Urolithiasis is a common problem in veterinary medicine. In dogs and cats, magnesium ammonium phosphate (struvite) and calcium oxalate uroliths are the most common types of uroliths, with incidence rates that range from 39% to 53% and 35% to 45%, respectively.1–3 Urate uroliths also occur commonly and account for approximately 24% of uroliths submitted for analysis.2 Although the overall incidence rate of urolithiasis has not changed dramatically over the past several decades, there has been a noticeable shift in the type of uroliths identified, with the incidence of struvite uroliths decreasing as the incidence of calcium oxalate uroliths increases. This shift is thought to be associated with improvements in the dietary management of patients with struvite uroliths. Unfortunately, the diets used to manage or prevent struvite uroliths increase the risk for the development of calcium oxalate uroliths.1–3
Cystic calculi are easily treated with surgery, but surgical treatment of renal and ureteral calculi is associated with substantial risk for complications. Both ESWL and intracorporeal shock wave lithotripsy are being used with increasing frequency for the treatment of cystic and renal or ureteral calculi, respectively. However, ESWL can have adverse effects such as hypertension, loss of renal function, and an increase in urolith recurrence.4 Not all uroliths are amenable to fragmentation with ESWL, with failure rates of 9.4% to 26.3% reported in human patients.5,6 The probability of treatment success for shock wave lithotripsy is dependent on urolith composition.5,6 Calcium oxalate, struvite, and hydroxyapatite uroliths are generally considered amenable to ESWL, whereas brushite and cystine uroliths are not.7–9 Uric acid uroliths are amenable to ESWL and medical management because they can be dissolved with dietary management if they are not causing an obstruction. Given the potential risks and costs associated with various treatment modalities for uroliths, it is clear that an in vivo method for determination of urolith composition would be advantageous to facilitate selection of the optimal treatment. Unfortunately, such a method is not currently available.
For a monoenergetic x-ray beam, the CT number, or HU, is a dimensionless quantity that represents the mean linear attenuation coefficient of patient tissue relative to water. The linear attenuation coefficient is the fraction of the x-ray photon interaction that is absorbed or scattered per unit (cm) of tissue thickness, and is dependent on the x-ray beam energy and mean atomic number for the patient tissue. Therefore, a CT image illustrates, or provides a visual representation of, the relative difference of the linear attenuation coefficient of various patient tissues with respect to water. The acquisition of CT images at various energies results in unique linear attenuation coefficients and, therefore, unique CT numbers. The typical energy range for diagnostic imaging is 60 to 140 kV. Within that energy range, there are 2 predominant interactions between the incident photon and atom: the photoelectric effect and Compton scatter. Dual-energy imaging exploits differences in the probability of the photoelectric and Compton interactions and the variability of k-edges among various tissues.10–12 Thus, the relative linear attenuation coefficients differ at different energies. Images are acquired at both high and low energies, and the image data are combined into dual-energy measurements. Although DECT scanners that can acquire these data in a single scan are available, they are not required to obtain dual-energy values. Measurements from 2 consecutively acquired scans can be used to calculate dual-energy values, the most common of which are the DECT number and DECT ratio. Dual-energy CT has been used to determine urolith composition in human patients,13–24 but its ability to determine the composition of uroliths in dogs has not been evaluated. The purpose of the study reported here was to evaluate whether DECT could accurately differentiate the composition of canine uroliths in a phantom model.
Materials and Methods
Thirty cystic calculi were obtained from the Canadian Veterinary Urolith Centre, Guelph, Ontario. Each urolith had undergone composition analysis and was determined to be > 70% pure for the primary component. Uroliths were suspended in the center of a 16-cm-diameter phantom made of agar and scanned with a 64-slice DECT scanner.a Two scans were acquired of each urolith, 1 at high energy (140 kV and 100 mAs) and 1 at low energy (80 kV and 100 mAs), with pitch equal to 1. All series used an axial scan with a slice thickness of 0.625 mm and an abdomen (soft tissue) reconstruction algorithm.
Images were viewed with a window width of 3,500 HU and window level of 1,000 HU. A manual ROI was drawn around the urolith excluding all visible partial-volume artifact along its periphery 3 times to obtain the mean CT number. A computer-generated ROI was then drawn for each urolith by use of a threshold value that included the entire stone. For each stone, high- and low-energy CT numbers were recorded, and the DECT number (low-energy CT number – high-energy CT number) and DECT ratio (low-energy CT number/high-energy CT number) were calculated.
