In-vivo Raman spectroscopy: from basics to applications

Hyperspectral and multispectral image processing for gross-level tumor detection in skin lesions: a systematic review

SIGNIFICANCE

Skin cancer is one of the most prevalent cancers worldwide. In the advent of medical digitization and telepathology, hyper/multispectral imaging (HMSI) allows for noninvasive, nonionizing tissue evaluation at a macroscopic level.

AIM

We aim to summarize proposed frameworks and recent trends in HMSI-based classification and segmentation of gross-level skin tissue.

APPROACH

A systematic review was performed, targeting HMSI-based systems for the classification and segmentation of skin lesions during gross pathology, including melanoma, pigmented lesions, and bruises. The review adhered to the 2020 Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. For eligible reports published from 2010 to 2020, trends in HMSI acquisition, preprocessing, and analysis were identified.

RESULTS

HMSI-based frameworks for skin tissue classification and segmentation vary greatly. Most reports implemented simple image processing or machine learning, due to small training datasets. Methodologies were evaluated on heavily curated datasets, with the majority targeting melanoma detection. The choice of preprocessing scheme influenced the performance of the system. Some form of dimension reduction is commonly applied to avoid redundancies that are inherent in HMSI systems.

CONCLUSIONS

To use HMSI for tumor margin detection in practice, the focus of system evaluation should shift toward the explainability and robustness of the decision-making process.

Classification of skin cancer using convolutional neural networks analysis of Raman spectra

BACKGROUND AND OBJECTIVE

Skin cancer is the most common malignancy in whites accounting for about one third of all cancers diagnosed per year. Portable Raman spectroscopy setups for skin cancer "optical biopsy" are utilized to detect tumors based on their spectral features caused by the comparative presence of different chemical components. However, low signal-to-noise ratio in such systems may prevent accurate tumors classification. Thus, there is a challenge to develop methods for efficient skin tumors classification.

METHODS

We compare the performance of convolutional neural networks and the projection on latent structures with discriminant analysis for discriminating skin cancer using the analysis of Raman spectra with a high autofluorescence background stimulated by a 785 nm laser. We have registered the spectra of 617 cases of skin neoplasms (615 patients, 70 melanomas, 122 basal cell carcinomas, 12 squamous cell carcinomas and 413 benign tumors) in vivo with a portable Raman setup and created classification models both for convolutional neural networks and projection on latent structures approaches. To check the classification models stability, a 10-fold cross-validation was performed for all created models. To avoid models overfitting, the data was divided into a training set (80% of spectral dataset) and a test set (20% of spectral dataset).

RESULTS

The results for different classification tasks demonstrate that the convolutional neural networks significantly (p<0.01) outperforms the projection on latent structures. For the convolutional neural networks implementation we obtained ROC AUCs of 0.96 (0.94 - 0.97; 95% CI), 0.90 (0.85-0.94; 95% CI), and 0.92 (0.87 - 0.97; 95% CI) for classifying a) malignant vs benign tumors, b) melanomas vs pigmented tumors and c) melanomas vs seborrheic keratosis respectively.

CONCLUSIONS

The performance of the convolutional neural networks classification of skin tumors based on Raman spectra analysis is higher or comparable to the accuracy provided by trained dermatologists. The increased accuracy with the convolutional neural networks implementation is due to a more precise accounting of low intensity Raman bands in the intense autofluorescence background. The achieved high performance of skin tumors classifications with convolutional neural networks analysis opens a possibility for wide implementation of Raman setups in clinical setting.

Towards Raman imaging of centimeter scale tissue areas for real-time opto-molecular visualization of tissue boundaries for clinical applications

Raman spectroscopy combined with augmented reality and mixed reality to reconstruct molecular information of tissue surface.

Raman spectroscopy: current applications in breast cancer diagnosis, challenges and future prospects

Despite significant improvements in the way breast cancer is managed and treated, it continues to persist as a leading cause of death worldwide. If detected and diagnosed early, when tumours are small and localised, there is a considerably higher chance of survival. However, current methods for detection and diagnosis lack the required sensitivity and specificity for identifying breast cancer at the asymptomatic or very early stages. Thus, there is a need to develop more rapid and reliable methods, capable of detecting disease earlier, for improved disease management and patient outcome. Raman spectroscopy is a non-destructive analytical technique that can rapidly provide highly specific information on the biochemical composition and molecular structure of samples. In cancer, it has the capacity to probe very early biochemical changes that accompany malignant transformation, even prior to the onset of morphological changes, to produce a fingerprint of disease. This review explores the application of Raman spectroscopy in breast cancer, including discussion on its capabilities in analysing both ex-vivo tissue and liquid biopsy samples, and its potential in vivo applications. The review also addresses current challenges and potential future uses of this technology in cancer research and translational clinical application.

