A combined model based on CT radiomics and clinical variables to predict uric acid calculi which have a good accuracy

The aim of this study was to develop a CT-based radiomics and clinical variable diagnostic model for the preoperative prediction of uric acid calculi. In this retrospective study, 370 patients with urolithiasis who underwent preoperative urinary CT scans were enrolled. The CT images of each patient were manually segmented, and radiomics features were extracted. Sixteen radiomics features were selected by one-way analysis of variance (ANOVA) and least absolute shrinkage and selection operator (LASSO). Logistic regression (LR), random forest (RF) and support vector machine (SVM) were used to model the selected features, and the model with the best performance was selected. Multivariate logistic regression was used to screen out significant clinical variables, and the radiomics features and clinical variables were combined to construct a nomogram model. The area under the receiver operating characteristic (ROC) curve (AUC), etc., were used to evaluate the diagnostic performance of the model. Among the three machine learning models, the LR model had the best performance and good robustness of the dataset. Therefore, the LR model was used to construct the nomogram. The AUCs of the nomogram model in the training set and validation set were 0.878 and 0.867, respectively, which were significantly higher than those of the radiomics model and the clinical feature model. The CT-based radiomics model based has good performance in distinguishing uric acid stones from nonuric acid stones, and the nomogram model has the best diagnostic performance among the three models. This model can provide an effective reference for clinical decision-making.

Comprehensive Nomogram for Prediction of the Uric Acid Composition of Ureteral Stones as a Part of Tailored Stone Therapy

BACKGROUND

Oral chemolitholysis is a noninvasive therapy for uric acid (UA) stones. Proper patient selection is crucial for success of the therapy.

OBJECTIVE

To develop a nomogram for prediction of UA stones using parameters gathered during emergency work-up for flank pain.

DESIGN, SETTING, AND PARTICIPANTS

A single-center cohort (459 patients) with singular ureteral stones and available stone analysis was retrospectively reviewed for radiological, urinary, and serological findings indicating UA stones.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

A Mann-Whitney U test or Kruskal-Wallis test was applied for univariate analysis. Categorical variables were compared using a χ² test. Binary logistic regression of significant parameters was performed to design the nomogram.

RESULTS AND LIMITATIONS

Univariate analysis revealed statistically significant differences in parameters between predominantly UA and non-UA groups, including median age (60 yr, interquartile range [IQR] 51.5-70.5 vs 51 yr, IQR 39-62; p < 0.001), body mass index (30.0 kg/m², IQR 27.25-35.0 vs 26.6 kg/m², IQR 24.0-30.467; p < 0.001), stone density (435.0 HU, IQR 329.0-528.0 vs 750.0 HU, IQR 548.0-995.0; p < 0.001), serum UA (437.5 μmol/l, IQR 374.25-478.0 vs 321.0 μmol/l, IQR 273.0-377.0; p < 0.001), and urine pH (5.5, IQR 5.0-5.5 vs 6.0, IQR 5.5-6.5; p < 0.001). Radiolucency was more frequent in the predominantly UA group (88.60% vs 32.70%; p < 0.001). Multivariate binary logistic regression confirmed age, body mass index, stone density, serum UA, urine pH, and radiolucency as independent predictors of UA stones and these parameters were used to design the nomogram.

CONCLUSIONS

We present a nomogram for the prediction of uric acid stones.

PATIENT SUMMARY

We developed a nomogram as a simple tool with potential to be useful in patient counseling regarding chemolitholysis as a tailored stone treatment for uric acid urinary stones.

Systemic analysis of urinary stones from the Northern, Eastern, Central, Southern and Southwest China by a multi-center study

BACKGROUND

To provide some basis for the prevention of urinary stones in general population, we did a systemic analysis of urinary stones from Northern, Eastern, Central, Southern and Southwest China by a multi-center study.

METHODS

A total of 11,157 urinary stones from Northern, Eastern, Central, Southern and Southwest China were obtained and analyzed by Fourier transform infrared spectroscopy. Combined with scanning electron microscopy and X-ray energy spectrometer, urinary stones were classified into different types. Furthermore, the correlation between stone types and clinical characteristics, as well as their regional distribution were elucidated.

RESULTS

Calcium oxalate stones were the most common type in each region, followed by calcium oxalate-calcium phosphate mixed stones, uric acid stones and calcium phosphate stones. The distribution of calcium oxalate stones were highest prevalence in Southwest China (67.9%, P < 0.05), followed by Eastern and Northern China. Anhydrous uric acid stones, with a constituent ratio of 19.3% in Southern China, and 13.7% in Central China, were significantly higher than that in other regions (P < 0.05). Elements analysis indicated varieties among stone types as well as distribution regions. Moreover, the clinical characteristics were highly correlated with stone types and anatomical locations but not their distribution regions.

CONCLUSIONS

The material and elements composition of urinary stones among different regions showed some varieties. Calcium oxalate stone has the highest constituent ratio in Southwest China, while anhydrous uric acid stone has the highest constituent ratio in Southern China. Moreover, the clinical characteristics were highly correlated with stone types and anatomical locations but not their distribution regions.

