The composition of urinary tract stones determines their hardness. Thus, calcium oxalate monohydrate and cystine stones have low SWL success rate as they are very hard [11]. However, stone components cannot be determined pre-SWL, so SWL cannot be avoided in such hard stones with unfavorable outcome. Only the HU value in CT can give an idea about the fragility of the stone. Low SWL success is linked to high HU [3, 12].

Unfortunately, CT imaging is associated with high cost and radiation exposure. Thus, studies are carried out to determine alternative parameters that can predict SWL outcome. Kraev et al. were the first to report the possibility of the use of SWE in determining the fragility of renal stones [9]. Then, Demir et al. documented the usability of SWE in the prediction of SWL success in their pilot study [10].

Concerning BMI, we concluded that it was a predictor of SWL success on univariate analysis but not independent predictor on multivariate analysis. The predictive value of BMI is debatable. Pareek et al., and El-Nahas et al., found it to be an independent variable of success [13, 14], while Ng et al., and Abdelhamid et al., did not [1, 15].

In terms of stone density (HU), we found a statistically significant difference between responders and non-responders with a cutoff value of > 894. Similarly, Perks et al. detected that stones < 900 HU were 6.2 times more likely to be treated successfully with SWL than were stones ≥ 900 HU [16], El-Assmy et al., reported that the HU cutoff value was > 1000 to determine SWL success [17]. Also, Hameed et al., stated that SWL outcome decreased in stones of HU > 1350 [18]. However, stone attenuation was not found to be an independent variable of SWL success by Wiesenthat et al. and Celik et al. on multivariate analysis [19, 20].

In our study, we found that lower calyceal location was an independent predictor of multivariate analysis of SWL success. It was seen in 25 (18.8%) subjects of the responders and 27 (51.9%) subjects of the non-responders (p = 0.001). In contrast, Abdelhamid et al., found lower calyceal location as a non-predictor variable [1].

In the present study, SSD was higher in the non-responders than responders (p < 0.001) with a cutoff value of > 111.5 mm. In agreement with this, Elawady et al., reported the cutoff value of SSD that predicted SWL success was 86 mm [21]. Also, Waqas et al. found that 100 mm was the suitable threshold value for SSD beyond which stone disintegration decreased [22]. Park et al. concluded that SSD was the only important factor for the prediction of SWL outcome and they explained that by the expected loss of shock waves energy on passing through the increased body fat percent with higher SSD [23]. While Geng et al., and Ng et al., did not find SSD as an independent variable of SWL success in their studies [15, 24].

Regarding SWE, we found that the mean SWE value was 11.74 ± 3.86 kPa in the responders, while it was 17.51 ± 3.07 kPa in the non-responders. This difference was highly statistically significant (p < 0.001), and the best cutoff value of SWE was ≥ 15.5 kPa to determine SWL success. Similarly, Demir et al., stated that the difference in SWE values between patients with successful SWL and patients with failed SWL was statistically significant (p < 0.05), They attributed that to the softness of stones with lower SWE [10].

In this study, it is noted that there is a correlation between the measurements of stone density by HU and SWE. This was also demonstrated by Demir et al. [10]. We believe SWE can replace HU in the prediction of SWL outcome. It will be helpful especially in avoiding radiation exposure in pediatric population.

Our study is small-scale as it has been conducted on relatively small number of participants and no chemical stone analysis. We are in need of further studies to validate our results. However, this study defined the role of SWE in the prediction SWL success for renal stones. Besides, it established the correlation between the measurement of stone density by SWE and HU.