Predicting urinary stone composition based on single-energy noncontrast computed tomography: the challenge of cystine

Environmental Conditions as Determinants of Kidney Stone Formation

Urolithiasis is a disease characterized by the presence of stones in the urinary tract, whether in the kidneys, ureters, or bladder. Its origin is multiple, and causes can be cited as hereditary, environmental, dietary, anatomical, metabolic, or infectious factors. A kidney stone is a biomaterial that originates inside the urinary tract, following the principles of crystalline growth, and in most cases, it cannot be eliminated naturally. In this work, 40 calculi from the Don Benito, Badajoz University Hospital are studied and compared with those collected in Madrid to establish differences between both populations with the same pathology and located in very different geographical areas. Analysis by cathodoluminescence offers information on the low crystallinity of the phases and their hydration states, as well as the importance of the bonds with the Ca cation in all of the structures, which, in turn, is related to environmental and social factors of different population groups such as a high intake of proteins, medications, bacterial factors, or possible contamination with greenhouse gases, among other factors.

In-vivo or in-vitro stone attenuation: what is more valuable for the prediction of renal stone composition in non-contrast-enhanced abdominal computed tomography?

OBJECTIVES

To compare the efficacy of in-vivo and in-vitro stone attenuation in the prediction of stone composition using non-contrast-enhanced abdominal computed tomography (NCCT).

METHODS

This study included a total of 104 patients with renal stones who received percutaneous nephrolithotomy treatment for renal stones between December 2016 and December 2019 and underwent NCCT before the procedure. Preoperative (in-vivo) and postoperative (in-vitro) kidney stone attenuations were compared using the NCCT images of the patients. Renal stone fragments were analysed with the infrared spectrophotometer method.

RESULTS

The mean age of the 104 patients was 49.5 (interquartile range: 37-61) years. According to the receiver operating characteristics analysis, the cut-off values for the prediction of uric acid stones were determined to be 556 HU for the in-vivo and 774 HU for the in-vitro attenuation measurement. Sensitivity and specificity were 100% and 96.6%, respectively, for the in-vivo and 90.9 and 91%, respectively, for the in-vitro images. The cut-off values for the prediction of calcium stones were determined to be 824 HU and 1065 HU for the in-vivo and in-vitro attenuation measurements, respectively. Sensitivity and specificity were 97.3 and 96% for the in-vivo and 96 and 96% for the in-vitro images.

CONCLUSIONS

In-vivo stone attenuation measurement in NCCT was slightly superior to in-vitro measurement due to the reduction in the composition and size of the stone. Our findings show that NCCT in-vivo stone attenuation might differentiate uric acid and calcium stones from the other stone types.

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.

The combination of mean and maximum Hounsfield Unit allows more accurate prediction of uric acid stones

Based on mean Hounsfield Unit (HuMean), we aimed to evaluate the additional use of standard deviation of Hounsfield Unit (HuStd), minimum Hounsfield Unit (HuMin), and maximum Hounsfield Unit (HuMax) in noncontrast computed tomography (NCCT) to evaluate uric acid (UA) stones more accurately. The data of patients who underwent the NCCT examination and infrared spectroscopy in our hospital from August 2017 to December 2021 were analyzed retrospectively. Based on CT scans, the HuMean, HuStd, HuMin, and HuMax of all patients were measured. The patients were divided into groups according to the stone composition. The attenuation value of mixed stones was in the middle of their pure stones. Except for Str, statistically significant differences between UA stones and other pure stones were observed for HuMean, HuStd, HuMin, and HuMax. A moderate correlation was found between HuMean, HuStd, HuMin, and HuMax and UA stones (r_s showed -0.585, -0.409, -0.492, and -0.577, respectively). Receiver operator characteristic (ROC) curve showed that the area under the curve (AUC) of HuMean and HuMax were higher than those of HuStd and HuMin (AUC = 0.896, AUC = 0.891 vs. AUC = 0.777, AUC = 0.833). Higher AUC (0.904), specificity (0.899) and positive predictive value (PPV) (0.712) can be obtained by combining HuMean and HuMax in the diagnosis of UA stones. In conclusion, HuMean and HuMax can better predict UA stones than HuStd and HuMin. The combined use of HuMean and HuMax can lead to higher accuracy.

