Renal CT algorithm for evaluating clear cell carcinoma in solid renal masses ≤ 4 cm: a retrospective chinese...

Area of Science:

• Radiology
• Oncology
• Medical Imaging

Background:

• Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer.
• Early and accurate diagnosis of small renal masses is crucial for effective treatment and patient outcomes.
• Renal CT imaging is a primary modality for evaluating renal masses, but differentiating ccRCC requires refined algorithms.

Purpose of the Study:

• To externally validate a renal CT algorithm for diagnosing ccRCC in solid renal masses ≤4 cm.
• To assess the inter-reader agreement of the algorithm based on reader experience and across different institutions.

Main Methods:

• A retrospective study of 217 patients with renal masses ≤4 cm from two Chinese centers.
• Radiologists evaluated attenuation ratio, heterogeneity, and CT score; histopathology served as the reference standard.
• Inter-reader agreement was assessed using Fleiss' weighted kappa; diagnostic performance was evaluated using ROC curve analysis.

Main Results:

• The algorithm demonstrated almost perfect inter-reader agreement for attenuation ratio and CT scores (κ=0.82-0.85).
• Area under the curve (AUC) ranged from 0.823 to 0.856, indicating good diagnostic accuracy.
• Sensitivity, specificity, and accuracy ranged from 68.8%–79.2%, with stable performance across readers and centers.

Conclusions:

• The renal CT score algorithm is reproducible and specific for diagnosing ccRCC in small renal masses.
• A CT score cutoff of ≥4 provides stable diagnostic performance, making it a promising low-cost tool for primary healthcare.
• Prospective validation is recommended to further establish its clinical utility.