Computerized Tomography Magnified Bone Windows are Superior to Standard Soft Tissue Windows for Accurate Measurement of Stone Size: An In Vitro and Clinical Study

Can Artificial Intelligence Accurately Detect Urinary Stones? A Systematic Review

Objectives: To perform a systematic review on artificial intelligence (AI) performances to detect urinary stones. Methods: A PROSPERO-registered (CRD473152) systematic search of Scopus, Web of Science, Embase, and PubMed databases was performed to identify original research articles pertaining to AI stone detection or measurement, using search terms ("automatic" OR "machine learning" OR "convolutional neural network" OR "artificial intelligence" OR "detection" AND "stone volume"). Risk-of-bias (RoB) assessment was performed according to the Cochrane RoB tool, the Joanna Briggs Institute Checklist for nonrandomized studies, and the Checklist for Artificial Intelligence in Medical Imaging (CLAIM). Results: Twelve studies were selected for the final review, including three multicenter and nine single-center retrospective studies. Eleven studies completed at least 50% of the CLAIM checkpoints and only one presented a high RoB. All included studies aimed to detect kidney (5/12, 42%), ureter (2/12, 16%), or urinary (5/12, 42%) stones on noncontrast computed tomography (NCCT), but 42% intended to automate measurement. Stone distinction from vascular calcification interested two studies. All studies used AI machine learning network training and internal validation, but a single one provided an external validation. Trained networks achieved stone detection, with sensitivity, specificity, and accuracy rates ranging from 58.7% to 100%, 68.5% to 100%, and 63% to 99.95%, respectively. Detection Dice score ranged from 83% to 97%. A high correlation between manual and automated stone volume (r = 0.95) was noted. Differentiate distal ureteral stones and phleboliths seemed feasible. Conclusions: AI processes can achieve automated urinary stone detection from NCCT. Further studies should provide urinary stone detection coupled with phlebolith distinction and an external validation, and include anatomical abnormalities and urologic foreign bodies (ureteral stent and nephrostomy tubes) cases.

Role of Noncontrast Computed Tomography Parameters in Predicting the Outcome of Extracorporeal Shock Wave Lithotripsy for Upper Urinary Stones Cases: A Meta-analysis

RATIONALE

Extracorporeal shock wave lithotripsy (ESWL) is widely considered the primary approach for managing urinary tract stones. This study aimed to assess the predictive factors associated with non-contrast computed tomography (NCCT)-based parameters of upper urinary stones in relation to the outcomes of ESWL.

MATERIALS AND METHODS

A systematic search was conducted in PubMed, ScienceDirect, Web of Science, and Cochrane Library to identify all relevant studies published up to June 3, 2023. Several NCCT-based parameters to predict ESWL outcomes, comprised of mean stone density (MSD), skin-to-stone distance (SSD), and stone size, were extracted and analyzed using Review Manager software.

RESULTS

Out of 979 publications screened, a total of 39 publications, involving 7869 patients, were enrolled in the analysis. The pooled estimate demonstrated significant differences between MSD, and stone size between successful and failure of stone fragmentation groups, in which lower values of these parameters are associated with successful ESWL outcomes.

CONCLUSION

The results from the current study suggested that lower NCCT parameters, notably MSD, SSD, and stone size, are significantly associated with successful ESWL outcome. However, additional large-scale prospective studies are required to utilize these parameters effectively, and the optimal cutoff value should be determined.

Comparison of ureteral stone measurements for predicting the efficacy of a single session of extracorporeal shockwave lithotripsy: one-, two-, and three-dimensional computed tomography measurements

The objective of this study was to compare the value of one-, two- and three-dimensional computed tomography (CT) measurements for predicting the efficacy of a single session of extracorporeal shock wave lithotripsy (ESWL) in patients with a single ureteral stone. A total of 165 patients were included based on the inclusion and exclusion criteria. Different models were constructed using a combination of patients' clinical data and measurements obtained by manual sketching and automated extraction software. Multivariate logistic regression was used to develop the models. Receiver operating characteristic curves were used to assess the performance of the models. There was good interobserver agreement for all measurements in different dimensions (P < 0.001). We also found that hydronephrosis, the largest diameter, the largest area, volume, and mean CT value were significantly greater in the failure group than in the success group (P < 0.01). Furthermore, all sizes and CT measurement values were found to be independent predictors for predicting efficacy after one session of ESWL (P < 0.05). In addition, the multivariate logistic analysis showed that the area under the curve (AUC) for two-dimensional and three-dimensional measurements was superior to that of one-dimensional measurement (P < 0.01). However, when size alone was included as a measurable predictor, there was no significant difference in the AUC among the one-, two-, and three-dimensional measurements (P > 0.05). In summary, after adjusting for clinical data, two- and three-dimensional measurements combining ureteral stone size and CT values were found to be the best predictors of ESWL efficacy, and software-based three-dimensional measurements should be considered to avoid interobserver variability in clinical practice.

How to estimate stone volume and its use in stone surgery: a comprehensive review

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.

Diagnostic performance and feasibility of dual-layer detector dual-energy CT for characterization of urinary stones in patients of different sizes

BACKGROUND

Urinary stones are frequently encountered in urology and are typically identified using non-contrast CT scans. Dual-energy CT (DECT) is a valuable imaging technique that produces material-specific images and allows for precise assessment of stone composition by estimating the effective atomic number (Zeff), a capability not achievable with the conventional single-energy CT's attenuation measurement method.

PURPOSE

To investigate the diagnostic performance and image quality of dual-layer detector DECT (dlDECT) in characterizing urinary stones in patients of different sizes.

METHODS

All consecutive dlDECT examinations with stone protocol and presence of urinary stones between July 2018 and November 2019 were retrospectively evaluated. Two radiologists independently reviewed 120 kVp and color-overlay Zeff images to determine stone composition (reference standard = crystallography) and image quality. The objective analysis included image noise and Zeff values measurement.

RESULTS

A total of 739 urinary stones (median size 3.7 mm, range 1-35 mm) were identified on 177 CT examinations from 155 adults (mean age, 57 ± 15 years, 80 men, median weight 82.6 kg, range 42.6-186.9 kg). Using color-overlay Zeff images, the radiologists could subjectively interpret the composition in all stones ≥ 3 mm (n = 491). For stones with available reference standards (n = 74), dlDECT yielded a sensitivity of 80% (95%CI 44-98%) and a specificity of 98% (95%CI 92-100%) in visually discriminating uric acid from non-uric acid stones. Patients weighing > 90 kg and ≤ 90 kg had similar stone characterizability (p = 0.20), with 86% of stones characterized in the > 90 kg group and 87% in the ≤ 90 kg group. All examinations throughout various patients' weights revealed acceptable image quality. A Zeff cutoff of 7.66 accurately distinguished uric acid from non-uric acid stones (AUC = 1.00). Zeff analysis revealed AUCs of 0.78 and 0.91 for differentiating calcium-based stones from other non-uric stones and all stone types, respectively.

CONCLUSION

dlDECT allowed accurate differentiation of uric acid and non-uric acid stones among patients with different body sizes with acceptable image quality.

CLINICAL IMPACT

The ability to accurately differentiate uric acid stones from non-uric acid stones using color-overlay Zeff images allows for better tailored treatment strategies, helping to choose appropriate interventions and prevent potential complications related to urinary stones in patient care.

