Use of computed tomography scout film and Hounsfield unit of computed tomography scan in predicting the radio-opacity of urinary calculi in plain kidney, ureter and bladder radiographs

Medial deviation of the ureter is a new sign that could predict stone impaction: a pilot study

OBJECTIVE

To assess the value medial deviation of the ureter at site of ureteric stone as a sign of ureteric stone impaction.

PATIENTS AND METHODS

All cases with medial deviation of the ureter at site of ureteric stones in our department over 4 years were enrolled in this pilot study. All cases were diagnosed with KUB and non-contrast CT (NCCT). Radiological and ureteroscopic findings were recorded.

RESULTS

A total of 32 patients with a single impacted stone in the proximal and middle third of the ureter were included in the study. Medial deviation of the ureter at the site of the stone was detected in the upper third of the ureter in 24 (75%) cases and in the middle third in 8 (25%) cases. There were mucosal polyps and mucosal erythema (inflammatory changes) seen by ureteroscopy in all cases (100%). Ureteroscopy was successfully completed with stone fragmentation in 23 (71.8%) patients: 8 of them needed ureteric catheter and 15 required JJ stent insertion. Failure of ureteroscopy with insertion of JJ stent was done in 5 (15.6%) patients. Removal of the stent and ureteroscopy was done after 4 weeks.

CONCLUSION

We conclude from this study that medial deviation of the ureter is a new reliable radiological sign of ureteric stone impaction.

Pure uric acid stone prediction model using the variant coefficient of stone density measured by thresholding 3D segmentation-based methods: A multicenter study

Urinary stones are common urological diseases with increasing prevalence and incidence worldwide. Among the various types of stones, uric acid stones can be dissolved by oral chemolysis without any surgical procedure. Therefore, our study demonstrates that variant coefficient of stone density measured by thresholding a three-dimensional segmentation-based method from noncontrast computed tomography images can be used to identify pure uric acid stones from non-pure uric acid stones. This study provides a preoperative pure uric acid stone prediction model that could reduce invasive procedural treatments. The pure uric acid stone prediction model may offer optimized clinical decision-making for patients with urinary stones.

BACKGROUND AND OBJECTIVES

While most urinary stones are managed with interventional therapy, uric acid (UA) stones can be dissolved by oral chemolysis without invasive procedures. This study aimed to develop and validate a pure UA (pUA) stone prediction model using a variant coefficient of stone density (VCSD) measured by thresholding a three-dimensional (3D) segmentation-based method.

METHODS

Patients with urolithiasis treated at Keimyung University Dongsan Hospital between January 2017 and December 2020 were divided into training and internal validation sets, and patients from Kyungpook National University Hospital between January 2017 and December 2018 were used as an external validation set. Each stone was segmented by a thresholding 3D segmentation-based method using an attenuation threshold of 130 Hounsfield units. VCSD was calculated as the stone heterogeneity index divided by the mean stone density.

RESULTS

A total of 1175 urinary stone cases in 1023 patients were enrolled in this study. Of these, 224 (19.1%) were pUA stone cases. Among the potential predictors, thresholding 3D segmentation-based VCSD, age, sex, radio-opacity, hypertension, diabetes, and urine pH were identified as independent pUA stone predictors, and VCSD was the most powerful indicator. The pUA stone prediction model showed good discrimination, yielding area under the receiver operating characteristic curve of 0.960 (95% confidence interval (CI): 0.940-0.979, P < 0.001), 0.931 (95% CI: 0.875-0.987, P < 0.001), and 0.938 (95% CI: 0.912-0.965, P < 0.001) in the training, internal validation, and external validation sets, respectively.

CONCLUSIONS

VCSD measured using 3D segmentation was a decisive independent predictive factor for pUA stones. Furthermore, the established prediction model with VCSD can serve as a noninvasive preoperative tool to identify pUA stones.

