pISSN 1598-298X / eISSN 2384-0749 J Vet Clin 34(3) : 178-184 (2017)
http://dx.doi.org/10.17555/jvc.2017.06.34.3.178
178
In vitro Estimation of The Hounsfield Units and
The Volume and Void of Canine Struvite Stones as Predictors of Fragility in Extracorporeal Shock Wave Lithotripsy
Ji-hwan Wang, Tae-sung Hwang, Dong-in Jung, Seong-chan Yeon and Hee-chun Lee1
Institute of Animal Medicine, College of Veterinary Medicine, Gyeongsang National University, Jinju 52828, Korea (Received: March 14, 2017 / Accepted: June 11, 2017)
Abstract : The aim of this study was to determine whether Hounsfield units (HUs), volume, and various void parameters can predict stone fragility in extracorporeal shock wave lithotripsy (ESWL). HU, volume, porosity, number of voids/
stone volume, and void distribution of 30 struvite stones were estimated using helical computed tomography (CT) and micro-CT. The number of shock waves necessary for full fragmentation was accepted as a measure of the stone fragility in ESWL. The correlations between the number of shock waves and the HU, volume, porosity, and number of voids/stone volume were examined. The number of shock waves of the two groups according to the void distribution was also compared. Stone volume correlated with the number of shock waves. Shell-patterned struvite stones were significantly less susceptible to fragmentation in ESWL than non-shell-patterned struvite stones. Stone volume and void distribution may be predictors of the outcome of ESWL treatment.
Key words : extracorporeal shock wave lithotripsy, tomography, struvite, volume, void.
Introduction
In vitro studies and clinical experience with extracorporeal shock wave lithotripsy (ESWL) in human medicine have revealed that the outcome of the treatment of urinary stones is closely related to the composition and size of the stones (4,25). Several studies have indicated that stones composed of cystine, brushite, and calcium oxalate monohydrate are less susceptible to ESWL than those composed of calcium oxalate dihydrate, hydroxyapatite, struvite, and uric acid (19,21,25,26).
However, the ESWL susceptibility of urinary stones with iden- tical composition varies markedly depending on their fragil- ity (6,7,25,26,29,30). This indicates that the internal structure of the stones partially determine their fragility to ESWL.
Several human medical studies have applied this concept and have proposed that the stone composition and structure related to fragility be identified using helical computed tomog- raphy (CT) (4,10,24,26,31). Although the determination of the stone composition using helical CT was limited in previous studies (4,12,13), Hounsfield units (HU) of helical CT have been used to predict the success or failure of ESWL (4,5,10, 17,22,23). The stone volume measurement in helical CT was also proposed as a predictor of the effectiveness of urinary stone treatment with ESWL (2,28), but it was not estimated in previous in vitro studies. Numerous studies on the internal structure of urinary stones using helical CT or micro-CT focused on the void regions occupied by radio-lucent regions (6,7,19,27,29). Although the quality of helical CT continues to improve, it is impossible to quantify void areas using heli-
cal CT because of limited resolving power, so the internal structure of the stones is currently subjectively estimated (29).
In addition, void estimation using micro-CT has assessed only the volume of the internal void (7,19,27). The conduct of various void estimations, including of the void volume, number, and distribution, is expected to be useful for the study of urinary stones in human and veterinary medicine.
This study was conducted to test if HU and volume estima- tion using helical CT and estimation of various void param- eters using micro-CT could be applied to struvite stones, which are among the most common of canine urinary stones (8), as predictors of fragility via ESWL.
Materials and Methods
Stone sampling
Fifty-four urinary stones (10-15 mm in diameter) extracted surgically without fragmentation were collected for this study.
The individual stones were obtained from different individ- ual patients. Of these stones, 30 struvite stones that were determined to have had major compositions with a X-ray microdiffraction instrument (D8 DISCOVER with GADDS;
Bruker AXS K.K.; Bruker, Karlsruhe, Germany) were used.