2022 Recommendations of the AFU Lithiasis Committee: Diagnosis

The choice of imaging modality is guided by the clinical presentation and the context (acute or not). Although ultrasound is safe (no radiation) and easily available, non-contrast-enhanced CT has become the gold standard in the diagnostic strategy for patients with acute flank pain because of its sensitivity (93.1%) and specificity (96.6%). It also allows determining the stone size, volume and density, visualizing their internal structure, and assessing their distance from the skin and the adjacent anatomy. All these parameters can influence the stone management and the choice of intervention modality. METHODOLOGY: These recommendations were developed using two methods: the Clinical Practice Recommendations method (CPR) and the ADAPTE method, depending on whether the issue was considered in the EAU recommendations (https://uroweb.org/guidelines/urolithiasis [EAU Guidelines on urolithiasis. 2022]) and their adaptability to the French context.

Influence of a Deep Learning Noise Reduction on the CT Values, Image Noise and Characterization of Kidney and Ureter Stones

Deep-learning (DL) noise reduction techniques in computed tomography (CT) are expected to reduce the image noise while maintaining the clinically relevant information in reduced dose acquisitions. This study aimed to assess the size, attenuation, and objective image quality of reno-ureteric stones denoised using DL-software in comparison to traditionally reconstructed low-dose abdominal CT-images and evaluated its clinical impact. In this institutional review-board-approved retrospective study, 45 patients with renal and/or ureteral stones were included. All patients had undergone abdominal CT between August 2019 and October 2019. CT-images were reconstructed using the following three methods: filtered back-projection, iterative reconstruction, and PixelShine (DL-software) with both sharp and soft kernels. Stone size, CT attenuation, and objective image quality (signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR)) were evaluated and compared using Bonferroni-corrected Friedman tests. Objective image quality was measured in six regions-of-interest. Stone size ranged between 4.4 × 3.1−4.4 × 3.2 mm (sharp kernel) and 5.1 × 3.8−5.6 × 4.2 mm (soft kernel). Mean attenuation ranged between 704−717 Hounsfield Units (HU) (soft kernel) and 915−1047 HU (sharp kernel). Differences in measured stone sizes were ≤1.3 mm. DL-processed images resulted in significantly higher CNR and SNR values (p < 0.001) by decreasing image noise significantly (p < 0.001). DL-software significantly improved objective image quality while maintaining both correct stone size and CT-attenuation values. Therefore, the clinical impact of stone assessment in denoised image data sets remains unchanged. Through the relevant noise suppression, the software additionally offers the potential to further reduce radiation exposure.

Variables measured on three-dimensional computed tomography are preferred for predicting the outcomes of shock wave lithotripsy

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.

Manual kidney stone size measurements in computed tomography are most accurate using multiplanar image reformatations and bone window settings

Computed tomography in suspected urolithiasis provides information about the presence, location and size of stones. Particularly stone size is a key parameter in treatment decision; however, data on impact of reformatation and measurement strategies is sparse. This study aimed to investigate the influence of different image reformatations, slice thicknesses and window settings on stone size measurements. Reference stone sizes of 47 kidney stones representative for clinically encountered compositions were measured manually using a digital caliper (Man-M). Afterwards stones were placed in a 3D-printed, semi-anthropomorphic phantom, and scanned using a low dose protocol (CTDIvol 2 mGy). Images were reconstructed using hybrid-iterative and model-based iterative reconstruction algorithms (HIR, MBIR) with different slice thicknesses. Two independent readers measured largest stone diameter on axial (2 mm and 5 mm) and multiplanar reformatations (based upon 0.67 mm reconstructions) using different window settings (soft-tissue and bone). Statistics were conducted using ANOVA ± correction for multiple comparisons. Overall stone size in CT was underestimated compared to Man-M (8.8 ± 2.9 vs. 7.7 ± 2.7 mm, p < 0.05), yet closely correlated (r = 0.70). Reconstruction algorithm and slice thickness did not significantly impact measurements (p > 0.05), while image reformatations and window settings did (p < 0.05). CT measurements using multiplanar reformatation with a bone window setting showed closest agreement with Man-M (8.7 ± 3.1 vs. 8.8 ± 2.9 mm, p < 0.05, r = 0.83). Manual CT-based stone size measurements are most accurate using multiplanar image reformatation with a bone window setting, while measurements on axial planes with different slice thicknesses underestimate true stone size. Therefore, this procedure is recommended when impacting treatment decision.

Impact of Multiparametric Stone Measurement in Noncontrast Computer Tomography on Ureterorenoscopic Stone Removal

PURPOSE

Low-dose computer tomography (NCCT) is the standard imaging modality for patients with acute flank pain with a suspicion of urolithiasis. The stone size is usually measured 2D by a radiologist. We compared 3D stone measurement using different windows to the 2D measurement and evaluated the clinical impact on ureterorenoscopic stone removal (URS).

METHODS

One hundred sixty-four patients (201 stones) with a preoperative NCCT, following a URS within 4 weeks, were included in this study. Stone location, number and size of stones, operating time, and laser lithotripsy were documented. Stones were measured in 3D using bone and soft tissue window. The maximum diameter was compared to the radiological report. The U test, Kruskal-Wallis, and regression were used for statistical analyses.

RESULTS

Almost two-thirds (64.68%; 130 stones) of stone measurements in 3D with the bone window were lower than the radiologist reports in 2D. One-third (34.83%; 70 stones) of stone measurements were higher and 0.5% (1 stone) reported the same size. Using the 3D soft tissue window, 81.09% (163 stones), 17.91% (37 stones), and 1% (2 stones) of stones were measured bigger, smaller, or had the same measurement results, respectively. In the clinical setting, we could calculate a cutoff for laser lithotripsy at a maximum stone diameter of 5.70 mm (p < 0.01) with the 3D and 6.01 mm with the 2D measurements, respectively, and found a significant correlation between maximum stone diameter and operating time (p < 0.01) and number of stones and operating time (p < 0.01 with and p = 0.02 without laser).

CONCLUSION

3D stone measurement with bone window seems to be more accurate than 2D measurement, but 2D is sufficient for planning stone treatment.

Automatic Detection and Scoring of Kidney Stones on Noncontrast CT Images Using S.T.O.N.E. Nephrolithometry: Combined Deep Learning and Thresholding Methods

PURPOSE

To develop and validate a deep learning and thresholding-based model for automatic kidney stone detection and scoring according to S.T.O.N.E. nephrolithometry.

PROCEDURES

Abdominal noncontrast computed tomography (NCCT) images were retrospectively archived from February 2018 to April 2019 for three parts: a segmentation dataset (n = 167), a hydronephrosis classification dataset (n = 282), and test dataset (n = 117). The model consisted of four steps. First, the 3D U-Nets for kidney and renal sinus segmentation were developed. Second, the deep 3D dual-path networks for hydronephrosis grading were developed. Third, the thresholding methods were used to detect and segment stones in the renal sinus region. The stone size, CT attenuation, and tract length were calculated from the segmented stone region. Fourth, the stone's location was determined. The stone detection performance was estimated with sensitivity and positive predictive value (PPV). The hydronephrosis grading and stone size, tract length, number of involved calyces, and essence grading were estimated with the area under the curve (AUC) method and linear-weighted κ statistics, respectively.