Statistical analysis
The extent of agreement between the manual and computer-generated ROIs was determined by linear regression and concordance correlation. A Bland-Altman test with a Student t test of the differences was used to assess variation among measurements. The urolith composition as determined by standard laboratory analysis performed by the Canadian Veterinary Urolith Centre was used as the definitive, or gold standard, composition. The distribution of data for the manual ROIs and computer-generated ROI for each urolith was assessed for normality by means of a Shapiro-Wilk test and compared by use of multivariate ANOVA with a Tukey-Kramer adjustment to control for type I error when multiple pairwise comparisons were necessary. All analyses were performed with statistical software,b and values of P < 0.05 were considered significant.
Results
Of the 30 uroliths evaluated, 10 were composed of struvite, 8 were composed of urate, 5 were composed of cystine, 4 were composed of calcium oxalate, and 3 were composed of brushite. Struvite and urate uroliths were overrepresented in the study because of selection bias (only uroliths with > 70% pure composition were evaluated). In dogs, urate uroliths form in response to metabolic changes and are likely to be of pure composition. Struvite uroliths form secondary to infection, and their occurrence tends to increase as the incidence of urinary tract infection increases. The diameter of the uroliths ranged from 1 to 40 mm (median, 7 mm).
Data were normally distributed. There was significant (P < 0.001) and excellent correlation (r > 0.95) between the mean DECT number for the 3 manual ROIs and DECT number for the computer-generated ROI (Figure 1). No bias was detected between the DECT numbers calculated from the manual ROI and the computer-generated ROI. The repeatability of manual ROI measures was also excellent (r > 0.90; P < 0.01). The DECT number was not significantly (P < 0.01) associated with urolith size.
Correlation between the mean DECT number for the 3 manual ROIs and the DECT number for the computer-generated ROI for 30 canine uroliths with pure compositions (ie, composed of ≥ 70% struvite [n = 10], urate [8], cystine [5], calcium oxalate [4], or brushite [3], as determined by standard laboratory methods performed at the Canadian Veterinary Urolith Centre). There was significant (P < 0.001) and excellent correlation (r > 0.95) between the 2 measures.
Citation: American Journal of Veterinary Research 78, 10; 10.2460/ajvr.78.10.1150
The mean ± SD values for high- and low-energy CT numbers, DECT number, and DECT ratio for each type of urolith were tabulated (Table 1). Results of the multivariate ANOVA were similar between data obtained by use of the manual ROIs and data obtained by use of a computer-generated ROI. No single DECT measurement was able to differentiate all types of uroliths, but the low-energy CT number, DECT number, and DECT ratio differed significantly between multiple pairwise combinations of urolith types (Table 2). All 3 variables (low-energy CT number, DECT number, and DECT ratio) were able to distinguish struvite uroliths from urate uroliths, calcium oxalate uroliths from urate uroliths, and brushite uroliths from urate uroliths. Urate uroliths were distinguishable from cystine uroliths only on the basis of the DECT ratio. Calcium oxalate uroliths were distinguishable from brushite uroliths only on the basis of the DECT number. None of the variables assessed were able to distinguish between struvite and cystine uroliths.
Mean ± SD values for the high- and low-energy CT numbers, DECT number, and DECT ratio for each of 5 types of uroliths as determined by DECT and measurement by use of manual ROIs.