Cystinuria: clinical practice recommendation

Cystinuria (OMIM 220100) is an autosomal recessive hereditary disorder in which high urinary cystine excretion leads to the formation of cystine stones because of the low solubility of cystine at normal urinary pH. We developed clinical practice recommendation for diagnosis, surgical and medical treatment, and follow-up of patients with cystinuria. Elaboration of these clinical practice recommendations spanned from June 2018 to December 2019 with a consensus conference in January 2019. Selected topic areas were chosen by the co-chairs of the conference. Working groups focusing on specific topics were formed. Group members performed systematic literature review using MEDLINE, drafted the statements, and discussed them. They included geneticists, medical biochemists, pediatric and adult nephrologists, pediatric and adult urologists experts in cystinuria, and the Metabolic Nephropathy Joint Working Group of the European Reference Network for Rare Kidney Diseases (ERKNet) and eUROGEN members. Overall 20 statements were produced to provide guidance on diagnosis, genetic analysis, imaging techniques, surgical treatment (indication and modalities), conservative treatment (hydration, dietetic, alkalinization, and cystine-binding drugs), follow-up, self-monitoring, complications (renal failure and hypertension), and impact on quality of life. Because of the rarity of the disease and the poor level of evidence in the literature, these statements could not be graded. This clinical practice recommendation provides guidance on all aspects of the management of both adults and children with cystinuria, including diagnosis, surgery, and medical treatment.

Split bolus dual-energy CT urography after urine dilution: a one-stop shop for detection and characterisation of urolithiasis

AIM

To determine the diagnostic performance of split-bolus dual-energy computed tomography (CT) urography (SBDECTU) in the detection and characterisation of urolithiasis.

MATERIALS AND METHODS

This single-centre Institute Ethics Committee (IEC)-approved prospective study was conducted from April 2014 to November 2015. One hundred and thirty consenting adults with microscopic haematuria underwent dual-energy true non-enhanced CT (DETNE) of the whole abdomen followed by a SBDECTU. The SBDECTU protocol consisted of synchronous nephrogram-urogram acquisition following urine dilution by oral hydration and normal saline injection. Calculi were detected and characterised using virtual non-enhanced (VNE) images derived from SBDECT were compared with DETNE (the reference standard). The subjective image quality and radiation dose were compared.

RESULTS

Twenty-six participants had one or more calculi (total 129 calculi) detected on DETNE CT. The sensitivity and specificity of VNE on a per-patient basis were 100%. Of the 129 calculi, 118 were detected on VNE, with a sensitivity of 91.47% and an accuracy of 91.47%. Of the calculi, 83.9% (99/118) could be characterised on SBDECTU images. On VNE images, complete iodine subtraction was seen in 73.1% (19/26). By omitting DETNE CT, the mean dose-length product of 537.6±152.9 mGy and volume CT dose index of 10.9±2.9 mGy•cm² could have been saved.

CONCLUSION

SBDECTU has high diagnostic accuracy in the detection and characterisation of clinically significant urinary calculi at potentially half the radiation dose.

The clinical role of X-ray computed tomography to predict the clinical efficiency of extracorporeal shock wave lithotripsy

AIM

To evaluate the clinical efficiency of computed tomography for diagnostics of patients with urolithiasis and the choice of treatment strategy.

MATERIAL AND METHODS

The study was carried out at the Urological Clinic of I.M. Sechenov First Moscow State Medical University and included 1044 patients with urinary stones. The ultimate goal of this study was to predict the clinical efficiency of extracorporeal shock wave lithotripsy using a combination of computed tomography and densitometry. Extracorporeal shock wave lithotripsy was performed on "Siemens Lithostar Plus," "Siemens Modularis Uro," and "Dornier Gemini" lithotripters. Statistical analysis of clinical data included evaluation of individual sampling groups and calculation of weighted arithmetic mean ( M).

