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Objective: To compare the predictive effects of stone size and volume on the efficacy and safety of retrograde intrarenal surgery (RIRS) and to determine the cutoff values of stone volume for prediction of RIRS efficacy and safety. Methods: Patients who underwent RIRS between 2017 and 2021 in six referral centers were retrospectively included in the study. The database of the RIRsearch group, which was formed prospectively, was used for this retrospective analysis. The surgical results and complications of RIRS were evaluated according to stone size and stone volume and compared between these groups. Results: A total of 1128 patients were included. Operation time, intraoperative complication rate, and postoperative complication rate increased significantly as stone size and stone volume increased ( P < .05). Stone size and volume were significant indicators for stone-free rates, but pairwise comparison showed that stone volume was a significantly better predictor of surgical success compared with stone size ( P < .001). Stone size was not sufficient to predict postoperative complications, whereas stone volume predicted these complications with low performance. Conclusions: Stone volume was a better predictor for surgical success than stone size, and it was as reliable as stone size in predicting postoperative complications.

Introduction: To develop a predictive model incorporating stone volume along with other clinical and radiological factors to predict stone-free (SF) status at ureteroscopy (URS)., Material and Methods: Retrospective analysis of patients undergoing URS for kidney stone disease at our institution from 2012 to 2021. SF status was defined as stone fragments < 2 mm at the end of the procedure confirmed endoscopically and no evidence of stone fragments > 2 mm at XR KUB or US KUB at 3 months follow up. We specifically included all non-SF patients to optimise our algorithm for identifying instances with residual stone burden. SF patients were also randomly sampled over the same time period to ensure a more balanced dataset for ML prediction. Stone volumes were measured using preprocedural CT and combined with 19 other clinical and radiological factors. A bagged trees machine learning model with cross-validation was used for this analysis., Results: 330 patients were included (SF: n = 276, not SF: n = 54, mean age 59.5 ± 16.1 years). A fivefold cross validated RUSboosted trees model has an accuracy of 74.5% and AUC of 0.82. The model sensitivity and specificity were 75% and 72.2% respectively. Variable importance analysis identified total stone volume (17.7% of total importance), operation time (14.3%), age (12.9%) and stone composition (10.9%) as important factors in predicting non-SF patients. Single and cumulative stone size which are commonly used in current practice to guide management, only represented 9.4% and 4.7% of total importance, respectively., Conclusion: Machine learning can be used to predict patients that will be SF at the time of URS. Total stone volume appears to be more important than stone size in predicting SF status. Our findings could be used to optimise patient counselling and highlight an increasing role of stone volume to guide endourological practice and future guidelines., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Objective: Current interventional guidelines refer to the cumulative stone diameter to choose the appropriate surgical modality (ureteroscopy [URS], extracorporeal shockwave lithotripsy [ESWL] and percutaneous nephrolithotomy [PCNL]). The stone volume (SV) has been introduced recently, to better estimate the stone burden. This review aimed to summarize the available methods to evaluate the SV and its use in urolithiasis treatment., Material and Methods: A comprehensive review of the literature was performed in December 2022 by searching Embase, Cochrane and Pubmed databases. Articles were considered eligible if they described SV measurement or the stone free rate after different treatment modalities (SWL, URS, PCNL) or spontaneous passage, based on SV measurement. Two reviewers independently assessed the eligibility and the quality of the articles and performed the data extraction., Results: In total, 28 studies were included. All studies used different measurement techniques for stone volume. The automated volume measurement appeared to be more precise than the calculated volume. In vitro studies showed that the automated volume measurement was closer to actual stone volume, with a lower inter-observer variability. Regarding URS, stone volume was found to be more predictive of stone free rates as compared to maximum stone diameter or cumulative diameter for stones >20 mm. This was not the case for PCNL and SWL., Conclusions: Stone volume estimation is feasible, manually or automatically and is likely a better representation of the actual stone burden. While for larger stones treated by retrograde intrarenal surgery, stone volume appears to be a better predictor of SFR, the superiority of stone volume throughout all stone burdens and for all stone treatments, remains to be proven. Automated volume acquisition is more precise and reproducible than calculated volume., (Copyright © 2023 AEU. Published by Elsevier España, S.L.U. All rights reserved.)

