Morphological characteristics and microstructure of kidney stones using synchrotron radiation μCT reveal the mechanism of crystal growth and aggregation in mixed stones

The key role of major and trace elements in the formation of five common urinary stones

BACKGROUND

Urolithiasis has emerged as a global affliction, recognized as one of the most excruciating medical issues. The elemental composition of stones provides crucial information, aiding in understanding the causes, mechanisms, and individual variations in stone formation. By understanding the interactions between elements in various types of stones and exploring the key role of elements in stone formation, insights are provided for the prevention and treatment of urinary stone disease.

METHODS

This study collected urinary stone samples from 80 patients in Beijing. The chemical compositions of urinary stones were identified using an infrared spectrometer. The concentrations of major and trace elements in the urinary stones were determined using Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES) and Inductively Coupled Plasma Mass Spectrometry (ICP-MS), respectively. The data were processed using correlation analysis and Principal Component Analysis (PCA) methods.

RESULTS

Urinary stones are categorized into five types: the calcium oxalate (CO) stone, carbonate apatite (CA) stone, uric acid (UA) stone, mixed CO and CA stone, and mixed CO and UA stone. Ca is the predominant element, with an average content ranging from 2.64 to 27.68% across the five stone groups. Based on geochemical analysis, the high-content elements follow this order: Ca > Mg > Na > K > Zn > Sr. Correlation analysis and PCA suggested significant variations in the interactions between elements for different types of urinary stones. Trace elements with charges and ionic structures similar to Ca may substitute for Ca during the process of stone formation, such as Sr and Pb affecting the Ca in most stone types except mixed stone types. Moreover, the Mg, Zn and Ba can substitute for Ca in the mixed stone types, showing element behavior dependents on the stone types.

CONCLUSION

This study primarily reveals distinct elemental features associated with five types of urinary stones. Additionally, the analysis of these elements indicates that substitutions of trace elements with charges and ion structures similar to Ca (such as Sr and Pb) impact most stone types. This suggests a dependence of stone composition on elemental behavior. The findings of this study will enhance our ability to address the challenges posed by urinary stones to global health and improve the precision of interventions for individuals with different stone compositions.

Kidney stone growth through the lens of Raman mapping

Bulk composition of kidney stones, often analyzed with infrared spectroscopy, plays an essential role in determining the course of treatment for kidney stone disease. Though bulk analysis of kidney stones can hint at the general causes of stone formation, it is necessary to understand kidney stone microstructure to further advance potential treatments that rely on in vivo dissolution of stones rather than surgery. The utility of Raman microscopy is demonstrated for the purpose of studying kidney stone microstructure with chemical maps at ≤ 1 µm scales collected for calcium oxalate, calcium phosphate, uric acid, and struvite stones. Observed microstructures are discussed with respect to kidney stone growth and dissolution with emphasis placed on < 5 µm features that would be difficult to identify using alternative techniques including micro computed tomography. These features include thin concentric rings of calcium oxalate monohydrate within uric acid stones and increased frequency of calcium oxalate crystals within regions of elongated crystal growth in a brushite stone. We relate these observations to potential concerns of clinical significance including dissolution of uric acid by raising urine pH and the higher rates of brushite stone recurrence compared to other non-infectious kidney stones.

Sample preparation and analysis protocols for the elucidation of structure and chemical distribution in kidney stones

Examining intact kidney stones both qualitatively and quantitatively can be difficult due to their size and fragility. Many modern analysis methods often lead to the destruction of the stone's structure during sample preparation. Preserving the structural integrity is crucial for accurately determining the chemical distribution of the components of kidney stones, which, in turn, improves our understanding of the disease's etiology. Infrared microspectroscopy and imaging play a vital role in revealing the stone's microstructure and component distribution. Consequently, this research focuses on investigating the impact of different sample preparation techniques on kidney stone analysis using infrared microspectroscopy. Specifically, it explores how polishing the surface of cross-sectioned stones influences the results. The polishing was performed utilizing abrasive discs and lapping films. A polishing device was also designed for the optimization of sample preparation. Additionally, this work involved a comparison of reflection infrared imaging with Attenuated Total Internal Reflection (ATR) infrared microspectroscopic imaging for the analysis of the microstructure of urinary stones.