RESULTS

The stone detection algorithm reached a sensitivity of 95.9 % (236/246) and a PPV of 98.7 % (236/239). The hydronephrosis classification algorithm achieved an AUC of 0.97. The scoring model results showed good agreement with radiologist results for the stone size, tract length, number of involved calyces, and essence grading (κ = 0.95, 95 % confidence interval [CI]: 0.92, 0.98; κ = 0.97, 95 % CI: 0.95, 1.00; κ = 0.95, 95 % CI: 0.92, 0.98; and κ = 0.97, 95 % CI: 0.94, 1.00), respectively.

CONCLUSIONS

The scoring model was constructed that can automatically detect and score stones in NCCT images.

Machine learning prediction of stone-free success in patients with urinary stone after treatment of shock wave lithotripsy

BACKGROUND

The aims of this study were to determine the predictive value of decision support analysis for the shock wave lithotripsy (SWL) success rate and to analyze the data obtained from patients who underwent SWL to assess the factors influencing the outcome by using machine learning methods.

METHODS

We retrospectively reviewed the medical records of 358 patients who underwent SWL for urinary stone (kidney and upper-ureter stone) between 2015 and 2018 and evaluated the possible prognostic features, including patient population characteristics, urinary stone characteristics on a non-contrast, computed tomographic image. We performed 80% training set and 20% test set for the predictions of success and mainly used decision tree-based machine learning algorithms, such as random forest (RF), extreme gradient boosting trees (XGBoost), and light gradient boosting method (LightGBM).

RESULTS

In machine learning analysis, the prediction accuracies for stone-free were 86.0, 87.5, and 87.9%, and those for one-session success were 78.0, 77.4, and 77.0% using RF, XGBoost, and LightGBM, respectively. In predictions for stone-free, LightGBM yielded the best accuracy and RF yielded the best one in those for one-session success among those methods. The sensitivity and specificity values for machine learning analytics are (0.74 to 0.78 and 0.92 to 0.93) for stone-free and (0.79 to 0.81 and 0.74 to 0.75) for one-session success, respectively. The area under curve (AUC) values for machine learning analytics are (0.84 to 0.85) for stone-free and (0.77 to 0.78) for one-session success and their 95% confidence intervals (CIs) are (0.730 to 0.933) and (0.673 to 0.866) in average of methods, respectively.

CONCLUSIONS

We applied a selected machine learning analysis to predict the result after treatment of SWL for urinary stone. About 88% accurate machine learning based predictive model was evaluated. The importance of machine learning algorithm can give matched insights to domain knowledge on effective and influential factors for SWL success outcomes.

Stone Burden Measurement by 3D Reconstruction on Noncontrast Computed Tomography Is Not a More Accurate Predictor of Stone-Free Rate After Percutaneous Nephrolithotomy Than 2D Stone Burden Measurements

Purpose: Stone burden has been reported as an independent predictor of stone-free rate after percutaneous nephrolithotomy (PCNL); however no consensus exists on a standardized method for measuring stone burden. Recently, stone volume has been advocated as the most accurate means of measuring stone burden. We aimed to compare different measuring methods of stone burden and to identify the predictive value of each for outcomes after PCNL. Materials and Methods: We performed a retrospective review of a prospective database of patients who underwent PCNL between 2006 and 2013. A preoperative CT and postoperative imaging at discharge were necessary for eligibility. Stone burden was assessed through four different ways on CT images: (1) cumulative stone diameter; (2) estimated SA (surface area) calculated as longest × orthogonal diameter × π/4; (3) manual outline of stone and computer SA calculation; and (4) automated 3D volume calculation using specific software. Primary outcome was stone-free status (SFS) at discharge. Secondary outcomes included operative time and the need for an ancillary procedure. Regression analysis and receiver operating characteristic curve analysis were used to evaluate the predictive value of each method. Results: Of 313 included patients, 69.6% were stone free at discharge. All measures of stone burden were independent predictors of SFS [OR and 95% CI of 1.027 (1.014, 1.040), 1.481 (1.180, 1.858), 1.736 (1.266, 2.380), and 1.311 (1.127, 1.526), respectively] and demonstrated similar predictive accuracy (area under the curve = 0.630, 0.630, 0.627, and 0.638, respectively). Stone burden by any measure was an independent predictor of operative time and secondary procedure. Conclusions: We demonstrated that measuring stone burden by manual outline or automated 3D volume on reformatted CT images had no added value compared with orthogonal measurement for predicting outcomes after PCNL.

Assessment of Residual Stone Fragments After Retrograde Intrarenal Surgery

OBJECTIVES

To define the most suitable approach to assess residual stone fragments after retrograde intrarenal surgery (RIRS).

METHODS

Ninety-two patients (115 renal units) submitted to RIRS for symptomatic kidney stones >5 mm and <20 mm or <15 mm in the lower Calyx diagnosed by noncontrast CT (NCCT) were prospectively studied. Residual fragments were assessed by endoscopic evaluation (END) at the end of the procedure and by NCCT, ultrasonography (US), and kidney, ureter, and bladder radiograph (KUB) on the 90th postoperative day (POD). NCCT was considered the gold standard for the evaluation of residual fragments after RIRS.

RESULTS

The 90th POD NCCT resulted in stone-free status in 74.8% (86/115), 0-2 mm in 8.7% (10/115), and >2 mm residual fragments in 16.5% (19/115) renal units. Stone-free status by END at the end of RIRS was coincident with NCCT in 93.0% of the cases (40/43). There were no cases of residual fragments >2 mm on NCCT if END resulted in stone-free status. In all cases where END resulted in residual fragments >2 mm, US proved to be correct according to NCCT. Neither US nor KUB was able to identify residual fragments between 0 and 2 mm. KUB had only 31.6% (6/19) sensitivity to detect residual fragments >2 mm and did not add sensitivity or specificity to US.

CONCLUSIONS

In the follow-up imaging after RIRS, we suggest that if END resulted in residual fragments <2 mm, a 90th POD NCCT should be performed. US may be used if END showed fragments >2 mm.

Computed tomography window affects kidney stones measurements

OBJECTIVES

Measurements of stone features may vary according to the non-contrast computed tomography (NCCT) technique. Using magnified bone window is the most accurate method to measure urinary stones. Possible differences between stone measurements in different NCCT windows have not been evaluated in stones located in the kidney. The aim of this study is to compare measurements of kidney stone features between NCCT bone and soft tissue windows in patients submitted to retrograde intrarenal surgery (RIRS).

MATERIALS AND METHODS

Preoperative and 90th postoperative day NCCT were performed in 92 consecutive symptomatic adult patients (115 renal units) with kidney stones between 5 mm to 20 mm (< 15 mm in the lower calyx) treated by RIRS. NCCT were evaluated in the magnified bone window and soft tissue window in three axes in a different time by a single radiologist blinded for the measurements of the NCCT other method.

RESULTS

Stone largest size (7.92±3.81 vs. 9.13±4.08; mm), volume (435.5±472.7 vs. 683.1±665.0; mm3) and density (989.4±330.2 vs. 893.0±324.6; HU) differed between bone and soft-tissue windows, respectively (p<0.0001) 5.2% of the renal units (6/115) were reclassified from residual fragments > 2 mm on soft tissue window to 0-2 mm on bone window.