Objective : Our study aimed to evaluate the success rate of ESWL and identify relevant treatment-specific factors affecting treatment outcomes, as well as to assess the accuracy of the updated Triple D scoring system and compare it with older systems. Material and Methods : A prospective study of 71 patients who received ESWL treatment for renal stones that were 5-15 mm in size was completed. The patient having no residual stones or residual stones lesser than 4 mm after ESWL was identified as a treatment success. Univariate and multivariate logistic regression and ROC curves were used to identify important factors for treatment outcomes. Results : Successful treatment was achieved for 66.2% of patients. The stone volume (SV), mean stone density (MD), and delivered power to the stone volume unit ratio (SMLI/SV) were defined as the most critical factors influencing ESWL success. An updated Triple D score system with a, SMLI/SV ratio could be an alternative to older systems and reach an even higher accuracy. A limitation of this study is the limited sample size due to the COVID-19 pandemic. Conclusions : Our results show that the three factors that most influence the success of ESWL are the stone size, mean stone density, and SMLI/SV ratio. Based on this, we present a simple updated triple D score system to predict ESWL success, which could be implemented in future clinical practice.

Purpose: To evaluate whether computer program-estimated urolith stone volume (SV) was a better predictor of spontaneous passage (SP) compared with program-estimated stone diameter (PD) or manually measured stone diameter (MD), and whether utilizing SV and MD together provided additional value in SP prediction compared with MD alone. Materials and Methods: Retrospective analysis of patients with acute renal colic and single renal/ureteral stone on CT from July 2017 to April 2020. Diameter obtained from radiology reports or manually measured when report not available. Semiautomated stone analysis software (qSAS) was used to estimate SV and PD. ROC analysis was performed to compare accuracy of SV vs MD vs PD in predicting SP by 2, 4, and 6 weeks. Subgroup analysis was performed by stone size (3 vs 312 mm 3 ; p  < 0.001). ROC analysis showed significantly higher area under curve (AUC) for SV for predicting SP by 4 and 6 weeks compared with MD and PD (AUC 0.93 vs 0.86 vs 0.85 4 weeks, p  < 0.001; 0.92 vs 0.85 vs 0.86 6 weeks, p  < 0.003). AUC difference between SV vs MD was much greater among stones ≥6 mm or proximal stones. Utilizing SV and MD together yielded improved positive predictive value and negative predictive value for SP prediction. Conclusions: SV is a more accurate predictor of SP compared with linear stone dimensions, especially in the setting of larger and/or more proximal stones. Utilizing SV and diameter together yielded improved SP predictions compared with using either metric alone. Prospective studies are indicated to investigate the clinical utility of SV for SP prediction.

Objective: The aim of the investigation was to determine the influence of such parametric characteristics of the stone such as size and volume on the duration of tulium laser disintegration of the urinary stone and to determine which of these parameters is more effective to use like prognostic criterion for the duration of the planned surgical intervention in the percutaneous nephrolithotripsy., Materials and Methods: Overall 52 patients (27 females and 25 males) with an average age of 56,9 (25-79) years participated in the present study. All patients underwent percutaneous nephrolithotripsy with disintegration of the kidney stone by thulium energy. Inclusion criteria were: stone size more or equal 2 cm, stone density >1100 HU. Exclusion criteria were: patients with a single kidney, urinary tract divertions, coagulopathy. The average operation time was 30 (15-100) minutes, with an average puncture time of 3.15 (1-10) minutes and lithotripsy time of 28 (14-98) minutes. To determine the volume we used the method of automatic lithometry according to CT data using the software: Vitrea ver. 4.1.52. The size of the stone was determined by the longest length in one of the plane. During the study it was found that the average size of the stone was 28.25 (20-58) mm and the average volume was 2579.4 (250-9990) mm3. To confirm our assumption, we decided to determine the dependence of the time of disintegration of the stone on the size and volume of the stone. For this purpose, we graphically presented the correlation of these parameters., Results: We have drawn 2 graphs reflecting the dependence of lithotripsy time parameters on the size and volume characteristics of the stone. As a result of comparing these parameters we found that size is a prognostically less reliable predictor of lithotripsy time, and is not characterized by a linear distribution, in contrast to the stone volume., Conclusions: Thereby, the main stereoscopic characteristic of a stone is a volume, which should be the primary guide in selecting the preferred method of treatment as well as in predicting the operative time and associated risks.

