3D Quantitative Chemical Imaging of Tissues by Spectromics

Toward cancer detection by label-free microscopic imaging in oncological surgery: Techniques, instrumentation and applications

This review examines the clinical application of label-free microscopy and spectroscopy, which are based on optical signals emitted by tissue components. Over the past three decades, a variety of techniques have been investigated with the aim of developing an in situ histopathology method that can rapidly and accurately identify tumor margins during surgical procedures. These techniques can be divided into two groups. One group encompasses techniques exploiting linear optical signals, and includes infrared and Raman microspectroscopy, and autofluorescence microscopy. The second group includes techniques based on nonlinear optical signals, including harmonic generation, coherent Raman scattering, and multiphoton autofluorescence microscopy. Some of these methods provide comparable information, while others are complementary. However, all of them have distinct advantages and disadvantages due to their inherent nature. The first part of the review provides an explanation of the underlying physics of the excitation mechanisms and a description of the instrumentation. It also covers endomicroscopy and data analysis, which are important for understanding the current limitations in implementing label-free techniques in clinical settings. The second part of the review describes the application of label-free microscopy imaging to improve oncological surgery with focus on brain tumors and selected gastrointestinal cancers, and provides a critical assessment of the current state of translation of these methods into clinical practice. Finally, the potential of confocal laser endomicroscopy for the acquisition of autofluorescence is discussed in the context of immediate clinical applications.

Complementary techniques for the reliable characterisation of tissue samples: A case study on pancreatic tumours analysed by means of X-ray fluorescence analysis and IR spectroscopy

An improvement in the reliability and comparability of tissue characterization results is crucial for enabling further progress in cancer detection and the assessment of therapeutic effects. This can only be achieved by integrating quantitative methods into well-established qualitative characterization routines. This case study presents a hybrid metrological approach for tissue characterisation including vibrational Fourier Transform InfraRed (FTIR) spectroscopy and traceable reference-free X-Ray Fluorescence analysis (XRF). Through the combination of spatially resolved qualitative molecular information with quantitative elemental concentrations an all-encompassing sample characterisation can be provided. The study was performed on tissue sections of syngeneic murine pancreatic ductal adenocarcinoma KPC (KrasG12D/+; Trp53R172H/+; Pdx-1-Cre) tumours ex-vivo. Sections from healthy pancreatic tissues, sham-exposed tumours and tumours subjected to low dose radiotherapy treatment (2 Gray and 6 Gray) were analysed using both methods. Additional sample integrity studies using Near Edge X-ray Absorption Fine Structure (NEXAFS) spectroscopy at the carbon and nitrogen K-edges were performed to assess the effect of sample aging and XRF investigations on the samples. Results showed an increase in the concentrations of elemental biomarkers, including S, K and amide I structures in malignant pancreatic tissue compared to healthy pancreatic tissue. The exposure of tumours to 6 Gy radiation decreases the levels of these elements towards a phenotype seen in the healthy pancreas. A protocol for hybrid investigations is presented, with emphasis on the sample preparation, minimizing the impact of consecutive applied methods on their measurands, and ensuring the compatibility and reliability of achieved results. The study demonstrates the cancer recognition capabilities, and the sensitivity for low dosage radiotherapy treatment monitoring for each method individually and assesses the potential of combining molecular fingerprinting with non-destructive quantitative elemental information for tissue sample characterization.

Vibrational spectroscopy and multiphoton microscopy for label-free visualization of nervous system degeneration and regeneration

Neurological disorders, including spinal cord injury, peripheral nerve injury, traumatic brain injury, and neurodegenerative diseases, pose significant challenges in terms of diagnosis, treatment, and understanding the underlying pathophysiological processes. Label-free multiphoton microscopy techniques, such as coherent Raman scattering, two-photon excited autofluorescence, and second and third harmonic generation microscopy, have emerged as powerful tools for visualizing nervous tissue with high resolution and without the need for exogenous labels. Coherent Raman scattering processes as well as third harmonic generation enable label-free visualization of myelin sheaths, while their combination with two-photon excited autofluorescence and second harmonic generation allows for a more comprehensive tissue visualization. They have shown promise in assessing the efficacy of therapeutic interventions and may have future applications in clinical diagnostics. In addition to multiphoton microscopy, vibrational spectroscopy methods such as infrared and Raman spectroscopy offer insights into the molecular signatures of injured nervous tissues and hold potential as diagnostic markers. This review summarizes the application of these label-free optical techniques in preclinical models and illustrates their potential in the diagnosis and treatment of neurological disorders with a special focus on injury, degeneration, and regeneration. Furthermore, it addresses current advancements and challenges for bridging the gap between research findings and their practical applications in a clinical setting.