CONCLUSION

Kidney stone measurements vary according to NCCT window. Measurements in soft tissue window NCCT of stone diameter and volume are larger and stone density is lesser than in bone window. These differences may have impact on clinical decisions.

Size is Not Everything That Matters: Preoperative CT Predictors of Stone Free After RIRS

OBJECTIVE

To define computed tomography (CT) predictors of residual fragments after retrograde intrarenal surgery (RIRS) for kidney stones up to 20 mm in patients never submitted to surgical procedures for stone removal.

METHODS

From August 2016 to August 2017, symptomatic adult patients with kidney stones less than 20 mm treated by RIRS had their pre- and postoperative CT prospectively evaluated in search for predictors of residual stone fragments. Stone size, stone volume, number of stones, stone density, and location were evaluated in preoperative CT and analyzed as predictors for residual stone fragments on 90 POD CT. Stone location was represented by the infundibulopelvic angle (IPA) measured for each stone on preoperative noncontrast CT using multiplanar reconstruction.

RESULTS

Ninety-two patients were successfully submitted to RIRS. Bilateral procedures were performed in 23 patients (25%) resulting in 115 renal units operated. Operative time was 54.5 ± 26.7 minutes (mean ± SD) and 96.7% (89/92) of the patients were discharged up to 12 hours after the procedure. Postoperative CT demonstrated stone-free in 86 of 115 (74.8%), 0-2 mm in 10 of 115 (8.7%), and > 2 mm residual fragments in 19 of 115 (16.5%) procedures. Logistic regression analysis revealed steep IPA was a predictor for any residual stone fragment after RIRS for kidney stones < 20 mm (P= .012). ROC curve showed that IPA < 41° was associated with a higher chance of residual fragments after RIRS.

CONCLUSION

IPA < 41° is associated with a higher chance of residual fragments after RIRS for kidney stones up to 20 mm.

A radiologist’s approach to CT KUB for the urologist

In this article we review the computed tomography imaging features of renal and ureteric calculi, the secondary signs of renal tract calculi and their possible complications. Most calculi appear as high-density foci due to their composition, whereas other signs that may be appreciated include the soft-tissue rim sign in the ureter, upstream renal tract dilation and peri-ureteric or peri-renal stranding. The most accurate means of measuring a calculus is in the coronal plane on bone windows. We also provide a systematic approach to interrogating computed tomography of the kidneys, ureter and bladder for the urologist, with examples of other conditions that may present as renal colic and are apparent on computed tomography.

Level of evidence: Not applicable as no original research is being proffered.

In-vitro comparison of different slice thicknesses and kernel settings for measurement of urinary stone size by computed tomography

Non-contrast enhanced computed tomography (NCCT) is widely used measuring stone size in patients with urolithiasis. We performed an evaluation of the accuracy of stone size measuring via NCCT. In an in-vitro study, we analyzed a total of 38 uric acid and 38 phantom stones. Within NCCT, we used different slice thicknesses (1.5 mm, 2.0 mm, and 3.0 mm) and kernel settings (bone and soft-tissue window). Maximal height, maximal length, and maximal width of each stone were measured on a picture archiving and communication system workstation. Blinded to these results, a second physician measured stone size in the same way using a caliper (real stone size). We used the Bland-Altman method for the analysis of agreement between the two measuring methods. The limit of agreement that was deemed clinical insignificant was ± 1.0 mm. All measurements via NCCT correlated significantly with the real stone size (p < 0.001). This was more pronounced for bone window and smaller slice thickness. Bland-Altman plots showed limits of agreement that exceeded the a priori defined level for all types of measurement with bone window and small slice thickness (1.5 mm) being better than soft-tissue window and large slice thickness (3.0 mm). We conclude that stone size measurement by NCCT with established settings is not exact. Stone size can easily be over- or underestimated by several millimeters. Using bone window and small slice thickness leads to more accurate results.

Noncontrast Computed Tomography Parameters for Predicting Shock Wave Lithotripsy Outcome in Upper Urinary Tract Stone Cases

Kidney stones are a major public health concern with continuously increasing worldwide prevalence. Shock wave lithotripsy (SWL) is the first line treatment choice for upper urinary tract calculi with ureteroscopy and has advantages of safety and noninvasiveness, but the treatment success rate of SWL is lower than that of other therapies. It is therefore important to identify predictive factors for SWL outcome and select a suitable treatment choice for patients with upper urinary tract calculi. In recent years, computed tomography (CT) has become the gold standard for diagnosis of upper urinary tract calculi. Several factors based on CT images, including skin-to-stone distance, mean stone density, stone heterogeneity index, and variation coefficient of stone density, have been reported to be useful for predicting SWL outcome. In addition, a new method of analysis, CT texture analysis, is reportedly useful for predicting SWL outcomes. This review aims to summarize CT parameters for predicting the outcome of shock wave lithotripsy in stone cases in the upper urinary tract.

Prediction of spontaneous ureteral stone passage: Automated 3D-measurements perform equal to radiologists, and linear measurements equal to volumetric

OBJECTIVES

To compare the ability of different size estimates to predict spontaneous passage of ureteral stones using a 3D-segmentation and to investigate the impact of manual measurement variability on the prediction of stone passage.

METHODS

We retrospectively included 391 consecutive patients with ureteral stones on non-contrast-enhanced CT (NECT). Three-dimensional segmentation size estimates were compared to the mean of three radiologists' measurements. Receiver-operating characteristic (ROC) analysis was performed for the prediction of spontaneous passage for each estimate. The difference in predicted passage probability between the manual estimates in upper and lower stones was compared.

RESULTS

The area under the ROC curve (AUC) for the measurements ranged from 0.88 to 0.90. Between the automated 3D algorithm and the manual measurements the 95% limits of agreement were 0.2 ± 1.4 mm for the width. The manual bone window measurements resulted in a > 20 percentage point (ppt) difference between the readers in the predicted passage probability in 44% of the upper and 6% of the lower ureteral stones.

CONCLUSIONS

All automated 3D algorithm size estimates independently predicted the spontaneous stone passage with similar high accuracy as the mean of three readers' manual linear measurements. Manual size estimation of upper stones showed large inter-reader variations for spontaneous passage prediction.

KEY POINTS

• An automated 3D technique predicts spontaneous stone passage with high accuracy. • Linear, areal and volumetric measurements performed similarly in predicting stone passage. • Reader variability has a large impact on the predicted prognosis for stone passage.

Low-dose CT with adaptive statistical iterative reconstruction for evaluation of urinary stone

Purpose

To prospectively determine the diagnostic performance of low-dose CT (LDCT) with adaptive statistical iterative reconstruction (ASIR) technique for the detection of urinary stone disease.

Results

The average DLP and ED was 408.16 ± 119.04 mGy and 6.12 ± 1.79 mSv in CDCT, and 138.19 ± 76.87 mGy and 2.07 ± 1.15 mSv in LDCT, respectively. The dose reduction rate of LDCT was nearly 66.1% for both DLP and ED (P < 0.05). LDCT–80% ASIR images showed great image quality (mean score = 4.09), which was similar to CDCT-FBP images (mean score = 4.17) (P > 0.05), but higher than LDCT-FBP images (mean score = 2.77) (P < 0.05).