The instrument was equipped with a two-dimensional detector (HI-STAR; Bruker) and a 500μm monocapillary lens. The detection parameters of the instrument were Cu Kα radiation operating at 40 kV and 40 mA, scanning angle 10-90o, step size 0.05o, and scan step time 40s.
Helical CT and data analysis
The stones were placed in a rectangular polypropylene container that had been partially filled with gelatin. The con-
1Corresponding author.
E-mail: lhc@gnu.ac.kr
tainer was 8.7 cm tall with a 12.0× 12.0 cm square base.
Dissolved gelatin was carefully poured into the container to a height of 3 cm to minimize air bubble formation, and was left to cool for approximately 30 minutes at 4oC. Then, the stones were arranged in arrays on the gelatin (which was still not completely firm) at 4oC overnight until completely set, after which they were covered with 0.9% saline (Fig 1). The submerged stones were left undisturbed for approximately 12 hours before they were scanned to allow trapped air bubbles on the their surface to dissipate.
The stones were examined by helical CT using a Soma- tom Emotion apparatus (Siemens Medical System, Erlangen, Germany). The CT parameters were 1 mm collimation, 110 kVp, 80 mA, 0.75 pitch, and 0.8-second rotation time. The soft tissue window setting was used to measure the stones’
HUs and volumes. The CT images were estimated at a Lucion offline workstation (Infinitt Technology, Seoul, Korea), and the stone volume was measured from three-dimensional (3- D) images. A representative CT image that showed the larg- est diameter of each stone was chosen to determine the stone HU. The stone HU was measured from the 3-4 mm2 circular region of interest (ROI) in the cross-sectional area and the ROI was moved to avoid measurement of the same region.
The mean HU was calculated for each stone from the three measurements.
Micro-CT and data analyses
The hardware device used in this study was a model 1076 desktop X-ray microfocus CT scanner (SkyScan, Kontich, Bel- gium). The scanning procedure was completed for all the stones using a 59 kV voltage, a 167μA current and a 160 ms exposure time. The transmission X-ray images were recorded at 0.6o rotational steps for 360o of rotation. Two frames were averaged at each rotation step. The resulting two-dimen- sional (2-D) shadow/transmission images (16-bit TIFF) were used to reconstruct the axial cross-sections. Then, each raw data set was reconstructed into images using the SkyScan
cluster reconstruction software (NRecon, Version 1.6.1.5). The average pixel size was 18.1μm.
The images were analyzed to calculate the porosity in % [(void volume ÷ total volume of the stone) × 100], number of voids ÷ total volume of the stone, and the distribution of the voids. Two models for the imaging analysis, porosity and number of voids ÷ total volume of the stones, were created in MATLAB 7 (MathWorks, Natick, USA) using internally devel- oped algorithms. The micro-CT images were imported, the material pixels were separated from the void pixels based on their grey values, and the binary images were obtained in which the 0’s represented voids and the 1’s represented the materials. To decrease the influence of the threshold selection on the results, the optimal threshold for the segmentation was chosen. An automated threshold method was used instead of the manual threshold method because there was no means of precisely measuring the volume of the void or the protein contents of the stones (19,27). Although there are different approaches to automated image segmentation, including Otsu’s method (16) and kriging techniques (14), the threshold value was chosen in this study using the IsoData algorithm (20).
The porosity analysis was modified from the method of Pramanik et al (19). Briefly, the micro-CT images were con- verted into binary images, and then white regions including voids and a background were determined for the ranking in the order of the largest to the smallest area in each slice. The total stone area in each slice was calculated from the differ- ence between the total slice area and the largest area in the white region, as the largest area of the white regions was Fig 1. Array of the urinary stones used for computed tomography.
Fig 2. Example of the criteria of the shell patterned stone in this study; A, B Transverse micro-CT image slice and corresponding binary image. C, D Sagittal micro-CT image slice and corre- sponding binary image. E, F Coronal micro-CT image slice and corresponding binary image. All of the three orthogonal planes show that all of the voids exist not near the stone surface but the core region.