Analysis of stone-free rates and residual fragment sizes following standard percutaneous nephrolithotomy: mistakes in the treatment of non-opaque kidney stones

Our presented study aimed to evaluate the possible effects of stone opacity, on both the success of percutaneous nephrolithotomy and the sizes of residual fragments following the procedure. Medical records of patients undergoing PCNL treatment for kidney stones at our clinic between July 2014 and May 2022 were evaluated in a retrospective manner. A total sample size of 304 patients with the required criteria was included. Patients were divided into two groups based on the radiopacity status of the stones assessed in the kidney-ureter-bladder graphy (KUB) [Group O (n = 211): opaque, Group N (n = 93): non-opaque)]. Demographic data, laboratory results, and surgical follow-up information were comparatively evaluated between groups. The mean age and percentage of female patients were higher in Group N (45.2 vs. 25,1%; p < 0.001). Also, patients in this group were associated with more comorbidities. No significant difference was present regarding stones' laterality, size, surface area, and localization. Cases in the Group N group demonstrated higher median hemoglobin reduction [1.7 (IQR = 1.2-2.5) vs. 2 (IQR = 1.6-2.6); p = 0.047]. The stone-free rates in Group O patients were higher (67.8% vs. 53.8%; p = 0.014). The size of the residual fragments was meaningfully larger in Group N cases [8 (IQR = 7-13) vs. 10 (IQR = 8-16); p = 0.032]. Finally, no significant difference was observed between the groups regarding both minor (as grade 3a and below) and major (grade 3b and above) assessed by the Modified Clavien-Dindo Classification. Our data show that treatment of patients with so-called non-opaque kidney stones by PCNL results in low SFR and larger residual fragments, which is due to a variety of errors that should be avoided by appropriate measures.

Machine Learning Models for Predicting Stone-Free Status after Shockwave Lithotripsy: A Systematic Review and Meta-Analysis

We performed a systematic review and meta-analysis to investigate the use of machine learning techniques for predicting stone-free rates following Shockwave Lithotripsy (SWL). Eight papers (3264 patients) were included. Two studies used decision-tree approaches, five studies utilised Artificial Neural Networks (ANN), and one study combined a variety of approaches. The summary true positive rate was 79%, summary false positive rate was 14%, and Receiver Operator Characteristic (ROC) was 0.90 for machine learning approaches. Machine learning algorithms were at least as good as standard approaches. Further prospective evidence is needed to routinely apply machine learning algorithms in clinical practice.

Urolithiasis and intracorporeal lithotripsy in 37 Military Hospital, Accra, Ghana

Objective

The purpose of this study was to determine the indications and complications of intracorporeal lithotripsy in our institution.

Methods

Retrospective study carried out at the urology unit of the 37 Military Hospital between 2012-2015. 42 patients had intracorporeal lithotripsy out of 359 patients who had surgery within the period. Records of all patients who had intracorporeal lithotripsy between December 2012 to December 2015 were collected and analysed. An endourology log sheet was used to record data of patient's name, age, sex, indication for operation, location of stone, intraoperative complications, type of instruments/materials used, stone analysis and follow-up dates. All patients between the ages of six months to seventy years presenting with urinary stones diseases within the period were included, whilst patients with urinary stone disease who were managed with open surgery were excluded.Ethical clearance was obtained from the 37 Military Hospital institutional review board.

Results

Lithotripsy constituted 42/359(11.7%) of the methods used in the surgical cases done within the period.The commonest age of presentation was between 31-40 years (26.2%), with a male to female ratio of 2:1. The commonest indications for lithotripsy were pain (92.8%) and hydronephrosis (61.9%). Ureteric stones are more common (50%), followed by renal stones (45%) with the commonest site being the proximal ureter. The commonest procedure was ureteroscopy. Ureteral mucosal injury (5/43) (11.62%), was the commonest intraoperative complication. Postoperative complications were reno-cutaneous fistula (1/43) (2.32%), severe bleeding (1/43) (2.32%) haematuria (4/43) (9.30%).

Conclusion

Pain was the commonest indication for intra-corporeal lithotripsy (92.8%) and also the commonest post-operative complication (9.30%).

Funding

None declared.

