literature

We describe the pathological and clinical presentation of a rare case of renal paraganglioma occurring as an incidental left renal mass in a 58-year-old woman. The patient underwent robotic assisted laparoscopic partial nephrectomy, which is the first one in the literature.