180 Ji-hwan Wang, Tae-sung Hwang, Dong-in Jung, Seong-chan Yeon and Hee-chun Lee
always a background in each slice. The total stone areas were summed up in all the slices to determine the total stone vol- ume. The total void area in each slice was calculated from the difference between the total area and the largest area of the white regions, and the total void areas were also summed up in all the slices to determine the total void volume. A 3-D image stack was reconstructed using an image stack of the extracted voids. Matlab using an internally developed algo- rithm enabled counting of the number of 3-D objects in a stack. Thus, the total number of voids in the 3-D image stacks was determined.
An offline image analysis system was used for the void distribution (ImageJ, US National Institutes of Health; http://
www.rsb.info.nih.gov/ij/). The micro-CT images of each stone were reconstructed into three orthogonal planes using the DataViewer software (SkyScan). The micro-CT images that showed the largest diameter in each plane of each stone were selected to estimate the void distribution. The selected images were converted into binary images using ImageJ. The stones were classified into those with a shell pattern and those with a non-shell pattern according to the void distribution. In the shell pattern, many voids appeared in the core region, but no or few voids were near the surface of the stone (Fig 2). Of the three orthogonal planes, if any plane did not agree with the criteria, the stones there were classified as having had a non-shell pattern (Fig 3).
ESWL
This study was conducted using the PCK Stonelith (PCK
Electronic Industry and Trade, Ankara, Turkey) spark gap shock wave generator lithotripter. The lithotripter was operated at an output voltage of 20 kV with a 1Hz pulse repetition rate.
Before the ESWL, all the stones were hydrated for 72 hours in 0.9% saline. The individual stones were then placed in an especially constructed experimental apparatus that con- sisted of a net with a pore size of 2 mm to support the stones and a plastic container that had one silicone rubber wall to allow passage of the shock waves. The plastic container was filled with water so that the stones would be completely sub- merged. The next step in the process was the inflation of the diaphragm of the lithotripter and the coupling of the silicone rubber wall of the plastic container to the ultrasound gel- smeared diaphragm of the lithotripter. An example of an in vitro ESWL set-up is shown in Fig 4. In veterinary medi- cine, successful fragmentation was defined as either stone-free or residual stone fragments < 2 mm in diameter (1). Thus, shock waves were applied until all the fragments had passed through the 2 mm net or until 3,000 shock waves had been delivered, and the number of shock waves was counted.
Statistical analysis
Data analysis was performed using a commercially avail- able software package (SPSS 14.0, SPSS Inc.). The linear regression of the independent and dependent variables was sta- tistically analyzed. The differences between the two patterns were assessed with an independent t test. P values < 0.05 were considered statistically significant.
Results
The number of shock waves required for successful frag- mentation and the stone volume were linearly related (P <
0.05 and r = 0.428) (Fig 5A). The CT-assessed HU and the fragmentation had no statistically significant correlation (P = 0.177 and r = 0.253) (Fig 5B). No relationship was observed between the number of shock waves required for successful fragmentation and other parameters such as the porosity and the void number/the stone volume (P = 0.926, r = 0.018, P = 0.868, and r = 0.32, respectively) (Figs. 5C, 5D).
It was decided that 12 struvite stones (40%) would have a shell pattern according to the void distribution. The mean Fig 3. Example of the criteria of the non-shell patterned stone in
this study; A, B Transverse micro-CT image slice and corre- sponding binary image. C, D Sagittal micro-CT image slice and corresponding binary image. E, F Coronal micro-CT image slice and corresponding binary image. Many voids near the stone sur- face were clearly observed, particularly in the sagittal micro-CT slice image, compared to Fig 2.
Fig 4. Experimental set-up used for predicting fragility of the in vitro stones.
diameters of the shell-patterned and non-shell-patterned stones did not differ (1.22 ± 0.22 and 1.19 ± 0.23 mm, respectively).
Table 1 shows the comparison of the number of shock waves between the two groups. The shell-patterned struvite stones were significantly less susceptible to fragmentation via ESWL than the non-shell-patterned struvite stones (Fig 6). The mean number of shock waves in the shell-patterned and non-shell- patterned stones were 1,992 ± 962 and 1,003 ± 1,028, respec- tively (P < 0.05).