| Urolith composition | No. of uroliths evaluated | High-energy CT No. (HU) | Low-energy CT No. (HU) | DECT No. (HU) | DECT ratio |
|---|---|---|---|---|---|
| Struvite | 10 | 797 ± 62 | 1,050 ± 87 | 253 ± 29 | 1.31 ± 0.02 |
| Calcium oxalate | 4 | 1,093 ± 98 | 1,584 ± 138 | 491 ± 46 | 1.45 ± 0.04 |
| Cystine | 5 | 506 ± 88 | 668 ± 124 | 162 ± 41 | 1.33 ± 0.03 |
| Urate | 8 | 496 ± 69 | 550 ± 98 | 54 ± 33 | 1.09 ± 0.03 |
| Brushite | 3 | 1,403 ± 98 | 2,012 ± 160 | 609 ± 53 | 1.43 ± 0.04 |
Each urolith was determined to be > 70% pure for the primary component on the basis of results of standard laboratory analyses performed by the Canadian Veterinary Urolith Centre. Each urolith was placed in the center of a 16-cm-diameter phantom made of agar, and DECT images were obtained by use of high-energy (140 kV and 100 mAs) and low-energy (80 kV and 100 mAs) settings. The images were viewed with a window width of 3,500 HU and window level of 1,000 HU. A manual ROI was drawn around the urolith, excluding all visible partial-volume artifact along its periphery, 3 times to obtain the mean high- and low-energy CT numbers for that urolith. The DECT number was calculated as the low-energy CT number – high-energy CT number, and the DECT ratio was calculated as the low-energy CT number/high-energy CT number.
Summary of pairwise comparisons between the various urolith types of Table 1 for which the low-energy CT number, DECT number, and DECT ratio did (X) or did not (—) differ significantly (P ≤ 0.05) as determined by multivariate ANOVA with a Tukey-Kramer adjustment to control for type I error inflation.
| Pairwise comparison | Low-energy CT No. | DECT No. | DECT ratio |
|---|---|---|---|
| Struvite-calcium oxalate | X | X | — |
| Struvite-urate | X | X | X |
| Struvite-cystine | — | — | — |
| Struvite-brushite | X | X | — |
| Calcium oxalate-urate | X | X | X |
| Calcium oxalate-cystine | X | X | — |
| Calcium oxalate-brushite | — | X | — |
| Urate-cystine | — | — | X |
| Urate-brushite | X | X | X |
| Cystine-brushite | X | X | — |
See Table 1 for key.
Discussion
Both ESWL and intracorporeal shock wave lithotripsy are becoming increasingly available in veterinary practice. The ability of those techniques to fragment various calculi is dependent on the composition of the calculi. Thus, an in vivo method for determining the composition of calculi would be beneficial for selection of the appropriate treatment. Unfortunately, the results of the present study indicated that DECT was unable to differentiate clinically important types of canine uroliths.
Computed tomography attenuation values are related to material density in a nonlinear manner (Figure 2). Use of a single-energy technique to obtain CT attenuation values for uroliths was promising initially when conducted in vitro,13 but findings of subsequent in vivo studies25–28 suggest that single-energy CT scans have poor reproducibility and the calculated attenuation for the various types of uroliths overlaps too much to be useful. Partial-volume averaging with surrounding soft tissues confounds use of single-energy CT attenuation values in vivo and makes them less accurate than DECT measures. The use of wide collimation and high pitch in vivo can artificially decrease the density of a urolith because the surrounding soft tissue is often included in the attenuation measurement.29 This may explain the discrepancies in the CT attenuation values noted between in vitro13 and in vivo25–28 studies because CT scans performed in vivo tend to have a thinner collimation than those performed in vitro.16 Although collimation artifact can be corrected by use of a mathematical model, it has become less of a problem with the increasing use of multislice CT scanners capable of submillimeter collimation.29 In the present study, the CT number did not differ significantly between the manually drawn ROIs, which excluded the urolith periphery that may have been affected by partial-volume averaging, and the computer-generated ROIs, which encompassed the entire urolith. That finding suggested that partial-volume averaging may not affect the CT number when submillimeter collimation is used.
Relative linear attenuation coefficients for water (solid line) and calcium (dashed line) from 10 to 120 kV. Notice that the attenuation coefficient varies in a nonlinear manner on the basis of material density and energy.
Citation: American Journal of Veterinary Research 78, 10; 10.2460/ajvr.78.10.1150
Results of the present study indicated that the DECT ratio, DECT number, and low-energy CT number were insufficient as stand-alone measurements to differentiate the various types of canine uroliths assessed. The DECT number was able to differentiate the greatest number of urolith types. When all 3 variables were assessed together, all urolith types could be differentiated except struvite and cystine. Radiographically, struvite uroliths are radiopaque, whereas cystine uroliths are not; therefore, the inability of DECT to differentiate between those 2 types of uroliths is not clinically relevant.