Materials and Methods

70 consetutive patients with clinically suspected urolithiasis underwent non-enhanced CT. Followed by both conventional-dose CT (CDCT) and low-dose CT (LDCT) scans. Automatic tube current modulation (ATCM) scanning was used, with a noise index setting of 13 in CDCT and 25 in LDCT. Reconstructions were performed with filtered back projection (FBP) and different settings of adaptive statistical iterative reconstruction [ASIR(40%, 60%, 80%)]. Urinary calculi (size, location, number), image quality (scale 1–5), image noise (scale 1–3) and diagnostic confidence levels (scale 1–3) were evaluated and measured by two radiologists independently. Radiation dose was recorded by calculating dose length product (DLP) and effective dose (ED). Statistical analyses included Mann-Whitney U test and Paired t tests.

Conclusions

LDCT with ASIR can reduce the radiation dose while maintain relatively high image quality in the diagnosis of urinary stone diseases.

The transgluteal approach to shockwave lithotripsy to treat distal ureter stones: a prospective, randomized, and multicenter study

PURPOSE

We compared the outcomes of SWL to treat distal ureter stones with regard to the conventional prone and supine positions using the transgluteal approach through the greater sciatic foramen.

METHODS

A prospective, randomized, single-blind, and multicenter study was conducted between October 2014 and July 2015. The inclusion criteria were radio-opaque distal ureter stones with a maximum diameter of 0.5-2 cm as measured on a CT scan. The included 160 patients were randomly assigned to two groups: the prone group (n = 80; treated in the conventional prone position) and the transgluteal group (n = 80; treated in the supine position using a transgluteal approach). In the latter group, the focused shock wave was transmitted through the greater sciatic foramen with the head positioned at a 40° angle to the vertical. "Stone-free" was defined as the complete clearance of stone fragments, assessed using a CT scan at 2 weeks after treatment. Overall satisfaction was self-reported using a 0-5 Likert scale.

RESULTS

The overall efficacy was 66.9%. The stone-free rate was significantly higher in the transgluteal group (72.6%) than in the prone group (54.7%; odds ratio 2.413, 95% CI 1.010-5.761, P = 0.023). No serious adverse events due to treatment were observed in either group. The satisfaction score of the transgluteal group was 4.21 ± 0.81, and 83.6% were willing to repeat the same procedure if necessary.

CONCLUSIONS

SWL using the transgluteal approach via a supine position through the greater sciatic foramen was more effective than via the conventional prone position. Furthermore, this approach provided a comparably safe and satisfactory procedure.

The R.I.R.S. scoring system: An innovative scoring system for predicting stone-free rate following retrograde intrarenal surgery

Background

To establish and internally validate an innovative R.I.R.S. scoring system that allows urologists to preoperatively estimate the stone-free rate (SFR) after retrograde intrarenal surgery (RIRS).

Methods

This study included 382 eligible samples from a total 573 patients who underwent RIRS from January 2014 to December 2016. Four reproducible factors in the R.I.R.S. scoring system, including renal stone density, inferior pole stone, renal infundibular length and stone burden, were measured based on preoperative computed tomography of urography to evaluate the possibility of stone clearance after RIRS.

Results

The median cumulative diameter of the stones was 14 mm, and the interquartile range was 10 to 21. The SFR on postoperative day 1 in the present cohort was 61.5% (235 of 382), and the final SFR after 1 month was 73.6% (281 of 382). We established an innovative scoring system to evaluate SFR after RIRS using four preoperative characteristics. The range of the R.I.R.S. scoring system was 4 to 10. The overall score showed a great significance of stone-free status (p < 0.001). The area under the receiver operating characteristic curve of the R.I.R.S. scoring system was 0.904.

Conclusions

The R.I.R.S. scoring system is associated with SFR after RIRS. This innovative scoring system can preoperatively assess treatment success after intrarenal surgery and can be used for preoperative surgical arrangement and comparisons of outcomes among different centers and within a center over time.

Clinical utility of computed tomography Hounsfield characterization for percutaneous nephrolithotomy: a cross-sectional study

Background

Computed Tomography (CT) is considered the gold-standard for the pre-operative evaluation of urolithiasis. However, no Hounsfield (HU) variable capable of differentiating stone types has been clearly identified. The aim of this study is to assess the predictive value of HU parameters on CT for determining stone composition and outcomes in percutaneous nephrolithotomy (PCNL).

Methods

Seventy seven consecutive cases of PCNL between 2011 and 2016 were divided into 4 groups: 40 (52%) calcium, 26 (34%) uric acid, 5 (6%) struvite and 6 (8%) cystine stones. All images were reviewed by a single urologist using abdomen/bone windows to evaluate: stone volume, core (HUC), periphery HU and their absolute difference. HU density (HUD) was defined as the ratio between mean HU and the stone’s largest diameter. ROC curves assessed the predictive power of HU for determining stone composition/stone-free rate (SFR).

Results

No differences were found based on the viewing window (abdomen vs bone). Struvite stones had values halfway between hyperdense (calcium) and low-density (cystine/uric acid) calculi for all parameters except HUD, which was the lowest. All HU variables for medium-high density stones were greater than low-density stones (p < 0.001). HUC differentiated the two groups (cut-off 825 HU; specificity 90.6%, sensitivity 88.9%). HUD distinguished calcium from struvite (mean ± SD 51 ± 16 and 28 ± 12 respectively; p = 0.02) with high sensitivity (82.5%) and specificity (80%) at a cut-off of 35 HU/mm. Multivariate analysis revealed HUD ≥ 38.5 HU/mm to be an independent predictor of SFR (OR = 3.1, p = 0.03). No relationship was found between HU values and complication rate.

Conclusions

HU parameters help predict stone composition to select patients for oral chemolysis. HUD is an independent predictor of residual fragments after PCNL and may be fundamental to categorize it, driving the imaging choice at follow-up.

Electronic supplementary material

The online version of this article (10.1186/s12894-017-0296-1) contains supplementary material, which is available to authorized users.

A new method for predicting uric acid composition in urinary stones using routine single-energy CT

Urinary stones composed of uric acid can be treated medically. Prediction of uric acid stone type is, therefore, desirable when a urinary stone is diagnosed with unenhanced CT. The purpose of the present study was to describe single-energy thin slice quantitative CT parameters of urinary stones correlated to chemical stone type and to develop a method to distinguish pure uric acid stones (UA) from other stones (non-UA/Mix). Unenhanced thin slice single-energy CT images of 126 urinary stones (117 patients) with known chemical stone type were retrospectively included in the study. Among the included stones, 22 were UA and 104 were non-UA/Mix. The included CT images and Laplacian filtered images of the stones were quantitatively analyzed using operator-independent methods. A post hoc classification method for pure UA stones was created using a combination of cutoff values for the peak attenuation and peak point Laplacian. The stone types differed in most quantitative image characteristics including mean attenuation (p < 0.001), peak attenuation (p < 0.001), and peak point Laplacian (p < 0.001). The sensitivity for the post hoc-developed peak attenuation-peak point Laplacian method for classifying pure UA stones was 95% [21/22, 95% CI (77-100%)] and the specificity was 99% [103/104, 95% CI (95-100%)]. In conclusion, quantitative image analysis of thin slice routine single-energy CT images is promising for predicting pure UA content in urinary stones, with results comparable to double energy methods.

Size matters: The width and location of a ureteral stone accurately predict the chance of spontaneous passage

Objectives

To determine how to most accurately predict the chance of spontaneous passage of a ureteral stone using information in the diagnostic non-enhanced computed tomography (NECT) and to create predictive models with smaller stone size intervals than previously possible.