Prediction of fragmentation of kidney stones: A statistical approach from NCCT images

INTRODUCTION

We sought to develop a system to predict the fragmentation of stones using non-contrast computed tomography (NCCT) image analysis of patients with renal stone disease.

METHODS

The features corresponding to first order statistical (FOS) method were extracted from the region of interest in the NCCT scan image of patients undergoing extracorporeal shockwave lithotripsy (ESWL) treatment and the breakability was predicted using neural network.

RESULTS

When mean was considered as the feature, the results indicated that the model developed for prediction had sensitivity of 80.7% in true positive (TP) cases. The percent accuracy in identifying correctly the TP and true negative (TN) cases was 90%. TN cases were identified with a specificity of 98.4%.

CONCLUSIONS

Application of statistical methods and training the neural network system will enable accurate prediction of the fragmentation and outcome of ESWL treatment.

Computerized tomography attenuation values can be used to differentiate hydronephrosis from pyonephrosis

PURPOSE

To determine the diagnostic value of computerized tomography (CT) in differentiating pyonephrosis from hydronephrosis on the basis of attenuation values (Hounsfield unit-HU).

METHODS

Data of the patients with grades 1-3 hydronephrosis on abdominopelvic CT, who underwent nephrostomy tube placement for decompression of the collecting system, were retrospectively analyzed. Patient demographics and CT findings were recorded along with the first access urine culture results. Three physicians calculated the surface areas and the attenuation values of the dilated collecting systems using the system software. Mean HU of pyonephrosis and hydronephrosis cases was compared.

RESULTS

A total of 105 patients with the mean age of 47.7 ± 15.5 (range 20-80) were included. The interclass correlation coefficient of three physicians was 0.981 for HU measurement and 0.999 for calculation of collecting system surface area. Of the patients, 47 (44.8 %) had pyonephrosis. Mean surface areas of the collecting system were similar in patients with pyonephrosis and hydronephrosis (1481.13 ± 1562.94 vs. 1612.94 ± 2261.4 mm², p = 0.735). Urine cultures were positive in all patients with pyonephrosis, whereas 12.7 % of hydronephrosis cases had bacterial in first access urine culture. The HU of the patients with pyonephrosis was significantly higher that that of patients with hydronephrosis (13.51 ± 13.29 vs. 4.67 ± 5.37, p = 0.0001). Having a HU of 9.21 or over diagnosed pyonephrosis accurately with 65.96 % sensitivity and 87.93 % specificity.

CONCLUSION

Measuring attenuation values of the collecting system may be useful to differentiate pyonephrosis from hydronephrosis. Diagnosing pyonephrosis accurately may avoid septic complications.

Distribution of ureteral stones and factors affecting their location and expulsion in patients with renal colic

Purpose

To evaluate the distribution of ureteral stones and to determine their characteristics and expulsion rate based on their location.

Materials and Methods

We retrospectively reviewed computed tomography (CT) findings of 246 patients who visited our Emergency Department (ED) for renal colic caused by unilateral ureteral stones between January 2013 and April 2014. Histograms were constructed to plot the distribution of stones based on initial CT findings. Data from 144 of the 246 patients who underwent medical expulsive therapy (MET) for 2 weeks were analyzed to evaluate the factors responsible for the stone distribution and expulsion.

Results

The upper ureter and ureterovesical junction (UVJ) were 2 peak locations at which stones initially lodged. Stones lodged at the upper ureter and ureteropelvic junction (group A) had a larger longitudinal diameter (4.21 mm vs. 3.56 mm, p=0.004) compared to those lodged at the lower ureter and UVJ (group B). The expulsion rate was 75.6% and 94.9% in groups A and B, respectively. There was no significant difference in the time interval from initiation of renal colic to arrival at the ED between groups A and B (p=0.422). Stone diameter was a significant predictor of MET failure (odds ratio [OR], 1.795; p=0.005) but the initial stone location was not (OR, 0.299; p=0.082).

Conclusions

The upper ureter and UVJ are 2 peak sites at which stones lodge. For stone size 10 mm or less, initial stone lodge site is not a significant predictor of MET failure in patients who have no previous history of active stone treatment in the ureter.