Dual-energy CT has been used to determine urolith composition in human patients with varying success.17–24 Potential reasons for the marked variability in the DECT results include errors in CT measurements related to beam-hardening artifact, partial-volume averaging, misregistration of the dual-energy images associated with patient motion between images, and CT scanner calibration errors. Partial-volume averaging should not affect dual-energy calculations because both the high- and low-energy measurements will be affected in a similar manner.20 However, for small uroliths, partial-volume averaging may result in incorrect material characterization even with dual-energy imaging because of inaccurate measurement of urolith density. Misregistration of images was a potential source of error in initial studies because the technology for the acquisition of images nearly simultaneously had not evolved. Images were either acquired in 2 consecutive scans at different energies or in alternating slices at different energies such that the images were offset by the slice thickness. Misregistration is unlikely to be an issue for veterinary patients that are anesthetized for CT scans, but may remain a potential source of error for patients that are only sedated. However, DECT scanners are now available that can acquire images nearly simultaneously, and misregistration is unlikely to be a source of error in studies that use those scanners.
Another explanation for the inability of DECT to differentiate among urolith types is that the linear attenuation coefficient is dependent on urolith density, and that density can be independent of urolith composition. The physical density of a urolith may vary sufficiently such that it obscures differences in the densities of various composing minerals. Theoretically, the DECT ratio should be unaffected by urolith density because the numerator and denominator are equally affected by the density. However, a urolith composed of a high-density material may cause greater beam hardening during the low-energy scan than during the high-energy scan, which could result in the density having an unequal effect on the numerator and denominator of the DECT ratio.
Another consideration is many uroliths are not composed of just 1 material (ie, do not have a pure composition). Urolith composition is generally deternined by use of polarized light microscopy, infrared spectroscopy, and x-ray diffraction techniques, all of which destroy and test only a portion of the urolith. For uroliths that have distinct layers, all layers are generally evaluated. However, for uroliths that do not have visibly evident layering, generally only 1 representative portion of the urolith is evaluated. Partial sampling may result in a urolith being reported as having a pure composition even though up to 5% to 10% of it may be composed of another material.20 The error associated with the inability of currently accepted gold-standard methods to accurately and completely determine urolith composition may have contributed to the inability of DECT to distinguish common types of canine uroliths in the present study and should be considered a limitation in similar studies.
The primary purpose for identifying an in vivo test that can accurately determine urolith composition is to facilitate the prediction of whether a urolith can be successfully fragmented with shock wave lithotripsy and guide treatment decisions. Numerous studies7–9,25,30–35 have been performed that describe shock wave lithotripsy and urolith fragility. Uric acid uroliths are soft and easily fragmented with shock wave lithotripsy, compared with brushite and cystine uroliths, which are harder and often resistant to ESWL.7–9 Struvite, uric acid, and calcium oxalate dihydrate uroliths tend to fragment into small pieces, whereas calcium oxalate monohydrate uroliths tend to fragment into large pieces that are less likely to be voided.32 However, the coefficient of variability for fragility can vary by up to 60% among uroliths with a specific chemical composition, particularly calcium oxalate monohydrate uroliths.8 The reason for that variability is poorly understood but may be related to variations in minor chemical elements or the presence of a central core with a different composition.31 Among calcium oxalate monohydrate uroliths, the magnesium, manganese, and zinc concentrations for uroliths that were successfully fragmented with ESWL were significantly lower than those for uroliths that were refractory to ESWL.32 Interestingly, calcium monohydrate uroliths of dogs are more fragile than those of cats, despite having the same chemical composition.33 This may be caused by the presence of varying amounts of organic material or a mix of minerals.8 It has been suggested that a classification scheme that is independent of composition and based solely on the mineral content of uroliths might be a more clinically relevant system than that currently used for predicting which uroliths will and will not respond to ESWL.34 In 1 study,25 CT attenuation was negatively associated with urolith fragility and the likelihood of fragmentation by ESWL, regardless of urolith composition, which indicates fragility is independent of composition. Although urolith composition is important for treatment planning, the site, size, and number of uroliths present in addition to the patient's history regarding urolithiasis, hydronephrosis, renal colic, and ureteral stents also affect the probability of successful treatment with ESWL.30,35
In the present study, no single DECT measurement was able to differentiate among canine uroliths composed of struvite, calcium oxalate, cystine, urate, and brushite in an in vitro phantom model; therefore, DECT is unlikely to be clinically useful for determining urolith composition in vivo. However, given that the primary reason for determining urolith composition in vivo is to predict response to shock wave lithotripsy, future research should focus on the correlation between DECT measurements and urolith fragility rather than urolith composition.