Methods

Retrospectively 392 consecutive patients with ureteric stone on NECT were included. Three radiologists independently measured the stone size. Stone location, side, hydronephrosis, CRP, medical expulsion therapy (MET) and all follow-up radiology until stone expulsion or 26 weeks were recorded. Logistic regressions were performed with spontaneous stone passage in 4 weeks and 20 weeks as the dependent variable.

Results

The spontaneous passage rate in 20 weeks was 312 out of 392 stones, 98% in 0–2 mm, 98% in 3 mm, 81% in 4 mm, 65% in 5 mm, 33% in 6 mm and 9% in ≥6.5 mm wide stones.

The stone size and location predicted spontaneous ureteric stone passage. The side and the grade of hydronephrosis only predicted stone passage in specific subgroups.

Conclusion

Spontaneous passage of a ureteral stone can be predicted with high accuracy with the information available in the NECT. We present a prediction method based on stone size and location.

Key Points

• Non-enhanced computed tomography can predict the outcome of ureteral stones.

• Stone size and location are the most important predictors of spontaneous passage.

• Prediction models based on stone width or length and stone location are introduced.

• The observed passage rates for stone size in mm-intervals are reported.

• Clinicians can make better decisions about treatment.

Comparison of ureteric stone size, on bone window versus standard soft-tissue window settings, on multi-detector non-contrast computed tomography

Objective

To compare the difference in mean stone size, as measured on bone window vs standard soft-tissue window setting using multi-detector computed tomography (MDCT) in patients with a solitary ureteric stone.

Patients and methods

In all, 60 patients presenting to the emergency and outpatient departments of a University Hospital from May 2015 to October 2015 and fulfilling the inclusion criteria were included in the study. A 64-slice MDCT was used to assess the locations and size of the ureteric stones. A consultant radiologist independently analysed the MDCT scans of all the patients. The mean difference in stone size was calculated between both window settings in axial and coronal planes.

Results

The mean (SD) age of the patients was 37.13 (11.9) years. Males constituted ∼68% of the cohort and 32% were female. In all, 85% of the patients had left ureteric stones and 15% had right ureteric stones. The mean (SD) stone size, as measured on the soft-tissue window setting was 6.68 (2.01) mm, and on the bone window setting was 4.8 (1.9) mm. The mean (SD) difference in stone size between the two window settings was +1.85 (0.55) mm. The two means were compared using Student’s t-test, and the difference was found to be statistically significant (P < 0.05).

Conclusion

The stone size measured using the soft-tissue window setting on a MDCT is significantly different from the measurement on the bone window setting.

Ultrasonography Significantly Overestimates Stone Size When Compared to Low-dose, Noncontrast Computed Tomography

OBJECTIVE

To evaluate the differences between low-dose noncontrast computed tomography (NCCT) and renal ultrasound (US) in the identification and measurement of urinary calculi.

MATERIALS AND METHODS

A retrospective review was conducted at 3 institutions of patients evaluated for flank pain with both renal US and NCCT, within 1 day of one another, from 2012 to 2015. Stone presence and size were compared between imaging modalities. Stone size was determined by largest measured diameter. Stones were grouped into size categories (≤5 mm, 5.1-10 mm, and >10 mm) based on NCCT and compared with US. Statistical analysis was performed using 2-sided t tests.

RESULTS

One hundred fifty-five patients received both a renal US and NCCT within 1 day. In 79 patients (51.0%), both US and NCCT identified a stone for size comparison. Fifty-eight patients (37.4%) had a stone visualized on NCCT but not on US, and 2 patients (1.3%) had a stone documented on US but not seen on NCCT. The average NCCT size of the stones missed on US was 4.5 mm. When comparing the average largest stone diameter for US (9.1 mm) vs NCCT (6.9 mm), US overestimated stone size by 2.2 mm (P < .001). US overestimated stone size by 84.6% for stones ≤5 mm, 27.1% for stones 5.1-10 mm, and 3.0% for stones >10 mm.

CONCLUSION

US significantly overestimated stone size and this was most pronounced for small (≤5 mm) stones. The potential for systematic overestimation of stone size with standard US techniques should be taken into consideration when evaluating endourologic treatment options.

Stone volume is best predictor of operative time required in retrograde intrarenal surgery for renal calculi: implications for surgical planning and quality improvement

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 mm³ (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 mm³ 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 mm³ increase in stone volume.

How do stone attenuation and skin-to-stone distance in computed tomography influence the performance of shock wave lithotripsy in ureteral stone disease?

Background

Shock wave lithotripsy (SWL) is a noninvasive, safe, and efficient treatment option for ureteral stones. Depending on stone location and size, the overall stone-free rate (SFR) varies significantly. Failure of stone disintegration results in unnecessary exposure to shock waves and radiation and requires alternative treatment procedures, which increases medical costs. It is therefore important to identify predictors of treatment success or failure in patients who are potential candidates for SWL before treatment. Nowadays, noncontrast computed tomography (NCCT) provides reliable information on stone location, size, number, and total stone burden. The impact of additional information provided by NCCT, such as skin-to-stone distance (SSD) and mean attenuation value (MAV), on stone fragmentation in ureteral stone disease has hardly been investigated separately so far. Thus, the objective of this study was to assess the influence of stone attenuation, SSD and body mass index (BMI) on the outcome of SWL in ureteral stones.

Methods

We reviewed the medical records of 104 patients (80 men, 24 women) with ureteral stone disease treated consecutively at our institution with SWL between 2010 and 2013. MAV in Hounsfield Units (HU) and SSD were determined by analyzing noncontrast computed tomography images. Outcome of SWL was defined as successful (visible stone fragmentation on kidney, ureter, and bladder film (KUB)) or failed (absent fragmentation on KUB).

Results

Overall success of SWL was 50 % (52 patients). Median stone attenuation was 956.9 HU (range 495–1210.8) in the group with successful disintegration and 944.6 (range 237–1302) in the patients who had absent or insufficient fragmentation. Median SSD was 125 mm (range 81–165 mm) in the group treated successfully and 141 mm (range 108–172 mm) in the patients with treatment failure. Unlike MAV (p = 0.37), SSD (p < 0.001) and BMI (p = 0.008) significantly correlated with treatment outcome.

Conclusion

The choice of treatment for ureteral stones should be based on stone location and size as considered in the AUA and EAU guidelines on urinary stone disease. In ambiguous cases, SSD and BMI can be used to assist in the decision. In this study, MAV showed no correlation with fragmentation rate of SWL.

Two- and three-dimensional CT measurements of urinary calculi length and width: a comparative study

BACKGROUND

The standard imaging procedure for a patient presenting with renal colic is unenhanced computed tomography (CT). The CT measured size has a close correlation to the estimated prognosis for spontaneous passage of a ureteral calculus. Size estimations of urinary calculi in CT images are still based on two-dimensional (2D) reformats.

PURPOSE

To develop and validate a calculus oriented three-dimensional (3D) method for measuring the length and width of urinary calculi and to compare the calculus oriented measurements of the length and width with corresponding 2D measurements obtained in axial and coronal reformats.

MATERIAL AND METHODS

Fifty unenhanced CT examinations demonstrating urinary calculi were included. A 3D symmetric segmentation algorithm was validated against reader size estimations. The calculus oriented size from the segmentation was then compared to the estimated size in axial and coronal 2D reformats.

