Objective: The aim of this study was to derive a model that predicts when a computed tomography (CT)-guided renal tumor biopsy will be diagnostic based on the tumor's unenhanced imaging characteristics.
Methods: The CT images used to guide percutaneous biopsy and the pathology reports of 276 consecutive patients undergoing renal tumor biopsy were retrospectively reviewed. The effect of tumor size, growth pattern, location, and CT attenuation on the diagnostic biopsy rate was assessed using univariate and multivariate techniques. A model was derived using logistic regression, and its discrimination was evaluated using receiver operator characteristic curves.
Results: The diagnostic rate for all masses was 76.8% (212/276). Univariate and multivariate analyses revealed that increasing size and solid tumor attenuation were associated with diagnostic biopsies. The model demonstrates a discrimination of 0.71.
Conclusions: The likelihood of a diagnostic biopsy of a solid tumor smaller than 1 cm and of any cystic tumor is significantly less than for larger solid renal tumors. The predictive model demonstrates moderate discrimination.