Discussion
Generally, the size of urinary stones is evaluated consider- ing the maximal axial diameter (2,3). The evaluation of the size of urinary stones using the diameter of the longest axis on the 2-D plane cannot correctly reflect stone volume because of the irregular and complex shape. One study measured stone size by abdominal radiography and compared the find- ings with actual stone size (16). They demonstrated that cor- rect measurement occurred in only 26% of cases. In addition,
20% of the abdominal radiographs overestimated size by more than 25%, and the size of stones was overestimated by
< 25% in another 39% of cases.
In contrast, other reported that size determination by heli- cal CT was considerably more accurate than plain radiogra- phy (15). The CT margin of error did not exceed 3.6% of actual size. Because of this, for the size of the urinary stone, the volume of the stone instead of the longest diameter was measured. In fact, even when the longest diameters were identical, the volume of the stone differed, and some stones with the same diameter differed in volume by three times or Fig 5. Correlation between (A) volume and the number of shock waves, (B) HU and the number of shock waves, (C) porosity and the number of shock waves, (D) number of voids/ stone volume and the number of shock waves. The number of shock waves showed correlation with volume only (R = 0.428, p < 0.02).
Table 1. Number of the non-shell-patterned and shell-patterned stones according to the number of shock waves
No. of shock waves No. (%) of non-shell-pattern
No. (%) of shell-pattern
0-1000 13 (72.2) 1 (8.3)
1001-2000 2 (11.1) 4 (33.3)
2001-3000 3 (16.7) 7 (58.4)
Totals 18 12
Fig 6. Comparison of the number of shock waves showing sta- tistically significant difference in both groups according to the void distribution.
182 Ji-hwan Wang, Tae-sung Hwang, Dong-in Jung, Seong-chan Yeon and Hee-chun Lee
more.
Some studies reported that the volume of stones was sig- nificantly greater in the ESWL treatment success group than in the ESWL treatment failure group, and that stone volume was a more meaningful predictor of the outcome of the ESWL treatment than the diameter of the stone (2,28). Although the volume of the stone was not measured using CT-based 3-D reconstruction, one reported on the correlation between the number of shock waves and the volume of urinary stones (22). In this study, stone volume was measured on 3-D images.
Recent studies have tried to predict the effect of ESWL treatment by measuring the HU of the stone using non- enhanced computed tomography (NECT). One of them mea- sured HU of urinary stone obtained from percutaneous neph- rolithotomy using NECT, put the stone in a container filled with artificial urine, and performed ESWL for the stone (22).
The authors reported that stones with higher HU required more shock waves to break down the stone. The results indi- cated that the HU of a stone can predict the outcome of the ESWL treatment. The authors were the first to present the possibility that NECT can be used as an important tool for diagnosing urinary stones and for selecting the treatment method for the stone. Since then, many studies reported the clinical usefulness of the HU of a urinary stone as a predic- tor of the outcome of ESWL treatment based on the compar- ison of the HU of the stone and the outcome of the ESWL treatment in patients with urinary stones (5,17,18,23,28). In contrast, One study performed an experiment using urinary stones normalized to stone size and reported that there was no correlation between the number of shock waves and the HUs of the urinary stones (29).
This study showed that there was no correlation between the HU of the urinary stone that was measured with NECT and the number of shock waves. This result is consistent with previously reported study (29), but is considered contrary to that of other studies (4,5,10,17,22,23) because in this study, urinary stones normalized to stone size were used and the stones were imaged with CT using high-resolution beam col- limation (1 mm).
One study reported that the number of shock waves and the HU of the urinary stone were correlated according to a CT image taken using 3 mm collimation, and that they were not correlated according to the CT image taken using 1 mm collimation because the narrower the width of the collimation, the higher was the HU due to the volume averaging effect (22). The smaller the size of the urinary stone is, the greater the HU error is (26). Thus, the positive correlation between the HU of the urinary stone and the number of shock waves on the images taken using low-resolution beam collimation (e.g., 3 mm collimation) is deemed to have been due to the size of the urinary stone rather than to the true HU (22,26).