RESULTS

The validation showed 0.1 ± 0.7 mm agreement against reference measure. There was a 0.4 mm median bias for 3D estimated calculus length compared to 2D (P < 0.001), but no significant bias for 3D width compared to 2D.

CONCLUSION

The length of a calculus in axial and coronal reformats becomes underestimated compared to 3D if its orientation is not aligned to the image planes. Future studies aiming to correlate calculus size with patient outcome should use a calculus oriented size estimation.

Kidney stones and imaging: what can your radiologist do for you?

OBJECTIVES

We discuss in this review, urologists' expectations of imaging in terms of detection, characterization, pre-planning treatment and follow-up of urinary stones.

MATERIALS AND METHODS

Data acquisition regarding kidney stones and imaging was performed using MEDLINE searches with combinations of the following keywords: urinary stones, CT Urography, low dose CT, MRI urography, renal stones ultrasound, conventional radiography, surgery.

RESULTS

CT has become the gold standard for the evaluation of urinary stones. Scanning provides information regarding stone (composition, size, burden, location), collecting system and renal parenchyma. Those findings are crucial in determining appropriate treatment strategies. Because CT exposes the patient to substantial ionizing radiation, efforts have already been made to decrease the CT radiation dose for CT examination (low dose CT) and optimize image quality. Efforts also are being made to use non ionizing modalities such as ultrasound in combination with radiography particularly for the follow up of renal stones.

CONCLUSION

CT is the preferred method for the evaluation and treatment planning of urolithiasis. CT radiation dose reduction can be achieved with low dose CT. However, conventional radiography and ultrasound are still recommended in the follow up of renal stones.

Tools to improve the accuracy of kidney stone sizing with ultrasound

PURPOSE

Ultrasound (US) overestimates stone size when compared with CT. The purpose of this work was to evaluate the overestimation of stone size with US in an in vitro water bath model and investigate methods to reduce overestimation.

MATERIALS AND METHODS

Ten human stones (3-12 mm) were measured using B-mode (brightness mode) US by a sonographer blinded to the true stone size. Images were captured and compared using both a commercial US machine and software-based research US device. Image gain was adjusted between moderate and high stone intensities, and the transducer-to-stone depth was varied from 6 to 10 cm. A computerized stone-sizing program was developed to outline the stone width based on a grayscale intensity threshold.

RESULTS

Overestimation with the commercial device increased with both gain and depth. Average overestimation at moderate and high gain was 1.9±0.8 and 2.1±0.9 mm, respectively (p=0.6). Overestimation increased an average of 22% with an every 2-cm increase in depth (p=0.02). Overestimation using the research device was 1.5±0.9 mm and did not vary with depth (p=0.28). Overestimation could be reduced to 0.02±1.1 mm (p<0.001) with the computerized stone-sizing program. However, a standardized threshold consistent across depth, system, or system settings could not be resolved.

CONCLUSION

Stone size is consistently overestimated with US. Overestimation increased with increasing depth and gain using the commercial machine. Overestimation was reduced and did not vary with depth, using the software-based US device. The computerized stone-sizing program shows the potential to reduce overestimation by implementing a grayscale intensity threshold for defining the stone size. More work is needed to standardize the approach, but if successful, such an approach could significantly improve stone-sizing accuracy and lead to automation of stone sizing.

Lithiasis size estimation variability depending on image technical methodology

The lithiasic size is a determining factor in selecting the most suitable treatment, surgical or medical. However, the method for obtaining a reliable lithiasic size is not standardized. Our objetives are to determine the differences between the estimated lithiasic sizes shown by plain radiography test and by computerized axial tomography (CT) scan (using different techniques) in relation to the actual size, and to establish which is the ideal type of imaging for this purpose. We present an in vitro model with lithiasis obtained in cooperation with four centers.

INCLUSION CRITERIA

lithiasis >0.5 cm, intact, and visible via simple radiography. A sample of 245 lithiases was obtained, with 87 rejected as they did not fulfill the inclusion criteria. Initially the three main actual diameters of each lithiasis were measured with a calibrator, then a plain X-ray and a CT scan were taken of the samples to determine the surface size in cm(2) for simple radiography; surface size and volume in cm(3) for CT scan, in bone window and soft tissue (Toshiba Aquillion 64, sections of 0.5 mm, 120 Kv, 250 mA). The tomographic area was calculated by employing the formula recommended by the European Association of Urology and scanner software. The actual, radiographic and tomographic measurements were taken by three different researchers who were unaware of the results obtained by the each other. The statistics program IBM SPSS Statistics(®) 19 was used. Differences were analyzed using the Wilcoxon sign test. The bone window CT scan slightly overestimated the actual lithiasic size (0.12 vs. 0.17 cm(3)), while in soft tissue window the actual volume was practically doubled (0.12 vs. 0.21 cm(3)) (p < 0.05). We did not find statistically significant differences in the comparison between actual surface size (0.39 cm(2)) and bone window CT scan size when using the EAU formula or scanner software (0.36/0.37 cm(2)). Resulting measurements in soft tissue window tended to significantly overestimate the surface size, although only slightly (0.42/0.44 cm(2)), whilst the plain radiography underestimated it slightly but significantly (0.37 cm(2)). CT scan, using the bone window, is the technical methodology with which the greatest in vitro accuracy in which actual lithiasis measurements can be estimated, although the craniocaudal diameter measurement will be overestimated. Using soft tissue window gives an overestimated size.

Utility and limitation of cumulative stone diameter in predicting urinary stone burden at flexible ureteroscopy with holmium laser lithotripsy: a single-center experience

PURPOSE

To retrospectively assess the clinical utility in ureteroscopy (URS) planning of cumulative stone diameter (CSD), which does not account for stone width or depth, as a predictor of URS outcome and compare it with stone volume.

MATERIALS AND METHODS

Patients with renal stones treated at a single institute by flexible URS were retrospectively evaluated. To assess the clinical utility of CSD, relationships between stone-free (SF) status and stone burden (CSD and volume) were analyzed using the area under the receiver operating characteristics (AUROC) curve. To identify stone number impact on CSD, the AUROC of CSD divided by stone number was evaluated. Correlation coefficients of CSD and stone volume were also calculated for groups by stone number.

RESULTS

In cases with CSD <20.0 mm, CSD and stone volume revealed equal ability to predict SF status. In cases with CSD ≥20.0 mm, stone volume showed higher predictive ability. The ROC curves for cases with ≥4 stones showed that CSD was less predictive of SF status than stone volume. The correlation coefficients of CSD and stone volume by stone number were 0.922 for 1 stone, 0.900 for 2-3 stones, and 0.661 for ≥4 stones.

CONCLUSIONS

In cases with CSD ≥20.0 mm or ≥4 stones, we should evaluate stone volume for a more predictive stone burden, and pretreatment non-contrast CT seems sufficient. In cases with CSD <20.0 mm or 1-3 stones, CSD was as valid a predictor of preoperative stone burden as stone volume, so preoperative kidney-ureter-bladder (KUB) films may be sufficient.

Radiation dose reduction at multidetector CT with adaptive statistical iterative reconstruction for evaluation of urolithiasis: how low can we go?

