[Application of multimode MRI in prediction of nuclear grade of clear cell renal cell carcinoma]

Objective: To investigate the predictive value of multimode MRI features for nuclear grade of clear cell renal cell carcinoma (ccRCC). Methods: From January 2016 to October 2017, 381 patients (387 tumors) with ccRCC proven by pathology in Chinese PLA General Hospital First Medical Center were enrolled (male 293, female 88, age 24-87 years old). The clinical and imaging data of these patients were retrospectively analyzed, including clinical information (gender, age, BMI, smoke, hypertension) and preoperative renal MRI. Pre-and post-contrast MRI features were subjectively scored. The largest diameter of each lesion was measured. Two-sample t-test,Chi-squared test and binuary Logistic regression analysis were used to evaluate the predictive efficacy of clinical and MRI data. Results: According to WHO/ISUP nuclear grade system,all ccRCCs (n=387) were divided into low grade (n=322) and high grade group (n=65). Between two groups, there were significant differences in age and diameter((54±12) vs (59±10) years old, P=0.001; (4.1±2.2) vs (6.2±3.0) cm, P<0.01). In MRI scores,there were significant differences in scores of pseudocapsule, shape and margin,hemorrhage,enhancement degree,cystic-solid,intratumoral vessel,peritumoral vessel, renal sinus invasion, vein thrombosis, lymphadenopathy, necrosis, perinephric invasion and metastasis, DWI signal intensity between high grade group and low grade group (all P<0.01). Binuary Logistic regression analysis showed that shape and margin, enhancement degree and DWI signal intensity were independent predictors for high grade ccRCC (OR=0.181, 95%CI 0.049-0.666; OR=0.393, 95%CI 0.182-0.846; OR=0.336, 95%CI 0.155-0.728). A nomogram model for predicting the risk of high grade ccRCC was constructed. Conclusions: Multimode MRI features can differentiate low grade and high grade ccRCC. The nomogram developed in this study might aid urologist in the pre-operative prediction of nuclear grade of ccRCC,which might contribute to developing treatment strategy.