Preoperative determination of uric acid stones from computed tomography (CT) imaging would be of tremendous clinical utility. We proposed to design a software algorithm that can utilize data from non-contrast CT to predict the presence of uric acid stones.
Patients with pure uric acid (UA) and calcium oxalate (CaOx) stones were identified from our stone registry. Only stones >4 mm and clearly traceable from initial CT to final composition were included. A semi-automated, computer algorithm processed the image data. Hounsfield unit (HU) averages, maximums, eccentricity (deviation from circle), and kurtosis ("peakedness" versus "flatness") were automatically generated. These parameters were examined in several mathematical models to predict presence of UA stones.
100 patients, 52 with CaOx and 48 with UA stones were included in the final analysis. UA stones were significantly larger (9.0 mm vs 12.2 mm, p=0.03), but CaOx stones had both higher mean (457 HU vs. 315 HU, p = 0.001), and maximum attenuations (918 vs. 553 HU, p<0.001). Kurtosis was significantly higher in both axes for calcium oxalate stones (both p < 0.001). A composite algorithm using attenuation distribution pattern, average attenuation, and stone size had an overall sensitivity of 89%, specificity of 91%, PPV 91% and NPV 89% for predicting of UA stone.
A combination of stone size, attenuation intensity and attenuation pattern from conventional CT imaging is able to discern UA stones from CaOx stones with high sensitivity and specificity.
The Journal of urology. 2017 Sep 15 [Epub ahead of print]
Vishnu Ganesan, Shubha De, Nicholas Shkumat, Giovanni Marchini, Manoj Monga
Lerner College of Medicine, Cleveland Clinic Foundation, Cleveland, OH, USA., Glickman Urological Kidney Institute, Cleveland Clinic Foundation, Cleveland, OH, USA., Department of Diagnostic Imaging, The Hospital for Sick Children, Toronto, ON, Canada., Glickman Urological Kidney Institute, Cleveland Clinic Foundation, Cleveland, OH, USA; Section of Endourology, Division of Urology, Hospital das Clínicas, University of Sao Paulo Medical School , Sao Paulo, Brazil., Glickman Urological Kidney Institute, Cleveland Clinic Foundation, Cleveland, OH, USA. Electronic address: .