Even if the compositions of urinary stones are identical, the outcomes of their ESWL treatment may differ depending on their fragility (6,7,25,26,29,30). One study compared the void volumes and the protein contents of a human apatite uri- nary stone and a human brushite urinary stone that had simi- lar chemical compositions but different clinical responses to ESWL treatment, and found that the protein content and void volume of the apatite urinary stone were significantly higher
than those of the brushite urinary stone (19). One study using micro-CT images measured and compared the void volume of a rough cystine urinary stone and a smooth cystine urinary stone that had different responses to ESWL treatment, and reported that the void volume of the rough cystine urinary stone that had a good response to ESWL treatment was signif- icantly higher than that of the smooth cystine urinary stone (7).
One study classified cystine urinary stones into a group that had a void and a group that had no void, based on the helical CT evaluation, performed in vitro ESWL, and com- pared the numbers of shock waves needed to break down the stones in the two groups (7). Similar study performed using calcium oxalate monohydrate (29). In both studies, the mean number of shock waves that broke the stones was signifi- cantly lower in the group that had an internal structure or void than in the group that had no internal structure or void.
In this study, however, the porosity and the number of shock waves required to break down the stones were not corre- lated, though the statistical methods differed from those of the previous studies (6,29). Likewise, the number of shock waves and the void number/the stone volume were not corre- lated, which had never been reported in previous studies. In this study, the voids tended to get more as the size of the stone gets larger. Therefore, the average of the void number in mm3 was obtained to minimize the error.
The number of shock waves required to break down the stones was significantly higher for the shell-patterned urinary stones than for the non-shell-patterned urinary stones (P <
0.05). Three of the non-shell-patterned urinary stones required 2,001-3,000 shock waves, but they were not completely bro- ken down, even using 3,000 shock waves.
One of the three stones had X-ray opaque regions inside, and was subjected to ESWL. After 3,000 shock waves, the remaining fragments were analyzed and found to have been calcium oxalate monohydrates, which have been reported to be resistant to ESWL (21,26). The other two stones were struvite stones with various sizes, which were surrounded by and fixed with X-ray lucent materials, as described by Pra- manik et al (19). The reason for the resistance of these types of stones to ESWL shock waves is unclear, but the X-ray lucent materials might have played the role of a buffer to the shock waves. It is known that during ESWL treatment, a uri- nary stone is broken down by stress waves and cavitation (9,32). Particularly, cavitation erosion is caused by bubble collapse and damages mostly the exterior surface of the stone (32). The X-ray lucent materials that surround the stone inter- rupt the cavitation erosion. Excluding these three atypical stru- vite urinary stones, the mean number of shock waves of non- shell-patterned stones considerably decreases from 1,003 ± 1,028 to 604 ± 509.
Even if the void volumes are identical, the distribution of voids may differ and, thus, the mechanical properties may also differ (11). Thus, the porosity and the distribution of voids should be considered. This study showed that the distribu- tion of voids of urinary stones is a more important parameter than the porosity in predicting fragility. However, this study failed to show the distribution of voids numerically. In addi- tion, no clear criteria for the acceptable number of voids near the stone surface have been established for shell-patterned
urinary stones. In this study, three or less dot-shaped voids and two or less very small voids among the voids with irreg- ular shapes were included in the shell-patterned urinary stones. Further studies on these limitations are required.
Conclusion
The volume of canine struvite urinary stones measured on 3-D images that were reconstructed from helical CT images was a significant predictor of the outcome of ESWL treat- ment. Although further studies are required, this study shows that the distribution of voids in a canine struvite urinary stone could also be used as a predictor of the outcome of ESWL treatment. Further in vivo studies based on the results of this study will be very helpful in predicting the success or failure of ESWL treatment, the prevention of complications, and the selection of treatment modalities in clinical practice.
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