Slots C. et al., 2026: Stone metrics: is stone volume the new king ?

Slots C, Boeykens M, Pauwaert K, Tailly T.
Curr Opin Urol. 2026 Mar 6. doi: 10.1097/MOU.0000000000001376

Abstract

Purpose of review: Stone volume represents the most accurate measure of urolithiasis burden. While this may be obvious to all, this stone metric has not yet found its way into standard clinical practice or guidelines algorithms guiding treatment strategies. Although linear measurements have their obvious limitations, they are still most commonly used in practice and reported in literature as well as guidelines. This review evaluates the current available evidence supporting stone volume as the most important stone metric.

Recent findings: By now, literature has been able to confidently demonstrate that stone volume is a more accurate predictor of stone free status in shockwave lithotripsy and ureteroscopy. Recent advances in three-dimensional imaging reconstruction, automated segmentation and artificial intelligence have lowered thresholds for obtaining stone volume from computed tomography imaging.

Summary: Today, historical barriers have been overcome, and fast, reproducible stone volume assessment is at our fingertips. And yet, we do not use volume in our daily practice, as we ourselves hold back evolution. While future efforts should be put towards embracing volume as a stone metric, more studies are also needed to identify volume-based thresholds for treatment success aiding in the development of new treatment algorithms.

Comment Hans-Göran Tiselius

It is surprising that despite the considerable period during which low-or non-invasive methods have been used for stone removal, so little attention has been paid to describe the stone burden in a more precise way.

Different methods for imaging most certainly can explain why stone diameters still are used in nomograms, guidelines and result reports. Sometimes authors have used the even worse alternative sum of diameters for multiple stones.

This method for size description has remained despite modern imaging procedures such as NCCT that enable approximate conclusions on both stone surface areas and stone volumes. But as the authors emphasize, accurate estimates of stone volumes carried out manually from NCCT images are time consuming procedures.

Now, application of artificial intelligence seems to be the novel and effective method for obtaining estimates of stone volumes. Hopefully, the future will provide more sophisticated measurements of the stone burdens that we remove with non-invasive or endoscopic methods.

Hans-Göran Tiselius