RESULTS

The efficiency of extracorporeal shock wave lithotripsy has been determined primarily using X-ray analysis of the concrement outlines and the structure (homogeneous or heterogeneous) of its central zone. However, in terms of efficiency and repetition rate (the number of fragmentation procedures required for complete clearance) of extracorporeal shock wave lithotripsy, the mean density of the concrement along the whole length of its three-dimensional structure (expressed in Hounsfield units) appeared to be the most reliable and informative predictive index in this study.

CONCLUSION

The combination of computed tomography with densitometry in the treatment of patients with urolithiasis allows one (1) to determine the exact localization, size, X-ray structure, and structural density of urinary stones and (2) to predict, on the basis of densitometric data histograms, the clinical efficiency and repetition rate of extracorporeal shock wave lithotripsy with due regard to the X-ray structure of peripheral and central zones, and mean density (in Hounsfield units) of urinary concrements.

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.

New Imaging Techniques in the Management of Stone Disease

Recent advances in computed tomography, X-ray-based imaging, and ultrasonography have improved the accuracy of urinary stone detection and differentiation of stone composition while minimizing radiation exposure. Dual-energy computed tomography and digital tomosynthesis show promise in predicting mineral composition to optimize medical and surgical therapy. Electromagnetic tracking may enhance the use of ultrasonography to achieve percutaneous renal access for nephrolithotomy. This article reviews innovations in imaging technology in the contemporary management of urinary stone disease.

A novel method for prediction of stone composition: the average and difference of Hounsfield units and their cut-off values

PURPOSE

The purpose of the study was to investigate the predictive value of stone measurements by including a novel method on non-contrast computed tomography (NCCT) images for stone composition.

METHODS

We retrospectively evaluated patients who had stone analysis, NCCT images, and underwent percutaneous nephrolithotomy between 2013 and 2016. Patient characteristics, stone measurements on NCCT images, and stone analysis results were evaluated. Hounsfield unit (HU) values (maximum (HU_max), minimum (HU_min), and average (HU_ave) of HU values) were investigated on NCCT images. HU_diff was calculated as the difference between the HU_max and the HU_min values. Patients were divided into seven stone groups and data were compared. Then patients were separately divided into two groups according to mineral complexity (mono-mineral and multi-mineral groups) and calcium-based (calcium and other stone groups) evaluation.

RESULTS

In the study, 115 patients were evaluated. Age, gender, HU_min, HU_max, and HU_ave were significantly different between the stone groups. HU_diff and HU_ave were found to be 341.5 HU (AUC = 0.719, p = 0.017) and 1051.5 HU (AUC = 0.701, p = 0.029) as cut-off, respectively. Seventy of 72 > 341.5 HU_diff patients and 64 of 67 > 1051.5 HU_ave patients had multi-mineral stones (p = 0.001, OR 9.26, and p = 0.028, OR 4.27), respectively. In multivariate analysis, > 341.5 HU_diff rate was significantly higher in multi-mineral and calcium stone groups; HU_ave was also significantly higher in the calcium stone group.

CONCLUSIONS

HU_diff and HU_ave were significant predictors of mineral complexity. HU_diff of < 341.5 HU showed 81.8% sensitivity and 67.2% specificity for identification of mono-mineral stones.

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.

Predicting the stone composition of children preoperatively by Hounsfield unit detection on non-contrast computed tomography

INTRODUCTION

Many studies have been performed on adult patients to reveal the relationship between Hounsfield unit (HU) value and composition of stone, but none have focused on childhood.

OBJECTIVE

We aimed to predict stone composition by HU properties in pre-intervention non-contrast computed tomography (NCCT) in children. This could help to orient patients towards more successful interventions.

