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Small (<4 cm) clear cell renal cell carcinoma: correlation between CT findings and histologic grade
Soo Yeon Choi1, Deuk Jae Sung2, Kyung Sook Yang3
1Department of Radiology, Anam Hospital, Korea University College of Medicine, Seoul, South Korea.
Abdominal Radiology (New York)
|April 5, 2016
Summary
CT imaging features can predict the grade of small clear cell renal cell carcinoma (ccRCC). Low attenuation and homogeneous enhancement patterns on CT scans are independent predictors of low-grade ccRCC, aiding treatment strategies.
Area of Science:
- Radiology
- Oncology
- Medical Imaging
Background:
- Clear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancer.
- Accurate grading of ccRCC is crucial for determining prognosis and guiding treatment decisions.
- Distinguishing between low-grade and high-grade ccRCC pre-therapeutically can optimize patient management.
Purpose of the Study:
- To investigate the correlation between computed tomography (CT) imaging findings and the histologic grade of small clear cell renal cell carcinoma (ccRCC).
- To identify specific CT features that can predict the biologic behavior and grade of small ccRCC.
- To assess the utility of CT in differentiating low-grade from high-grade ccRCC.
Main Methods:
- Retrospective review of CT scans from 101 patients with small ccRCC.
- Radiologists assessed tumor size, shape, margin, encapsulation, and enhancement patterns (homogeneous, relatively homogeneous, heterogeneous).
- Quantitative CT parameters and histologic grades (Fuhrman I-IV) were analyzed using univariate and multivariate logistic regression.
Main Results:
- Low-grade ccRCC (63 cases) showed significantly different CT features compared to high-grade ccRCC (38 cases).
- Features associated with low-grade ccRCC included homogeneous or relatively homogeneous enhancement patterns and lower attenuation on unenhanced scans (≤30 HU).
- Multivariate analysis identified enhancement pattern and low attenuation as independent predictors of low-grade ccRCC, with logistic regression achieving 70.3%-79.2% accuracy.
Conclusions:
- CT imaging features, specifically tumor attenuation and enhancement patterns, are valuable for predicting the histologic grade of small ccRCC.
- These CT findings can help predict the biologic behavior of ccRCC, informing the selection of appropriate treatment strategies.
- Utilizing CT characteristics may lead to more tailored and effective management plans for patients with small ccRCC.