Uric acid nephrolithiasis: An update

Uric acid nephrolithiasis appears to increase in prevalence. While a relationship between uric acid stones and low urinary pH has been for long known, additional association with various metabolic conditions and pathophysiological basis has recently been elucidated. Some conditions such as diabetes and metabolic syndrome disease, excessive dietary intake, and increased endogenous uric acid production and/or defect in ammoniagenesis are associated with low urinary pH. In addition, the phenomenon of global warming could result in an increase in areas with greater climate risk for uric acid stone formation. There are three therapeutic steps to be taken for management of uric acid stones: identification of urinary pH profiles, assessment of urinary volume status, and identification of disorders leading to excessive uric acid production. However, the most important factor for uric acid stone formation is acid urinary pH, which is a prerequisite for uric acid precipitation. This article reviews recent insights into the pathophysiology of uric acid stones and their management.

Epidemiology, pathophysiology, and management of uric acid urolithiasis: A narrative review

An in-depth comprehension of the epidemiology as well as pathophysiology of uric acid urolithiasis is important for the identification, treatment, and prophylaxis of calculi in these patients. Persistently low urinary pH, hyperuricosuria, and low urinary volume are the most important factors in pathogenesis of uric acid urolithiasis. Other various causes of calculus formation comprises of chronic diarrhea, renal hyperuricosuria, insulin resistance, primary gout, extra purine in the diet, neoplastic syndromes, and congenital hyperuricemia. Non-contrast-enhanced computed tomography is the radiologic modality of choice for early assessment of patients with renal colic. Excluding situations where there is acute obstruction, rising blood chemistry, severe infection, or unresolved pain, the initial management ought to be medical dissolution by oral chemolysis since this method has proved to be effective in most of the cases.

Dual energy can accurately differentiate uric acid-containing urinary calculi from calcium stones

PURPOSE

To retrospectively evaluate the accuracy of dual-energy CT (DECT) in the detection of the chemical composition of urinary calculi in correlation with infrared spectroscopic stone analysis.

METHODS

We reviewed the CT scans of 255 patients who underwent DECT due to a clinical suspicion of urolithiasis. Out of this group, we included 64 patients with clinically symptomatic urolithiasis requiring stone removal. After surgical removal of the stone by ureterorenoscopy, chemical composition was analyzed with infrared spectroscopy. We correlated DECT stone characterization results with chemical stone composition based on dual-energy indices (DEI). A total of 213 renal and ureteral stones could be removed and chemically analyzed.

RESULTS

A total of 213 calculi were evaluated. Thirty eight out of sixty four (59 %) patients had >1 stone. DECT was used to differentiate stones by using DEI. Stones harboring calcium (CA) were color-coded in blue, while stones containing uric acid (UA) were colored red. Median DEI in UA-containing stones were 0.001. Non-UA-containing stones had a DEI between 0.073 for pure CA stones and 0.077 containing CA and other substances (p = 0.001; p = 0.03, respectively). Sensitivity of DECT was 98.4 % for differentiation of UA from non-UA-containing calculi. Specificity was 98.1 %. Mean effective radiation dose of DECT was 4.18 mSv (0.44-14.27 mSv), thus comparable to conventional CT scans of the abdomen. Conventional measurement of Hounsfield units did not correlate with stone composition.

CONCLUSION

DECT with image post-processing reliably discriminates UA-containing calculi from all other stones, but the study offered limitations. Discrimination within the non-UA stones cannot be reliably achieved but is clinically insignificant.

Metabolic syndrome, obesity and kidney stones

OBJECTIVES

To give a comprehensive and focused overview on the current knowledge of the causal relations of metabolic syndrome and/or central obesity with kidney stone formation.

METHODS

Previous reports were reviewed using PubMed, with a strict focus on the keywords (single or combinations thereof): urolithiasis, nephrolithiasis, kidney stones, obesity, metabolic syndrome, bariatric surgery, calcium oxalate stones, hyperoxaluria, insulin resistance, uric acid stones, acid-base metabolism.

RESULTS

Obesity (a body mass index, BMI, of >30 kg/m(2)) affects 10-27% of men and up to 38% of women in European countries. Worldwide, >300 million people are estimated to be obese. Epidemiologically, a greater BMI, greater weight, larger waist circumference and major weight gain are independently associated with an increased risk of renal stone formation, both for calcium oxalate and uric acid stone disease.

CONCLUSIONS

There are two distinct metabolic conditions accounting for kidney stone formation in patients with metabolic syndrome/central obesity. (i) Abdominal obesity predisposes to insulin resistance, which at the renal level causes reduced urinary ammonium excretion and thus a low urinary pH; the consequence is a greater risk of uric acid stone formation. (ii) Bariatric surgery, the only intervention that facilitates significant weight loss in morbidly obese people, carries a greater risk of calcium oxalate nephrolithiasis. The underlying pathophysiological mechanisms are profound enteric hyperoxaluria due to intestinal binding of calcium by malabsorbed fatty acids, and severe hypocitraturia due to soft or watery stools, which lead to chronic bicarbonate losses and intracellular metabolic acidosis.