MATERIALS AND METHODS

Data of 94 children, whose pre-intervention NCCT and post-interventional stone analysis were available were included. Stones were grouped into three groups: calcium oxalate (CaOx), cystine, and struvite. Besides spot urine PH value, core HU, periphery HU, and Hounsfield density (HUD) values were measured and groups were compared statistically.

RESULTS

The mean age of patients was 7 ± 4 (2-17) years and the female/male ratio was 51/43. The mean stone size was 11.7 ± 5 (4-24) mm. There were 50, 38, and 6 patients in the CaOx, cystine, and struvite groups, respectively. The median values for core HU, periphery HU, and mean HU in the CaOx group were significantly higher than the corresponding median values in the cystine and struvite groups. Significant median HUD difference was seen only between the CaOx and cystine groups. No difference was seen between the cystine and struvite groups in terms of HU parameters. To distinguish these groups, mean spot urine PH values were compared and were found to be higher in the struvite group than the cystine group (Table).

DISCUSSION

The retrospective nature and small number of patients in some groups are limitations of this study, which also does not include all stone compositions. Our cystine stone rate was higher than childhood stone composition distribution in the literature. This is because our center is a reference center in a region with high recurrence rates of cystine stones. In fact, high numbers of cystine stones helped us to compare them with calcium stones more accurately and became an advantage for this study.

CONCLUSIONS

NCCT at diagnosis can provide some information for determination of stone composition. While CaOx stones can be discriminated from cystine and struvite stones using HU parameters, a simple spot urine pH assessment must be added to distinguish cystine stones from struvite stones.

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.

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.

Stone heterogeneity index as the standard deviation of Hounsfield units: A novel predictor for shock-wave lithotripsy outcomes in ureter calculi

We investigated whether stone heterogeneity index (SHI), which a proxy of such variations, was defined as the standard deviation of a Hounsfield unit (HU) on non-contrast computed tomography (NCCT), can be a novel predictor for shock-wave lithotripsy (SWL) outcomes in patients with ureteral stones. Medical records were obtained from the consecutive database of 1,519 patients who underwent the first session of SWL for urinary stones between 2005 and 2013. Ultimately, 604 patients with radiopaque ureteral stones were eligible for this study. Stone related variables including stone size, mean stone density (MSD), skin-to-stone distance, and SHI were obtained on NCCT. Patients were classified into the low and high SHI groups using mean SHI and compared. One-session success rate in the high SHI group was better than in the low SHI group (74.3% vs. 63.9%, P = 0.008). Multivariate logistic regression analyses revealed that smaller stone size (OR 0.889, 95% CI: 0.841–0.937, P < 0.001), lower MSD (OR 0.995, 95% CI: 0.994–0.996, P < 0.001), and higher SHI (OR 1.011, 95% CI: 1.008–1.014, P < 0.001) were independent predictors of one-session success. The radiologic heterogeneity of urinary stones or SHI was an independent predictor for SWL success in patients with ureteral calculi and a useful clinical parameter for stone fragility.

Combining Mean and Standard Deviation of Hounsfield Unit Measurements from Preoperative CT Allows More Accurate Prediction of Urinary Stone Composition Than Mean Hounsfield Units Alone

INTRODUCTION AND OBJECTIVES

The mineral composition of a urinary stone may influence its surgical and medical treatment. Previous attempts at identifying stone composition based on mean Hounsfield Units (HUm) have had varied success. We aimed to evaluate the additional use of standard deviation of HU (HUsd) to more accurately predict stone composition.

METHODS

We identified patients from two centers who had undergone urinary stone treatment between 2006 and 2013 and had mineral stone analysis and a computed tomography (CT) available. HUm and HUsd of the stones were compared with ANOVA. Receiver operative characteristic analysis with area under the curve (AUC), Youden index, and likelihood ratio calculations were performed.