Uric acid en route to gout

Gout and hyperuricemia (HU) have generated immense attention due to increased prevalence. Gout is a multifactorial metabolic and inflammatory disease that occurs when increased uric acid (UA) induce HU resulting in monosodium urate (MSU) crystal deposition in joints. However, gout pathogenesis does not always involve these events and HU does not always cause a gout flare. Treatment with UA-lowering therapeutics may not prevent or reduce the incidence of gout flare or gout-associated comorbidities. UA exhibits both pro- and anti-inflammation functions in gout pathogenesis. HU and gout share mechanistic and metabolic connections at a systematic level, as shown by studies on associated comorbidities. Recent studies on the interplay between UA, HU, MSU and gout as well as the development of HU and gout in association with metabolic syndromes, non-alcoholic fatty liver disease (NAFLD), and cardiovascular, renal and cerebrovascular diseases are discussed. This review examines current and potential therapeutic regimens and illuminates the journey from disrupted UA to gout.

Theranostic roles of machine learning in clinical management of kidney stone disease

Kidney stone disease (KSD) is a common illness caused by deposition of solid minerals formed inside the kidney. The disease prevalence varies, based on sociodemographic, lifestyle, dietary, genetic, gender, age, environmental and climatic factors, but has been continuously increasing worldwide. KSD is a highly recurrent disease, and the recurrence rate is about 11% within two years after the stone removal. Recently, machine learning has been widely used for KSD detection, stone type prediction, determination of appropriate treatment modality and prediction of therapeutic outcome. This review provides a brief overview of KSD and discusses how machine learning can be applied to diagnostics, therapeutics and prognostics in clinical management of KSD for better therapeutic outcome.

Multidisciplinary investigation of an ancient renal stone in a mummy from Popoli, central Italy

The renal stone found in the natural mummy of an anonymous nobleman dating to 19^th century was investigated using advanced imaging modalities and analytic investigations. By this multidisciplinary approach we were able to identify the chemical components and their distribution throughout the sample. These results allowed to understand the lifestyle habits of the subject, as well as the exact pathogenesis of his disease.

Detection of the mineral constituents in human renal calculi by vibrational spectroscopic analysis combined with allied techniques Powder XRD, TGA, SEM, IR imaging and TXRF

Detection of the mineral constituents in a batch of 310 samples of human urinary calculi (kidney stones-235 and bladder stones-75) combined with a semi-quantitative analysis has been presented on the basis of Fourier Transform based IR and Raman spectral measurements. Some of the observed characteristic IR and Raman bands have been proposed as 'Marker Bands' for the most reliable identification of the constituents. A detailed vibrational spectral analysis combined with a DFT level calculation for the functional groups in Calcium Oxalate Monohydrate (COM), Magnesium Ammonium Phosphate Hexahydrate (MAPH), Calcium Hydrogen Phosphate Dihydrate (CHPD), Penta-Calcium Hydroxy-Triphosphate (PCHT) and Uric Acid (UA) has been proposed. It has been shown that the identified mineral constituents as major or minor components can be deduced from the application of Lambert-Beer law of radiation absorption and results are in agreement with quantitative Spectral Data base. This simple method has the potential to be integrated into the management of Urolithiasis, a process of forming renal calculi in the kidney, bladder and/or urethra. Employment of powder XRD, TGA, SEM, TXRF and IR Imaging techniques has provided additional support for the proposed foolproof identification of the mineral constituents. Among the mineral constituents, Calcium Oxalate Monohydrate, Calcium Oxalate Dihydrate or their mixture account for 85% of the total number of samples; the remaining 15% and 5% samples contain Phosphate and Uric acid stones respectively.

Bioinformatics analysis of pathways of renal infiltrating macrophages in different renal disease models

Background

Recent studies have suggested that macrophages are significantly involved in different renal diseases. However, the role of these renal infiltrating macrophages has not been entirely uncovered. To further clarify the underlying mechanism and identify therapeutic targets, a bioinformatic analysis based on transcriptome profiles was performed.

Methods

Three transcription profiling datasets, GSE27045, GSE51466 and GSE75808, were obtained from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were assessed by Gene Ontology (GO) functional annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and gene set enrichment analysis (GSEA).