Purpose: Shock wave lithotripsy (SWL) is used to treat upper urinary tract stones. Recently, some volume analyzers have enabled preoperative assessment using three-dimensional computed tomography (3D-CT). We evaluated the efficacy of 3D-CT variables for predicting the outcomes of SWL., Methods: The study population included 193 patients who underwent SWL between November 2014 and August 2020. In addition to conventional two-dimensional computed tomography (2D-CT) assessments, 3D-CT assessments of targeted stones were retrospectively performed, and stone size and stone density (SD) were measured. The successful and unsuccessful treatment groups were compared and risk factors for an unsuccessful first SWL session were investigated. The predictive accuracy of variables measured on 3D-CT was evaluated by receiver operating characteristic curves and multivariate analyses., Results: The success rate of the first SWL session was 73.1%. Stone volume, mean SD and highest SD on 3D-CT were significantly higher in the unsuccessful group than in the successful group. Stone volume showed a higher area under the curve (AUC) than the estimated volumetric stone burden and stone diameter, which were measured on 2D-CT (0.729, 0.683, and 0.672, respectively). The AUCs of the mean SD and highest SD on 3D-CT were higher than those on 2D-CT (0.699, 0.680, 0.617, and 0.627, respectively). Multivariate analyses identified stone volume (≥ 0.29 ml), mean SD on 3D-CT (≥ 421 HU), and absence of hydronephrosis as independent predictive factors for unsuccessful SWL., Conclusion: 3D-CT variables were promising predictors of the outcomes of SWL. Preoperative 3D-CT assessment is helpful for selecting favorable patients for SWL., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

This study aimed to evaluate the additional utility of an automated method of estimating volume for stones being treated with shockwave lithotripsy (SWL) using computed tomography (CT) images compared to manual measurement. Utility was assessed as the ability to accurately measure stone burden before and after SWL treatment, and whether stone volume is a better predictor of SWL outcome than stone diameter. 72 patients treated with SWL for a renal stone with available CT scans before and after treatment were included. Stone axes measurement and volume estimation using ellipsoid equations were compared to volume estimation using software using CT textural analysis (CTTA) of stone images. There was strong correlation (r > 0.8) between manual and CTTA estimated stone volume. CTTA measured stone volume showed the highest predictive value (r 2  = 0.217) for successful SWL outcome on binary logistic regression analysis. Three cases that were originally classified as 'stone-free with clinically insignificant residual fragments' based on manual axis measurements actually had a larger stone volume based on CTTA estimation than the smallest fragments remaining for cases with an outcome of 'not stone-free'. This study suggests objective measurement of total stone volume could improve estimation of stone burden before and after treatment. Current definitions of stone-free status based on manual measurements of residual fragment sizes are not accurate and may underestimate remaining stone burden after treatment. Future studies reporting on the efficacy of different stone treatments should consider using objective stone volume measurements based on CT image analysis as an outcome measure of stone-free state.

Objectives: To validate AutoMated UroLithiasis Evaluation Tool (AMULET) software for kidney stone volumetry and compare its performance to standard clinical practice., Materials and Methods: Maximum diameter and volume of 96 urinary stones were measured as reference standard by three independent urologists. The same stones were positioned in an anthropomorphic phantom and CT scans acquired in standard settings. Three independent radiologists blinded to the reference values took manual measurements of the maximum diameter and automatic measurements of maximum diameter and volume. An "expected volume" was calculated based on manual diameter measurements using the formula: [Formula: see text] Results: Ninety-six stones were analyzed in the study. We had initially aimed to assess 100. Nine were replaced during data acquisition due of crumbling and four had to be excluded because the automated measurement did not work. Mean reference maximum diameter was 13.3 mm (5.2-32.1 mm). Correlation coefficients among all measured outcomes were compared. The correlation between the manual and automatic diameter measurements to the reference was 0.98 and 0.91, respectively (p < 0.001). Mean reference volume was 1200 mm 3 (10-9000 mm 3 ). The correlation between the "expected volume" and automatically measured volume to the reference was 0.95 and 0.99, respectively (p < 0.001)., Conclusions: Patients' kidney stone burden is usually assessed according to maximum diameter. However, as most stones are not spherical, this entails a potential bias. Automated stone volumetry is possible and significantly more accurate than diameter-based volumetric calculations. To avoid bias in clinical trials, size should be measured as volume. However, automated diameter measurements are not as accurate as manual measurements.

Objective: The objective of this prospective study is to evaluate the consistency of renal stone volume estimation using dual-energy CT across scanner model and reconstruction algorithm configurations., Subjects and Methods: Patients underwent scanning with routine kidney stone composition protocols on both second- and third-generation dual-source CT scanners. Images were reconstructed using filtered back projection and iterative reconstruction (IR). In addition, a modified IR kernel on the third-generation CT scanner was evaluated. Individual kidney stone volumes were determined and compared., Results: No significant difference was noted in measured volumes between filtered back-projection data, IR data from the second-generation scanner, and the modified IR kernel data (p > 0.05). The third-generation commercially available IR kernel yielded lower volumes than did the other configurations (p < 0.0001)., Conclusion: With the use of a modified kernel for the third-generation scanner, patients being monitored for changes in kidney stone volume can undergo scanning performed with second- or third-generation dual-energy CT scanners, and the images obtained can be reconstructed with either filtered back projection or IR without the introduction of bias into kidney stone volume measurements.

