High precision mapping of kidney stones using μ-IR spectroscopy to determine urinary lithogenesis

Fast Nano-IR Hyperspectral Imaging Empowered by Large-Dataset-Free Miniaturized Spatial-Spectral Network

The emerging field of nanoscale infrared (nano-IR) offers label-free molecular contrast, yet its imaging speed is limited by point-by-point traverse acquisition of a three-dimensional (3D) data cube. Here, we develop a spatial-spectral network (SS-Net), a miniaturized deep-learning model, together with compressive sampling to accelerate the nano-IR imaging. The compressive sampling is performed in both the spatial and spectral domains to accelerate the imaging process. The SS-Net is trained to learn the mapping from small nano-IR image patches to the corresponding spectra. With this elaborated mapping strategy, the training can be finished quickly within several minutes using the subsampled data, eliminating the need for a large-labeled dataset of common deep learning methods. We also designed an efficient loss function, which incorporates the image and spectral similarity to enhance the training. We first validate the SS-Net on an open stimulated Raman-scattering dataset; the results exhibit the potential of 10-fold imaging speed improvement with state-of-the-art performance. We then demonstrate the versatility of this approach on atomic force microscopy infrared (AFM-IR) microscopy with 7-fold imaging speed improvement, even on nanoscale Fourier transform infrared (nano-FTIR) microscopy with up to 261.6 folds faster imaging speed. We further showcase the generalization of this method on AFM-force volume-based multiparametric nanoimaging. This method establishes a paradigm for rapid nano-IR imaging, opening new possibilities for cutting-edge research in materials, photonics, and beyond.

Quantitative analysis of calcium oxalate monohydrate and dihydrate for elucidating the formation mechanism of calcium oxalate kidney stones

We sought to identify and quantitatively analyze calcium oxalate (CaOx) kidney stones on the order of micrometers, with a focus on the quantitative identification of calcium oxalate monohydrate (COM) and dihydrate (COD). We performed Fourier transform infrared (FTIR) spectroscopy, powder X-ray diffraction (PXRD), and microfocus X-ray computed tomography measurements (microfocus X-ray CT) and compared their results. An extended analysis of the FTIR spectrum focusing on the 780 cm-1 peak made it possible to achieve a reliable analysis of the COM/COD ratio. We succeeded in the quantitative analysis of COM/COD in 50-μm2 areas by applying microscopic FTIR for thin sections of kidney stones, and by applying microfocus X-ray CT system for bulk samples. The analysis results based on the PXRD measurements with micro-sampling, the microscopic FTIR analysis of thin sections, and the microfocus X-ray CT system observation of a bulk kidney stone sample showed roughly consistent results, indicating that all three methods can be used complementarily. This quantitative analysis method evaluates the detailed CaOx composition on the preserved stone surface and provides information on the stone formation processes. This information clarifies where and which crystal phase nucleates, how the crystals grow, and how the transition from the metastable phase to the stable phase proceeds. The phase transition affects the growth rate and hardness of kidney stones and thus provides crucial clues to the kidney stone formation process.

Towards an understanding of the chemo-mechanical influences on kidney stone failure via the material point method

This paper explores the use of the meshfree computational mechanics method, the Material Point Method (MPM), to model the composition and damage of typical renal calculi, or kidney stones. Kidney stones are difficult entities to model due to their complex structure and failure behavior. Better understanding of how these stones behave when they are broken apart is a vital piece of knowledge to medical professionals whose aim is to remove these stone by breaking them within a patient’s body. While the properties of individual stones are varied, the common elements and proportions are used to generate synthetic stones that are then placed in a digital experiment to observe their failure patterns. First a more traditional engineering model of a Brazil test is used to create a tensile fracture within the center of these stones to observe the effect of stone consistency on failure behavior. Next a novel application of MPM is applied which relies on an ultrasonic wave being carried by surrounding fluid to model the ultrasonic treatment of stones commonly used by medical practitioners. This numerical modeling of Extracorporeal Shock Wave Lithotripsy (ESWL) reveals how these different stones failure in a more real-world situation and could be used to guide further research in this field for safer and more effective treatments.

Calcium oxalate kidney stones, where is the organic matter?: A synchrotron based infrared microspectroscopy study

Kidney stones are collections of microcrystals formed inside the kidneys, which affect 6% to 12% of the population worldwide, with an increasing recurrence (50%-72%) after the first episode. The most abundant type is calcium oxalate (66%), described as monohydrated (COM) and dihydrated (COD). An issue in their chemistry is the transformation process of the metastable specie (COD) into the stable one, which is chemically, and in appearance, monohydrated. Since the origin of these species is different, it is important to differentiate between the transformation stage (and what stabilize COD) to understand the physiopathology and prevent the patients' recurrence. This work focuses on the organic matter distribution along these nephroliths by synchrotron radiation-based infrared microspectroscopy. Differences in the asymmetric stretching of the aliphatic hydrocarbons suggest that lipids may participate in the stabilization of COD and as inhibitors of COM formation/development; however, the presence of proteins in the nucleus could indicate a promoting role.