PURPOSE

To evaluate the performance of computed tomographic (CT) examinations at 80 and 100 kV with tube current-time products of 75-150 mA and the effect of adaptive statistical iterative reconstruction (ASIR) on CT image quality in patients with urinary stone disease.

MATERIALS AND METHODS

In this HIPAA-compliant institutional review board-approved study, verbal consent for prospective low-dose CT and waivers of consent for retrospective review of CT scans were obtained. Between November 2010 and April 2011, 25 patients (15 men, 10 women; mean age, 35 years) with urolithiasis underwent 64-section multidetector CT with 75-150 mA and noise index of 30. Modified protocol was based on body weight (<200 lb [90 kg], 80 kV; >200 lb [90 kg], 100 kV). Images of 5-mm section thickness were reconstructed with filtered back projection (FBP) and 60% and 80% ASIR techniques, with 3-mm coronal and sagittal reformations. Two readers independently reviewed FBP and ASIR data sets for image quality (scale, 1-5), noise (scale , 1-3), and calculi (number, size, location). Confidence levels for urolithiaisis and alternate diagnoses were rated (scale, 1-3). In 13 patients, FBP CT images acquired with the reference standard departmental protocol were available for comparison. Radiation dose was compared between imaging series. Statistical analysis was performed with Wilcoxon signed rank and paired t tests.

RESULTS

Modified-protocol FBP images showed low image quality (score, 2.5), with improvement on modified-protocol ASIR images (score, 3.4) (P=.03). All 33 stones (mean diameter, 6.1 mm; range, 2-28 mm) at modified-protocol CT were diagnosed by both readers. In 20 of 25 patients (80%), ASIR images were rated adequate for rendering other diagnoses in the abdomen (score, 2.0), as opposed to FBP images (score, 1.3). Mean radiation dose for modified-protocol CT was 1.8 mGy (1.3 mGy for patients<200 lb; 2.3 mGy for patients>200 lb) in comparison with 9.9 mGy for reference-protocol CT (P=.001).

CONCLUSION

Image quality improvements with ASIR at reduced radiation dose of 1.8 mGy enabled effective evaluation of urinary calculi without substantially affecting diagnostic confidence. © RSNA, 2012.

The most reliable preoperative assessment of renal stone burden as a predictor of stone-free status after flexible ureteroscopy with holmium laser lithotripsy: a single-center experience

OBJECTIVE

To examine which parameters should be measured to preoperatively determine the stone burden as predictors of stone-free (SF) status after a single flexible ureteroscopy (URS). Although several stone parameters reportedly influence the outcome of treatment for urinary stones, the most reliable indicators of stone burden remain unclear.

METHODS

Patients with renal stones treated by flexible URS with holmium laser lithotripsy between October 2009 and December 2011 at a single institute were retrospectively evaluated. The SF status was determined by kidney-ureter-bladder (KUB) films at postoperative day 1. Correlations of possible predictors with the SF status were analyzed using a logistic regression model.

RESULTS

According to the univariate analysis, the following variables were significantly associated with failed treatment: number of stones (P = .001), cumulative stone diameter (CSD) (P < .001), stone surface area (SA) (P < .001), stone volume (P < .001), and presence of lower pole calculi (P = .008). According to the multivariate analysis, the stone volume (P < .001) and the CSD (P = .015) were found to be independent predictors of SF status. The SA (P = .598) had no significant independent influence on the SF status.

CONCLUSION

Among the several parameters regarding the renal stone burden, the stone volume determined by noncontrast computed tomography and the CSD of the KUB were significantly and independently inversely related to the success rate of URS. Among the 3 parameters of stone burden, the SA was found to have a lower clinical utility and priority as a predictor of a SF status after URS.

Automated volumetric assessment by noncontrast computed tomography in the surveillance of nephrolithiasis

OBJECTIVE

To evaluate the use of automated volumetric assessment for stone surveillance and compare the results with manual linear measurement.

METHODS

We retrospectively reviewed patients seen in our stone clinic who had undergone 2 noncontrast computed tomography (NCCT) scans without stone intervention during the interval between scans. Thirty patients met our inclusion criteria and underwent longitudinal assessment for urolithiasis via NCCT (mean interval 583.2 days, range 122-2030). Fifty-two discrete calculi were analyzed. Three board certified radiologists measured maximal linear stone size in the axial plane using electronic calipers on soft tissue (ST) and bone windows (BWs). Automated stone volume was also obtained by each reader using a dedicated prototype software tool for stone evaluation.

RESULTS

Mean stone linear size and volume was 4.9 ± 2.8 mm (ST), 4.5 ± 2.6 mm (BW), and 116.2 ± 194.6 mm(3) (window independent), respectively. Mean interobserver variability for linear size measurement was 16.4 ± 10.5% (ST) and 20.3 ± 13.8% (BW). Interobserver variability for volumetric measurement was 0%. Of the 52 persistent stones, the mean percent change in linear stone size between CT studies was 39.3 ± 46.7% (ST) and 42.9 ± 53.1% (BW) growth, compared with 171.4 ± 320.1% (window independent) growth for automated volume measurement over a mean of 583.2 days. However, discordant results for increased vs decreased interval size was seen between linear and volumetric assessment in 19/52 stones (36.5%).

CONCLUSION

Automated volumetric measurement of renal calculi via NCCT is independent of specific reader and window settings. Volumetric assessment amplifies smaller linear changes over time, whereas as much as one third of cases show linear-volume measurement discordance. Volumetric assessment is therefore preferable, particularly for longitudinal surveillance of renal calculi.

CT-based determination of maximum ureteral stone area: a predictor of spontaneous passage

OBJECTIVE

The purpose of this study was to test the hypothesis that the maximum axial area of ureteral stones is a more accurate predictor of spontaneous passage than the maximum axial diameter.

MATERIALS AND METHODS

This study retrospectively reviewed 211 consecutive emergency department patients (mean age, 48.8 years; age range, 18-88 years) with acute flank pain due to ureteral stones diagnosed using unenhanced CT. Measurements of maximum atrial area were obtained using fixed (FTM) and variable (VTM) threshold methods. For the FTM, stones were segmented using an attenuation threshold of 130 HU. For the VTM, stones were segmented using an attenuation threshold determined by one half of individual stone attenuation. Measurements of maximum atrial diameter were obtained using soft-tissue and bone window settings. Receiver operating characteristic (ROC) analysis was used to compare the accuracy of maximum atrial area with maximum atrial diameter measurements for predicting spontaneous passage.

RESULTS

Fifty-seven patients (27%) required urologic intervention. The areas under the ROC curve (AUC) of maximum atrial area using FTM (0.83, p = 0.013) and VTM (0.84, p = 0.004) were larger than the AUC (0.8, p = 0.4) for maximum atrial diameter using bone window settings or AUC (0.79) for maximum atrial iameter using soft-tissue window settings. For stones with maximum atrial diameter (in soft-tissue window settings) > 5 mm and ≤ 10 mm, the accuracy of maximum atrial area using VTM (AUC = 0.75) and FTM (AUC = 0.74) was superior to the accuracy of maximum atrial diameter in soft-tissue (AUC = 0.67) and bone (AUC = 0.69) window settings (p < 0.05) in predicting spontaneous passage.

CONCLUSION

Determination of the maximum axial area may improve the accuracy in predicting spontaneous passage of ureteral stones, particularly those between 5 and 10 mm.