Results

The classic signaling pathways and metabolic pathways of macrophages infiltrating the kidney in different pathophysiological processes, including lupus nephritis (LN), renal crystal formation and renal ischemia-reperfusion injury (IRI), were analysed. Furthermore, the common classical pathways significantly altered in the three renal disorders were the oxidative phosphorylation, VEGF signaling and JAK/STAT signaling pathways, while the renin-angiotensin system was uniquely altered in LN, the glycolysis and gluconeogenesis pathways were uniquely altered in models of renal crystal formation, and the calcium signaling pathway was specific to renal IRI.

Conclusions

Via bioinformatics analysis, this study revealed the transcriptional features of macrophages in murine LN, renal crystal formation and IRI models, which may serve as promising targets for mechanistic research and the clinical treatment of multiple renal diseases.

The white beam station at imaging beamline BL-4, Indus-2

The high flux density of synchrotron white beam offers several advantages in X-ray imaging such as higher resolution and signal-to-noise ratio in 3D/4D micro-tomography, higher frame rate in real-time imaging of transient phenomena, and higher penetration in thick and dense materials especially at higher energies. However, these advantages come with additional challenges to beamline optics, camera and sample due to increased heat load and radiation damage, and to personal safety due to higher radiation dose and ozone gas hazards. In this work, a white beam imaging facility at imaging beamline BL-4, Indus-2, has been developed, while taking care of various instrumental and personal safety challenges. The facility has been tested to achieve 1.5 µm spatial resolution, increased penetration depth up to 900 µm in steel, and high temporal resolutions of ∼10 ms (region of interest 2048 × 2048 pixels) and 70 µs (256 × 2048 pixels). The facility is being used successfully for X-ray imaging, non-destructive testing and dosimetry experiments.

Automated radiomic analysis of CT images to predict likelihood of spontaneous passage of symptomatic renal stones

PURPOSE

To evaluate the ability of a semi-automated radiomic analysis software in predicting the likelihood of spontaneous passage of urinary stones compared with manual measurements.

METHODS

Symptomatic patients visiting the emergency department with suspected stones in either kidney or ureters who underwent a CT scan were included. Patients were followed for up to 6 months for the outcome of a trial of passage. Maximum stone diameters in axial and coronal images were measured manually. Stone length, width, height, max diameter, volume, the mean and standard deviation of the Hounsfield units, and morphologic features were also measured using automated radiomic analysis software. Multivariate models were developed using these data to predict subsequent spontaneous stone passage, with results expressed as the area under a receiver operating curve (AUC).

RESULTS

One hundred eighty-four patients (69 females) with a median age of 56 years were included. Spontaneous stone passage occurred in 114 patients (62%). Univariate analysis demonstrated an AUC of 0.83 and 0.82 for the maximum stone diameter determined manually in the axial and coronal planes, respectively. Multivariate models demonstrated an AUC of 0.82 for a model including manual measurement of maximum stone diameter in axial and coronal planes. The same AUC was found for a model including automatic measurement of maximum height and diameter of the stone. Further addition of morphological parameters measured automatically did not increase AUC beyond 0.83.

CONCLUSION

The semi-automated radiomic analysis of urinary stones shows similar accuracy compared with manual measurements for predicting urinary stone passage. Further studies are needed to predict clinical impacts of reporting the likelihood of urinary stone passage and improving inter-observer variation using automatic radiomic analysis software.

A Combined Experimental and Modelling Study on Solubility of Calcium Oxalate Monohydrate at Physiologically Relevant pH and Temperatures

Accurate Calcium Oxalate Monohydrate (COM) solubility measurements are essential for elucidating the physiochemical mechanism behind the formation of kidney stones, nephrolithiasis. Yet the reported solubility values of COM in ultrapure water, arguably the simplest solvent relevant for nephrolithiasis, vary significantly depending on implemented method. To address this variation, we present an experimental study of the solubility of COM validated by a model based on the Debye–Hückel theory describing the solution chemistry and the complex formation. We also carefully monitor potential pseudopolymorphic/hydrate transitions during the solubility measurements with in-situ and ex-situ methods. Our results indicate that the solubility of COM in ultrapure water is a weak function of temperature. However, the measured solubility varies significantly in buffer solutions across physiologically relevant pH values at body temperature. The proposed model explains observed trends as a combined effect of ionic strength, protonation reactions, and soluble complex formation. Moreover, it predicts solubility of COM in buffer solutions remarkably well using our measurements in ultrapure water as input, demonstrating the consistency of presented approach. The presented study parleying experiments and modelling provides a solid stepping stone to extend the physiochemical understanding of nephrolithiasis to more realistic solutions laden with biological complexity.

