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% CI 0.61–0.91, 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.
Urinary tract stones (urolithiasis) are one of the most common causes of acute and chronic pain causing significant morbidity. The lifetime incidence in developed countries is about 10% to 15%, with a relapse rate of 50% in 10 years and 75% in 20 years . One of the key factors for optimizing the management of patients with urolithiasis is the chemical composition of the stone . Medical treatment, preoperative evaluation, and the strategy for recurrence prevention are all influenced by stone type. For example, because uric acid stones can dissolve in urine of higher pH, alkalization of the urine is often effective. Extracorporeal shock wave lithotripsy is commonly used for stone removal , but certain firm stones, such as brushite and some calcium oxalate (CaOx) stones, resist fragmentation. Overall, unnecessary procedures can potentially be avoided if the chemical composition is readily known in the initial stage of patient evaluation .
About 80% of stones are composed of CaOx and/or hydroxyapatite (HA) . These two stone types form under different physiochemical conditions, making the differentiation between the two stone types desirable for both research and treatment purposes . Twenty-four-hour urine collection used to measure key components in the urine is the most common method to assess kidney stone risk factors. For example, CaOx stones can form under a wide range of physiologic urinary pH conditions, while HA stones tend to form in alkaline urine . Urinary supersaturation (SS) calculated from the composition of a twenty-four-hour urine collection also correlates with the crystalline component of the stones passed . Therefore, physicians rely largely on urine pH and urine SS profile to predict stone composition when a previous stone analysis is not available.
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Materials and methods
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Patient Inclusion
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Clinical CT Data Acquisition and Image Processing
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Clinical Lab Urine Evaluations
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Statistical Analysis
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Results
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Table 1
Dual-energy CTR, SS-HA, SS-CaOx, and Urine pH of CaOx and HA Stone Patients
CaOx HA_P_ Value Mean ± SD Range Mean ± SD Range CTR 1.40 ± 0.13 1.17 to 1.68 1.49 ± 0.11 1.35 to 1.71 .016 SS-HA, D.G. 3.29 ± 1.95 −1.94 to 6.72 5.43 ± 2.67 −0.74 to 9.36 <.01 SS-CaOx, D.G. 1.85 ± 0.57 0.29 to 2.86 1.68 ± 0.64 0.45 to 2.54 .32 Urine pH 6.0 ± 0.7 4.7 to 7.5 6.2 ± 0.6 5.2 to 7.6 .20
CaOx, calcium oxalate; CTR, computed tomography number ratio; D.G., delta gibbs; HA, hydroxyapatite; SD, standard deviation; SS, supersaturation.
Table 2
Summary of Statistical Analysis Result Using One or Combination of Variables as Predictor(s) of Stone Type
Variable(s) Area Under ROC Curve (C-statistic) 95% Confidence Interval_P_ Value CTR 0.78 0.66–0.91 .016 SS-HA 0.76 0.61–0.91 .003 SS-CaOx 0.57 0.42–0.73 .32 Urine pH 0.60 0.44–0.75 .20 CTR + SS-HA 0.79 0.66–0.92 .007 ∗ CTR + urine pH 0.77 0.65–0.88 .02 ∗ CTR + SS-HA + urine pH 0.80 0.67–0.92 .07 ∗
CaOx, calcium oxalate; CTR, computed tomography number ratio; HA, hydroxyapatite; SS, supersaturation.
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Discussion and conclusion
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Acknowledgments
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