TY - JOUR
T1 - Differentiating Calcium Oxalate and Hydroxyapatite Stones InVivo Using Dual-Energy CT and Urine Supersaturation and pH Values
AU - Liu, Yu
AU - Qu, Mingliang
AU - Carter, Rickey E.
AU - Leng, Shuai
AU - Ramirez-Giraldo, Juan Carlos
AU - Jaramillo, Giselle
AU - Krambeck, Amy E.
AU - Lieske, John C.
AU - Vrtiska, Terri J.
AU - McCollough, Cynthia H.
N1 - Funding Information:
This study was supported by the Mayo Clinic O'Brien Urology Research Center P50 DK083007 from the National Institute of Diabetes and Digestive and Kidney Diseases . Dr Cynthia McCollough receives research support from Siemens Healthcare . The other authors have nothing to disclose. The authors would like to thank Amy Nordstrom for her assistance with manuscript preparation.
PY - 2013/12
Y1 - 2013/12
N2 - Rationale and Objectives: Knowledge of urinary stone composition can guide therapeutic intervention for patients with calcium oxalate (CaOx) or hydroxyapatite (HA) stones. In this study, we determined the accuracy of noninvasive differentiation of these two stone types using dual-energy CT (DECT) and urine supersaturation (SS) and pH values. Materials and Methods: Patients who underwent clinically indicated DECT scanning for stone disease and subsequent surgical intervention were enrolled. Stone composition was determined using infrared spectroscopy. DECT images were processed using custom-developed software that evaluated the ratio of CT numbers between low- and high-energy images. Clinical information, including patient age, gender, and urine pH and supersaturation profile, was obtained from electronic medical records. Simple and multiple logistic regressions were used to determine if the ratio of CT numbers could discriminate CaOx from HA stones alone or in conjunction with urine supersaturation and pH. Results: Urinary stones (CaOx n=43, HA n=18) from 61 patients were included in this study. In a univariate model, DECT data, urine SS-HA, and urine pH had an area under the receiver operating characteristic curve of 0.78 (95% confidence interval [CI] 0.66-0.91, P=016), 0.76 (95% CI0.61-0.91, P=003), and 0.60 (95% CI 0.44-0.75, P=20), respectively, for predicting stone composition. The combination of CT data and the urinary SS-HA had an area under the receiver operating characteristic curve of 0.79 (95% CI 0.66-0.92, P=007) for correctly differentiating these two stone types. Conclusions: DECT differentiated between CaOx and HA stones similarly to SS-HA, whereas pH was a poor discriminator. The combination of DECT and urine SS or pH data did not improve this performance.
AB - Rationale and Objectives: Knowledge of urinary stone composition can guide therapeutic intervention for patients with calcium oxalate (CaOx) or hydroxyapatite (HA) stones. In this study, we determined the accuracy of noninvasive differentiation of these two stone types using dual-energy CT (DECT) and urine supersaturation (SS) and pH values. Materials and Methods: Patients who underwent clinically indicated DECT scanning for stone disease and subsequent surgical intervention were enrolled. Stone composition was determined using infrared spectroscopy. DECT images were processed using custom-developed software that evaluated the ratio of CT numbers between low- and high-energy images. Clinical information, including patient age, gender, and urine pH and supersaturation profile, was obtained from electronic medical records. Simple and multiple logistic regressions were used to determine if the ratio of CT numbers could discriminate CaOx from HA stones alone or in conjunction with urine supersaturation and pH. Results: Urinary stones (CaOx n=43, HA n=18) from 61 patients were included in this study. In a univariate model, DECT data, urine SS-HA, and urine pH had an area under the receiver operating characteristic curve of 0.78 (95% confidence interval [CI] 0.66-0.91, P=016), 0.76 (95% CI0.61-0.91, P=003), and 0.60 (95% CI 0.44-0.75, P=20), respectively, for predicting stone composition. The combination of CT data and the urinary SS-HA had an area under the receiver operating characteristic curve of 0.79 (95% CI 0.66-0.92, P=007) for correctly differentiating these two stone types. Conclusions: DECT differentiated between CaOx and HA stones similarly to SS-HA, whereas pH was a poor discriminator. The combination of DECT and urine SS or pH data did not improve this performance.
KW - Composition characterization
KW - Dual-energy CT
KW - Urinary stones
KW - Urine pH
KW - Urine supersaturation
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U2 - 10.1016/j.acra.2013.08.018
DO - 10.1016/j.acra.2013.08.018
M3 - Article
C2 - 24200478
AN - SCOPUS:84887209665
SN - 1076-6332
VL - 20
SP - 1521
EP - 1525
JO - Academic Radiology
JF - Academic Radiology
IS - 12
ER -