RESULTS

Data were available for 466 patients. The major components were calcium oxalate monohydrate (COM), uric acid, hydroxyapatite, struvite, brushite, cystine, and CO dihydrate (COD) in 41.4%, 19.3%, 12.4%, 7.5%, 5.8%, 5.4%, and 4.7% of patients, respectively. The HUm of UA and Br was significantly lower and higher than the HUm of any other stone type, respectively. HUm and HUsd were most accurate in predicting uric acid with an AUC of 0.969 and 0.851, respectively. The combined use of HUm and HUsd resulted in increased positive predictive value and higher likelihood ratios for identifying a stone's mineral composition for all stone types but COM.

CONCLUSIONS

To the best of our knowledge, this is the first report of CT data aiding in the prediction of brushite stone composition. Both HUm and HUsd can help predict stone composition and their combined use results in higher likelihood ratios influencing probability.

How should patients with cystine stone disease be evaluated and treated in the twenty-first century?

Cystinuria continues to be one of the most challenging stone diseases. During the latest decades our knowledge of the molecular basis of cystinuria has expanded. Today 160 different mutations in the SLC3A1 gene and 116 in the SLC7A9 gene are listed. The full implications of type A, B or AB status are not yet fully understood but may have implications for prognosis, management and treatment. Despite better understanding of the molecular basis of cystinuria the principles of recurrence prevention have remained essentially the same through decades. No curative treatment of cystinuria exists, and patients will have a life long risk of stone formation, repeated surgery, impaired renal function and quality of life. Therapy to reduce stone formation is directed towards lowering urine cystine concentration and increasing cystine solubility. Different molecules that could play a role in promoting nucleation and have a modulating effect on cystine solubility may represent new targets for cystinuria research. Investigation of newer thiol-containing drugs with fewer adverse effects is also warranted. Determining cystine capacity may be an effective tool to monitor the individual patient's response. Compliance in cystinuric patients concerning both dietary and pharmacological intervention is poor. Frequent clinical follow-up visits in dedicated centres seem to improve compliance. Cystinuric patients should be managed in dedicated centres offering the complete range of minimal invasive treatment modalities, enabling a personalized treatment approach in order to reduce risk and morbidity of multiple procedures.

Evaluating the Patient with Left Lower Quadrant Abdominal Pain

Left lower quadrant pain is a frequent indication for imaging in the emergency department. Most causes of pain originate from the colon, including diverticulitis, colitis, fecal impaction, and epiploic appendagitis. Left-sided urolithiasis and spontaneous hemorrhage in the retroperitoneum or rectus sheath are additional causes of pain. Computed tomography is the preferred imaging modality in the emergent setting for all of these pathologic conditions. Gynecologic, testicular, and neoplastic pathology may also cause left lower quadrant pain but are not discussed in this article.

Usefulness of hounsfield unit and density in the assessment and treatment of urinary stones

Computed tomography (CT) is widely used to examine stones in the urinary system. In addition to the size and location of the stone and the overall health of the kidney, CT can also assess the density of the stone in Hounsfield units (HU). The HU, or Hounsfield density, measured by CT, is related to the density of the tissue or stone. A number of studies have assessed the use of HU in urology. HUs have been used to predict the type and opacity of stones during diagnosis, and the efficacy has been assessed using methods including extracorporeal shock wave lithotripsy (ESWL), percutaneous nephrolithotomy (PCNL), ureterorenoscopic ureterolithotripsy (URSL), and medical expulsive treatment (MET). Previous studies have focused on the success rate of HU for predicting the type of stone and of ESWL treatment. Understanding the composition of the stone plays a key role in determining the most appropriate treatment modality. The most recent reports have suggested that the HU value and its variants facilitate prediction of stone composition. However, the inclusion of data regarding urine, such as pH and presence of crystals, increases the predictive accuracy. HUs, which now form part of the clinical guidelines, allow us to predict the success of ESWL; therefore, they should be taken into account when ESWL is considered as a treatment option. However, there are currently insufficient data available regarding the value of HU for assessing the efficacy of PCNL, URSL, and MET. Studies performed to date suggest that these values would make a significant contribution to the diagnosis and treatment of urinary system stones. However, more data are required to assess this further.