Retrograde intrarenal surgery (RIRS) is highly successful at eliminating renal stones of various sizes and compositions. As urologists are taking on more complex procedures using RIRS, this has led to an increase in operative (OR) times. Our objective was to determine the best predictor of OR time in patients undergoing RIRS. We retrospectively reviewed the records of patients undergoing unilateral RIRS for solitary stones over a 10 year time span. Stones were fragmented and actively extracted using a basket. Variables potentially affecting OR time such as patient age, sex, BMI, lower pole stone location, volume, Hounsfield units (HU), composition, ureteral access sheath (UAS) use, and pre-operative stenting were collected. Multivariable linear and stepwise regression was used to evaluate the predictors of OR time. There were 118 patients that met inclusion criteria. The median stone volume was 282.6 mm 3 (IQR 150.7-644.7) and the mean OR time was 50 min (±25.9 SD). On univariate linear regression, stone volume had a moderate correlation with OR time (y = 0.022x + 38.2, r 2  = 0.363, p < 0.01). On multivariable stepwise regression, stone volume had the strongest impact on OR time, increasing time by 2.0 min for each 100 mm 3 increase in stone volume (p < 0.001). UAS added 13.5 (SE 3.9, p = 0.001) minutes and renal lower pole location added 9 min (SE 4.3, p = 0.03) in each case they were used. Pre-operative stenting, HU, calcium oxalate stone composition, sex, and age had no significant effect on OR time. Amongst the main stone factors in RIRS, stone volume has the strongest impact on operative time. This can be used to predict the length of the procedure by roughly adding 2 min per 100 mm 3 increase in stone volume.

This study describes and evaluates the use of non-contrast enhanced computerized tomography (NCCT) before and after extracorporeal shockwave lithotripsy (SWL). Computer measured stone volume was used as an exact measurement for treatment response. 81 patients received SWL of kidney stones at Herlev Hospital between April 2013 and January 2014 and follow-up was possible in 77 (95 %) patients. NCCT was used before and after treatment. Treatment response was expressed as a reduction of the stone volume. Stone characteristics as the stone volumes, HU, SSD and localization were measured by radiologist using a vendor non-specific computer program. Complications, patient characteristics and additional treatment were registered. On average, 5858 shocks were given each patient. The follow-up NCCT was performed 24 days after treatment. It was possible to calculate the stone volume in 88 % of the patients-the remaining 12 % it was not possible due to stone disintegration. The stone free rate was 22 %. The average relative reduction in stone burden was 62 %. Only 8 % of the patients were radiological non-responders. Steinstrasse was observed in 13 (17 %) and 28 (36 %) patients had additional treatment performed. Irradiation dose per NCCT was 2.6 mSv. Stone volume could be calculated in most patients. The relative reduction in stone burden after treatment was 62 %. The stone volume was redundant when evaluating stone free patients, but in cases of partial response it gave an exact quantification, to be used in the further management and follow-up of the patients.

Objectives: To determine the optimal method for assessing stone volume, and thus stone burden, by comparing the accuracy of scalene, oblate, and prolate ellipsoid volume equations with three-dimensional (3D)-reconstructed stone volume. Kidney stone volume may be helpful in predicting treatment outcome for renal stones. While the precise measurement of stone volume by 3D reconstruction can be accomplished using modern computer tomography (CT) scanning software, this technique is not available in all hospitals or with routine acute colic scanning protocols. Therefore, maximum diameters as measured by either X-ray or CT are used in the calculation of stone volume based on a scalene ellipsoid formula, as recommended by the European Association of Urology., Methods: In all, 100 stones with both X-ray and CT (1-2-mm slices) were reviewed. Complete and partial staghorn stones were excluded. Stone volume was calculated using software designed to measure tissue density of a certain range within a specified region of interest. Correlation coefficients among all measured outcomes were compared. Stone volumes were analysed to determine the average 'shape' of the stones., Results: The maximum stone diameter on X-ray was 3-25 mm and on CT was 3-36 mm, with a reasonable correlation (r = 0.77). Smaller stones (<9 mm) trended towards prolate ellipsoids ('rugby-ball' shaped), stones of 9-15 mm towards oblate ellipsoids (disc shaped), and stones >15 mm towards scalene ellipsoids. There was no difference in stone shape by location within the kidney., Conclusions: As the average shape of renal stones changes with diameter, no single equation for estimating stone volume can be recommended. As the maximum diameter increases, calculated stone volume becomes less accurate, suggesting that larger stones have more asymmetric shapes. We recommend that research looking at stone clearance rates should use 3D-reconstructed stone volumes when available, followed by prolate, oblate, or scalene ellipsoid formulas depending on the maximum stone diameter., (© 2013 The Authors. BJU International © 2013 BJU International.)