Acknowledgments
This manuscript represents a portion of a thesis submitted by Dr. Nykamp to the Western University Department of Medical Biophysics as partial fulfillment of the requirements for a Master of Science degree.
Presented as a poster at the American College of Veterinary Radiology Annual Scientific Conference, Orlando, Fla, October 2016.
The authors thank the Canadian Urolith Centre, Guelph, ON for the stone samples.
ABBREVIATIONS
| DECT | Dual-energy CT |
| ESWL | Extracorporeal shock wave lithotripsy |
| HU | Hounsfield units |
| ROI | Region of interest |
Footnotes
Discovery CT750, GE Healthcare, Waukesha, Wis.
SAS, version 9.4, SAS Institute Inc, Cary, NC.
References
1. Houston DM, Moore AE. Canine and feline urolithiasis: examination of over 50,000 urolith submissions to the Canadian Veterinary Urolith Centre from 1998 to 2008. Can Vet J 2009; 50: 1263–1268.
2. Low WW, Uhl JM, Kass PH, et al. Evaluation of trends in urolith composition and characteristics of dogs with urolithiasis: 25,499 cases (1985–2006). J Am Vet Med Assoc 2010; 236: 193–200.
3. Westropp JL, Buffington CAT. Lower Urinary Tract Disorders in Cats. In: Ettinger S, Feldman E, eds. Textbook of veterinary internal medicine. 7th ed. Philadelphia: Elsevier Saunders, 2009; 2080–2086.
4. Ng CS, Fuchs GJ, Streem SB. Extracorporeal shockwave lithotripsy. In: Stoller ML, Meng MV, eds. Urinary stone disease: the practical guide to medical and surgical management. Towata, NJ: Humana Press, 2007; 555–569.
5. Logarakis NF, Jewett MA, Luymes J, et al. Variation in clinical outcome following shock wave lithotripsy. J Urol 2000; 163: 721–725.
6. Ehreth JT, Drach GW, Arnett ML, et al. Extracorporeal shock wave lithotripsy: multicenter study of kidney and upper ureter versus middle and lower ureter treatments. J Urol 1994; 152: 1379–1385.
7. Evan AP, Coe FL, Lingeman JE, et al. Insights on the pathology of kidney stone formation. Urol Res 2005; 33: 383–389.
8. Williams JC Jr, Saw KC, Paterson RF, et al. Variability of renal stone fragility in shock wave lithotripsy. Urology 2003; 61: 1092–1096.
9. Ansari MS, Gupta NP, Seth A, et al. Stone fragility: its therapeutic implications in shock wave lithotripsy of upper urinary tract stones. Int Urol Nephrol 2003; 35: 387–392.
10. Richard S, Siewerdsen JH, Jaffray DA, et al. Generalized DQE analysis of radiographic and dual-energy imaging using flat-panel detectors. Med Phys 2005; 32: 1397–1413.
11. Brody WR, Butt G, Hall A, et al. A method for selective tissue and bone visualization using dual energy scanned projection radiography. Med Phys 1981; 8: 353–357.
12. Coursey CA, Nelson RC, Boll DT, et al. Dual-energy multidetector CT: how does it work, what can it tell us, and when can we use it in abdominopelvic imaging? Radiographics 2010; 30: 1037–1055.
13. Mostafavi MR, Ernst RD, Saltzman B. Accurate determination of chemical composition of urinary calculi by spiral computerized tomography. J Urol 1998; 159: 673–675.
14. Mitcheson HD, Zamenhof RG, Bankoff MS, et al. Determination of the chemical composition of urinary calculi by computerized tomography. J Urol 1983; 130: 814–819.
15. Hillman BJ, Drach GW, Tracey P, et al. Computed tomographic analysis of renal calculi. AJR Am J Roentgenol 1984; 142: 549–552.
16. Demirel A, Suma S. The efficacy of non-contrast helical computed tomography in the prediction of urinary stone composition in vivo. J Int Med Res 2003; 31: 1–5.