Three-dimensional quantitative mass spectrometry imaging in complex system: From subcellular to whole organism

Mass spectrometry imaging (MSI) has been applied for label-free three-dimensional (3D) imaging from position array across the whole organism, which provides high-dimensional quantitative data of inorganic or organic compounds that may play an important role in the regulation of cellular signaling, including metals, metabolites, lipids, drugs, peptides, and proteins. While MSI is suitable for investigation of the spatial distribution of molecules, it has a limitation with visualization and quantification of multiple molecules. 3D-MSI, however, can be applied toward exploring metabolic pathway as well as the interactions of lipid-protein, protein-protein, and metal-protein in complex systems from subcellular to the whole organism through an untargeted methodology. In this review, we highlight the methods and applications of MS-based 3D imaging to address the complexity of molecular interaction from nano- to micrometer lateral resolution, with particular focus on: (a) common and hybrid 3D-MSI techniques; (b) quantitative MSI methodology, including the methods using a stable isotope labeling internal standard (SILIS) and SILIS-free approaches with tissue extinction coefficient or virtual calibration; (c) reconstruction of the 3D organ; (d) application of 3D-MSI for biomarker screening and environmental toxicological research. 3D-MSI quantitative analysis provides accurate spatial information and quantitative variation of biomolecules, which may be valuable for the exploration of the molecular mechanism of the disease progresses and toxicological assessment of environmental pollutants in the whole organism. Additionally, we also discuss the challenges and perspectives on the future of 3D quantitative MSI.

On 2D-FTIR-XRF microscopy - A step forward correlative tissue studies by infrared and hard X-ray radiation

Correlative Fourier Transform Infra-Red (FTIR) and hard X-Ray Fluorescence (XRF) microscopy studies of thin biological samples have recently evolved as complementary methods for biochemical fingerprinting of animal/human tissues. These are seen particularly useful for tracking the mechanisms of neurological diseases, i.e., in Alzheimer/Parkinson disease, in the brain where mishandling of trace metals (Fe, Cu, Zn) seems to be often associated with ongoing damage to molecular components via, among others, oxidative/reductive stress neurotoxicity. Despite substantial progress in state-of-the-art detection and data analysis methods, combined FTIR-XRF experiments have never benefited from correlation and co-localization analysis of molecular moieties and chemical elements, respectively. We here propose for the first time a completely novel data analysis pipeline, utilizing the idea of 2D correlation spectrometry for brain tissue analysis. In this paper, we utilized combined benchtop FTIR - synchrotron XRF mapping experiments on thin brain samples mounted on polypropylene membranes. By implementing our recently developed Multiple Linear Regression Multi-Reference (MLR-MR) algorithm, along with advanced image processing, artifact-free 2D FTIR-XRF spectra could be obtained by mitigating the impact of spectral artifacts, such as Etalon fringes and mild scattering Mie-like signatures, in the FTIR data. We demonstrated that the method is a powerful tool for co-localizing and correlating molecular arrangements and chemical elements (and vice versa) using visually attractive 2D correlograms. Moreover, the methods' applicability for fostering the identification of distinct (biological) materials, involving chemical elements and molecular arrangements, is also shown. Taken together, the 2D FTIR-XRF method opens up for new measures for in-situ investigating hidden complex biochemical correlations, and yet unraveled mechanisms in a biological sample. This step seems crucial for developing new strategies for facilitating the research on the interaction of metals/nonmetals with organic components. This is particularly important for enhancing our understanding of the diseases associated with metal/nonmetal mishandling.

