Imaging Tool for Predicting Renal Clear Cell Carcinoma Fuhrman Grade: Comparing R.E.N.A.L. Nephrometry Score and CT...

Area of Science:

• Oncology
• Radiology
• Medical Imaging

Background:

• Clear cell renal cell carcinoma (ccRCC) is the most prevalent renal malignancy.
• Preoperative imaging is crucial for ccRCC diagnosis and treatment planning.

Purpose of the Study:

• To develop and compare models using R.E.N.A.L. nephrometry score (RNS) and CT texture analysis (CTTA) for estimating ccRCC Fuhrman grade.
• To evaluate the diagnostic performance of RNS and CTTA in predicting tumor aggressiveness.

Main Methods:

• 143 ccRCC patients with confirmed pathology were analyzed.
• RNS and CTTA features were extracted from CT images.
• Logistic regression models were built using RNS and CTTA features to predict Fuhrman grade.

Main Results:

• The RNS model showed an AUC of 0.911, with R, E, and L scores as significant predictors.
• The CTTA model identified energy, kurtosis, and entropy as independent predictors, achieving an AUC of 0.941.
• CTTA exhibited higher sensitivity (84.44%) and specificity (93.88%) compared to RNS (71.11% and 83.67%).

Conclusions:

• RNS has a predictive role in ccRCC Fuhrman grading.
• CTTA shows potential to surpass RNS in evaluating Fuhrman classification for ccRCC.
• CTTA may offer a valuable tool for clinicians in surgical decision-making for ccRCC.