17. Hidas G, Eliahou R, Duvdevani M, et al. Determination of renal stone composition with dual-energy CT: in vivo analysis and comparison with x-ray diffraction. Radiology 2010; 257: 394–401.
18. Thomas C, Heuschmid M, Schilling D, et al. Urinary calculi composed of uric acid, cystine, and mineral salts: differentiation with dual-energy CT at a radiation dose comparable to that of intravenous pyelography. Radiology 2010; 257: 402–409.
19. Graser A, Johnson TR, Bader M, et al. Dual energy CT characterization of urinary calculi: initial in vitro and clinical experience. Invest Radiol 2008; 43: 112–119.
20. Primak AN, Fletcher JG, Vrtiska TJ, et al. Noninvasive differentiation of uric acid versus non-uric acid kidney stones using dual-energy CT. Acad Radiol 2007; 14: 1441–1447.
21. Boll DT, Patil NA, Paulson EK, et al. Renal stone assessment with dual-energy multidetector CT and advanced postprocessing techniques: improved characterization of renal stone composition—pilot study. Radiology 2009; 250: 813–820.
22. Qu M, Jaramillo-Alvarez G, Ramirez-Giraldo JC, et al. Urinary stone differentiation in patients with large body size using dual-energy dual-source computed tomography. Eur Radiol 2013; 23: 1408–1414.
23. Wang J, Qu M, Duan X, et al. Characterisation of urinary stones in the presence of iodinated contrast medium using dual-energy CT: a phantom study. Eur Radiol 2012; 22: 2589–2596.
24. Qu M, Ramirez-Giraldo JC, Leng S, et al. Dual-energy dual-source CT with additional spectral filtration can improve the differentiation of non-uric acid renal stones: an ex vivo phantom study. AJR Am J Roentgenol 2011; 196: 1279–1287.
25. Joseph P, Mandal AK, Singh SK, et al. Computerized tomography attenuation value of renal calculus: can it predict successful fragmentation of the calculus by extracorporeal shock wave lithotripsy? A preliminary study. J Urol 2002; 167: 1968–1971.
26. Thomas C, Patschan O, Ketelsen D, et al. Dual-energy CT for the characterization of urinary calculi: in vitro and in vivo evaluation of a low-dose scanning protocol. Eur Radiol 2009; 19: 1553–1559.
27. Motley G, Dalrymple N, Keesling C, et al. Hounsfield unit density in the determination of urinary stone composition. Urology 2001; 58: 170–173.
28. Zarse CA, Hameed TA, Jackson ME, et al. CT visible internal stone structure, but not Hounsfield unit value, of calcium oxalate monohydrate (COM) calculi predicts lithotripsy fragility in vitro. Urol Res 2007; 35: 201–206.
29. Saw KC, McAteer JA, Monga AG, et al. Helical CT of urinary calculi: effect of stone composition, stone size, and scan collimation. AJR Am J Roentgenol 2000; 175: 329–332.
30. Gupta NP, Ansari MS, Kesarvani P, et al. Role of computed tomography with no contrast medium enhancement in predicting the outcome of extracorporeal shock wave lithotripsy for urinary calculi. BJU Int 2005; 95: 1285–1288.
31. Kijvikai K, de la Rosette JJ. Assessment of stone composition in the management of urinary stones. Nat Rev Urol 2011; 8: 81–85.
32. Turgut M, Unal I, Berber A, et al. The concentration of Zn, Mg and Mn in calcium oxalate monohydrate stones appears to interfere with their fragility in ESWL therapy. Urol Res 2008; 36: 31–38.
33. Adams LG, Williams JC Jr, McAteer JA, et al. In vitro evaluation of canine and feline calcium oxalate urolith fragility via shock wave lithotripsy. Am J Vet Res 2005; 66: 1651–1654.
34. Mandhani A, Raghavendran M, Srivastava A, et al. Prediction of fragility of urinary calculi by dual x-ray absorptiometry. J Urol 2003; 170: 1097–1100.
35. Wang M, Shi Q, Wang X, et al. Prediction of outcome of extracorporeal shock wave lithotripsy in the management of ureteric calculi. Urol Res 2011; 39: 51–57.