Model-based correction algorithm for Fourier Transform infrared microscopy measurements of complex tissue-substrate systems

Model-based algorithms have recently attracted much attention for data pre-processing in tissue mapping and imaging by Fourier transform infrared micro-spectroscopy (FTIR). Their versatility, robustness and computational performance enabled the improvement of spectral quality by mitigating the impact of scattering and fringing in FTIR spectra of chemically homogeneous biological systems. However, to date, no comprehensive algorithm has been optimized and automated for large-area FTIR imaging of histologically complex tissue samples. Herein, for the first time, we propose a unique, integrated and fully-automated Multiple Linear Regression Multi-Reference (MLR-MR) method for correcting linear baseline effects due to diffuse scattering, for compensating substrate thickness inhomogeneity and accounting for sample chemical heterogeneity in FTIR images. In particular, the algorithm uses multiple-reference spectra for histologically heterogeneous biological samples. The performance of the procedure was demonstrated for FTIR imaging of chemically complex rat brain frontal cortex tissue samples, mounted onto Ultralene® films. The proposed MLR-MR correction algorithm allows the efficient retrieval of "pure" absorbance spectra and greatly improves the histological fidelity of FTIR imaging data, as compared with the one-reference approach. In addition, the MLR-MR algorithm here presented opens up the possibility for extracting information on substrate thickness variability, thus enabling the indirect evaluation of its topography. As a whole, the MLR-MR procedure can be easily extended to more complex systems for which Mie scattering effects must also be eliminated.

A Toolbox for Organelle Mechanobiology Research-Current Needs and Challenges

Mechanobiology studies from the last decades have brought significant insights into many domains of biological research, from development to cellular signaling. However, mechano-regulation of subcellular components, especially membranous organelles, are only beginning to be unraveled. In this paper, we take mitochondrial mechanobiology as an example to discuss recent advances and current technical challenges in this field. In addition, we discuss the needs for future toolbox development for mechanobiological research of intracellular organelles.

Imaging the Microprocesses in Biofilm Matrices

Biofilms, which are aggregates of microorganisms and extracellular matrices, widely colonize natural water bodies, wastewater treatment systems, and body tissues, and have vital roles in water purification, biofouling, and infectious diseases. Recently, multiple imaging modalities have been developed to visualize the morphological structure and material distribution within biofilms and to probe the microprocesses in biofilm matrices, including biofilm formation, transfer and metabolism of substrates, and cell-cell communication. These technologies have improved our understanding of biofilm control and the fates of substrates in biofilms. In this review, we describe the principles of various imaging techniques and discuss the advantages and limitations of each approach to characterizing microprocesses in biofilm matrices.

3D Digital Pathology for a Chemical-Functional Analysis of Glomeruli in Health and Pathology

Determining the filtration function and biochemical status of kidney at the single glomerulus level remains hardly accessible, even from biopsies. Here, we provide evidence that IR spectro-microscopy is a suitable method to account for the filtration capacity of individual glomeruli along with related physio-pathological condition. A ∼4 μm voxel resolution 3D IR image reconstruction is built from consecutive tissue sections, thus, providing a 3D IR spectrum matrix of an individual glomerulus. The filtration capacity of glomeruli was quantitatively determined after BaSO₄ perfusion, and additional chemical data could be used to determined oxidative stress effects and fibrosis, thus, combining functional and biochemical information from the same 3D IR spectrum matrix. This analytical approach was applied on mice with unilateral ureteral obstruction (UUO) inducing chronic kidney disease. Compared to the healthy condition, UUO induced a significant drop in glomeruli filtration capacity (-17 ± 8% at day 4 and -48 ± 14% at day 14) and volume (36 ± 10% at day 4 and 67 ± 13% at day 14), along a significant increase of oxidative stress (+61 ± 19% at day 4 and +84 ± 17% at day 14) and a change in the lipid-to-protein ratio (-8.2 ± 3.6% at day 4 and -18.1 ± 5.9% at day 14). Therefore, IR spectro-microscopy might be developed as a new 3D pathology resource for analyzing functional and biochemical parameters of glomeruli.