The surgeon's role on chemical investigations of the composition of urinary stones

The chemical analysis of an urolith is often interpreted as "stone's composition". However, it must be taken into consideration, that in most cases, only a fragment of the stone has been sent to the laboratory. In some recurrent patients, stone compositions either vary considerably between episodes or the analytical result obtained from the stone fragment does not fit with the data of e.g. current 24 h-urinalysis or urinary pH-records. The question arises, whether this outcome may be the result of an improper stone sampling scheme. On a simple layered 2D-stone model composed of two mineral phases it is shown, how the choice of a stone fragment process may influence the result of "stone composition". Depending on the initial position of fragment within the whole stone, the respective calculated analyses can relevantly differ from the whole stone composition as well as strongly between two fragments. Even under the simplified conditions of a 2D-2-component-model "grown" under defined conditions, the differences between the analyses of the different specimens taken from a stone are in part remarkable. The more it can be argued that these differences increase if a real 3D-urolith is investigated. Further sampling biases may evolve and increase the problem of proper sampling:, e.g., if an urolith's more resistant parts remain intact while ESWL or laser-based stone fragmentation ("dusting"), the weak parts became fully disintegrated and removed from the body as fine-grained sludge-the stone's fine fraction is lost although its composition may carry important information on the stone's pathogenesis. Consequently, a "stone analysis" only obtained from the harder remains reveals an incomplete result, a fact that in principle limits its clinical interpretation. Choice of stone fragment is crucial. The extent of the uncertainty of an analysis resulting from potential selection biases should not be underestimated. Thus, sampling should be considered as an important part of the processes of quality assurance and management. Errors made at this early stage of diagnosis finding will affect the analytical result and thus influence the clarification of the underlying pathomechanism. This can lead to an improper metaphylactic strategy potentially causing recurrent stone formation which otherwise would have been prevented. A decision scheme for analysis of urinary stones removed using endoscopic methods is suggested.

Microstructural diversity of gallstones revealed by spectral microanalyses and their association with hepatic parameters

BACKGROUND

Gallstones (GS) are formed as a result of impaired metabolic regulation and can be reflected in serum parameters. This study was focused on classifying GS based on spectral microanalysis and identifying the possible role of serum hepatic parameters on GS of different compositions.

METHODS

The study included a total of 126 GS from 80 consecutive patients who underwent cholecystectomy for GS diseases in a single center. The composition and microstructure of GS were analyzed using Fourier-transform infrared (FTIR) spectroscopy, field emission scanning electron microscopy (FESEM), and energy dispersive X-ray spectroscopy (EDS). The serum hepatic parameters were studied in order to establish a possible etiologic relationship with GS composition.

RESULTS

In the study group, the incidence of GS was higher in females 62 (77.5%) compared with males 18 (22.5%). The mean age was 42.81 ± 13.01 and 43.78 ± 14.4 years for female and male patients, respectively. Based on composition, the GS were assigned to four major groups: cholesterol, pigment, phosphate, and mixed stones. Mixed composition stones totally represented the majority 53 (66.3%), followed by pure cholesterol 23 (28.8%), pigment stones 2 (2.5%), and phosphate stones 2 (2.5%), respectively. Elemental composition revealed the presence of carbon (C), oxygen (O), calcium (Ca), and phosphorus (P) to be major elements along with traces of sodium (Na), magnesium (Mg), aluminum (Al), iron (Fe), copper (Cu), bromine (Br), manganese (Mn), and zinc (Zn). Among serum parameters, total bilirubin, direct bilirubin, indirect bilirubin, serum glutamic-oxaloacetic transaminase, and total protein were higher in patients with pigment GS than cholesterol GS.

CONCLUSIONS

Characterization of GS indicates that different types of stones have different characteristics in terms of microstructure, elemental composition, and distribution. Serum hepatic function test profiles showed an association with the compositions of GS.