Investigation of molecular mechanisms of experimental compounds in murine models of chronic allergic airways disease using synchrotron Fourier-transform infrared microspectroscopy

The ovalbumin-induced (OVA) chronic allergic airways murine model is a well-established model for investigating pre-clinical therapies for chronic allergic airways diseases, such as asthma. Here, we examined the effects of several experimental compounds with potential anti-asthmatic effects including resveratrol (RV), relaxin (RLN), l-sulforaphane (LSF), valproic acid (VPA), and trichostatin A (TSA) using both a prevention and reversal model of chronic allergic airways disease. We undertook a novel analytical approach using focal plane array (FPA) and synchrotron Fourier-transform infrared (S-FTIR) microspectroscopic techniques to provide new insights into the mechanisms of action of these experimental compounds. Apart from the typical biological effects, S-FTIR microspectroscopy was able to detect changes in nucleic acids and protein acetylation. Further, we validated the reduction in collagen deposition induced by each experimental compound evaluated. Although this has previously been observed with conventional histological methods, the S-FTIR technique has the advantage of allowing identification of the type of collagen present. More generally, our findings highlight the potential utility of S-FTIR and FPA-FTIR imaging techniques in enabling a better mechanistic understanding of novel asthma therapeutics.

Raman chemical imaging, a new tool in kidney stone structure analysis: Case-study and comparison to Fourier Transform Infrared spectroscopy

BACKGROUND AND OBJECTIVES

The kidney stone's structure might provide clinical information in addition to the stone composition. The Raman chemical imaging is a technology used for the production of two-dimension maps of the constituents' distribution in samples. We aimed at determining the use of Raman chemical imaging in urinary stone analysis.

MATERIAL AND METHODS

Fourteen calculi were analyzed by Raman chemical imaging using a confocal Raman microspectrophotometer. They were selected according to their heterogeneous composition and morphology. Raman chemical imaging was performed on the whole section of stones. Once acquired, the data were baseline corrected and analyzed by MCR-ALS. Results were then compared to the spectra obtained by Fourier Transform Infrared spectroscopy.

RESULTS

Raman chemical imaging succeeded in identifying almost all the chemical components of each sample, including monohydrate and dihydrate calcium oxalate, anhydrous and dihydrate uric acid, apatite, struvite, brushite, and rare chemicals like whitlockite, ammonium urate and drugs. However, proteins couldn't be detected because of the huge autofluorescence background and the small concentration of these poor Raman scatterers. Carbapatite and calcium oxalate were correctly detected even when they represented less than 5 percent of the whole stones. Moreover, Raman chemical imaging provided the distribution of components within the stones: nuclei were accurately identified, as well as thin layers of other components. Conversion of dihydrate to monohydrate calcium oxalate was correctly observed in the centre of one sample. The calcium oxalate monohydrate had different Raman spectra according to its localization.

CONCLUSION

Raman chemical imaging showed a good accuracy in comparison with infrared spectroscopy in identifying components of kidney stones. This analysis was also useful in determining the organization of components within stones, which help locating constituents in low quantity, such as nuclei. However, this analysis is time-consuming, making it more suitable for research studies rather than routine analysis.

Modern trends in biophotonics for clinical diagnosis and therapy to solve unmet clinical needs

This contribution covers recent original research papers in the biophotonics field. The content is organized into main techniques such as multiphoton microscopy, Raman spectroscopy, infrared spectroscopy, optical coherence tomography and photoacoustic tomography, and their applications in the context of fluid, cell, tissue and skin diagnostics. Special attention is paid to vascular and blood flow diagnostics, photothermal and photodynamic therapy, tissue therapy, cell characterization, and biosensors for biomarker detection.

Taking advantage of hyperspectral imaging classification of urinary stones against conventional infrared spectroscopy

The analysis of urinary stones is mandatory for the best management of the disease after the stone passage in order to prevent further stone episodes. Thus the use of an appropriate methodology for an individualized stone analysis becomes a key factor for giving the patient the most suitable treatment. A recently developed hyperspectral imaging methodology, based on pixel-to-pixel analysis of near-infrared spectral images, is compared to the reference technique in stone analysis, infrared (IR) spectroscopy. The developed classification model yields >90% correct classification rate when compared to IR and is able to precisely locate stone components within the structure of the stone with a 15 µm resolution. Due to the little sample pretreatment, low analysis time, good performance of the model, and the automation of the measurements, they become analyst independent; this methodology can be considered to become a routine analysis for clinical laboratories.