Variation coefficient of stone density – can it crack the stone?

Abstract

Extracorporeal shock wave lithotripsy (ESWL) is recognised as the ideal non-invasive procedure for urolithiasis. However, the suitability of ESWL varies depending on the composition of the stone. The chemical structure of the stone may not be uniform throughout the stone and this heterogeneity provides the clue in the form of variation coefficient of stone density. To be aware of the success of the stone breakage by ESWL is an advantage upfront, so that it is possible to apply the technology to the most appropriate patient. This is an important aspect in the successful management of urolithiasis.

Key Words: Urolithiasis; Variation coefficient; Stone density; Lithotripsy; Renal stones

Core Tip: Extracorporeal shock wave lithotripsy is a popular technology for management of urolithiasis. Available factors for predicting the successful outcome of the procedure are many but not reliable. The objective is to explore the utility of variation coefficient of stone density as a parameter in effective lithotripsy.

INTRODUCTION

The European Association of Urology has recognised extracorporeal shock wave lithotripsy (ESWL) as the treatment of choice for renal stones less than 20 mm. As the procedure is on an out-patient basis, less invasive and safe, ESWL enjoys widespread popularity. It is of note that the procedural stone clearance rate is low. In comparison to the percutaneous and endoscopic procedures available for management of urolithiasis, ESWL ranks much lower due to its variable range of stone clearance rate. This suboptimal outcome of ESWL may involve additional sittings for effective clearance of stones. This is a cause for concern, which requires assessment with a view to address the implicating factors[1].

Studies have proposed stone characteristics such as mean stone density, maximum stone density, and standard deviation of stone density as factors forecasting the likelihood of good outcomes of ESWL. Certain aspects of the stone, such as disparity in the composition, intrinsic morphological texture and density at various places of the stone, constitute the stone heterogeneity, which has a bearing on the ability of the stone breakability. Literature has provided ample material regarding the stone heterogeneity, but the outcome predictability still appears elusive based on the information from several previous parameters[2,3].

In ESWL, the generated shock beam targeting the stone has to pass through several layers of the abdominal wall. The tissues at the subcutaneous level and the muscle and renal parenchyma offer changing resistance to the traversing beam. In addition, the stone has variable architecture and heterogeneity, which can alter the pulverising effectiveness of the beam velocity. Hence, the stone density alone might fail to predict the ESWL success. The unreliability of mean stone density and standard deviation of stone density in isolation is known from the studies. In order to overcome this unreliability, a computation combining both, namely the variation coefficient of stone density (VCSD), is proposed. VCSD is a recently introduced parameter which can be deduced from non-contrast computed tomography. Introduced as an innovative parameter, VCSD has been noted as an important predictor of lithotripsy outcome[4].

The standard deviation of stone density qualifies the deviation of density from the mean. Instances of analogous standard deviation but dissimilar stone composition are common. Hence, VCSD, as a parameter combining both, is expected to compute the heterogeneity better. VCSD comes close to estimating the stone fragility better and is superior to others in the correct prediction of ESWL outcome. A recent study established the significance of VCSD as an independent factor by multivariate analysis[5].

Although several parameters are available to evaluate and manage urolithiasis, VCSD ranks higher, as evidenced in the literature[3,4]. Future management protocols are expected to integrate VCSD in the algorithms based on the newer machine learning tools[6]. The role of VCSD in the ESWL outcome is well documented by Iqbal et al[7].

CONCLUSION

VCSD, by incorporation into unique scoring systems, can guide the selection of patients for ESWL and provide optimal outcomes in the appropriate management of urolithiasis. Artificial intelligence can further extend the use of VCSD to the next level.