Real-time molecular imaging of near-surface tissue using Raman spectroscopy

The steady progress in medical diagnosis and treatment of diseases largely hinges on the steady development and improvement of modern imaging modalities. Raman spectroscopy has attracted increasing attention for clinical applications as it is label-free, non-invasive, and delivers molecular fingerprinting information of a sample. In combination with fiber optic probes, it also allows easy access to different body parts of a patient. However, image acquisition with fiber optic probes is currently not possible. Here, we introduce a fiber optic probe-based Raman imaging system for the real-time molecular virtual reality data visualization of chemical boundaries on a computer screen and the physical world. The approach is developed around a computer vision-based positional tracking system in conjunction with photometric stereo and augmented and mixed chemical reality, enabling molecular imaging and direct visualization of molecular boundaries of three-dimensional surfaces. The proposed approach achieves a spatial resolution of 0.5 mm in the transverse plane and a topology resolution of 0.6 mm, with a spectral sampling frequency of 10 Hz, and can be used to image large tissue areas in a few minutes, making it highly suitable for clinical tissue-boundary demarcation. A variety of applications on biological samples, i.e., distribution of pharmaceutical compounds, brain-tumor phantom, and various types of sarcoma have been characterized, showing that the system enables rapid and intuitive assessment of molecular boundaries.

Raman Spectroscopy as a Neuromonitoring Tool in Traumatic Brain Injury: A Systematic Review and Clinical Perspectives

Traumatic brain injury (TBI) is a significant global health problem, for which no disease-modifying therapeutics are currently available to improve survival and outcomes. Current neuromonitoring modalities are unable to reflect the complex and changing pathophysiological processes of the acute changes that occur after TBI. Raman spectroscopy (RS) is a powerful, label-free, optical tool which can provide detailed biochemical data in vivo. A systematic review of the literature is presented of available evidence for the use of RS in TBI. Seven research studies met the inclusion/exclusion criteria with all studies being performed in pre-clinical models. None of the studies reported the in vivo application of RS, with spectral acquisition performed ex vivo and one performed in vitro. Four further studies were included that related to the use of RS in analogous brain injury models, and a further five utilised RS in ex vivo biofluid studies for diagnosis or monitoring of TBI. RS is identified as a potential means to identify injury severity and metabolic dysfunction which may hold translational value. In relation to the available evidence, the translational potentials and barriers are discussed. This systematic review supports the further translational development of RS in TBI to fully ascertain its potential for enhancing patient care.

Raman Spectroscopy: In Vivo Application for Bone Evaluation in Oral Reconstructive (Regenerative) Surgery

The aim of this study was to evaluate the quality of the bone, revealing the different phases for calcified tissues independent of the medical history of the patient in relation to periodontitis by means of in vivo Raman spectroscopy. Raman spectroscopy measurements were performed in vivo during surgery and then ex vivo for the harvested bone samples for the whole group of patients (ten patients). The specific peaks for the Raman spectrum were traced for reference compounds (e.g., calcium phosphates) and bone samples. The variation in the intensity of the spectrum in relation to the specific bone constituents’ concentrations reflects the bone quality and can be strongly related with patient medical status (before dental surgery and after a healing period). Moreover, bone sample fluorescence is related to collagen content, enabling a complete evaluation of bone quality including a “quasi-quantification” of the healing process similar to the bone augmentation procedure. A complete evaluation of the processed spectra offers quantitative/qualitative information on the condition of the bone tissue. We conclude that Raman spectroscopy can be considered a viable investigation method for an in vivo and quick bone quality assessment during oral and periodontal surgery.

Single-Cell Photothermal Analysis Induced by MoS2 Nanoparticles by Raman Spectroscopy

Two-dimensional nanomaterials, such as MoS2 nanosheets, have been attracting increasing attention in cancer diagnosis and treatment, thanks to their peculiar physical and chemical properties. Although the mechanisms which regulate the interaction between these nanomaterials and cells are not yet completely understood, many studies have proved their efficient use in the photothermal treatment of cancer, and the response to MoS2 nanosheets at the single-cell level is less investigated. Clearly, this information can help in shedding light on the subtle cellular mechanisms ruling the interaction of this 2D material with cells and, eventually, to its cytotoxicity. In this study, we use confocal micro-Raman spectroscopy to reconstruct the thermal map of single cells targeted with MoS2 under continuous laser irradiation. The experiment is performed by analyzing the water O-H stretching band around 3,400 cm−1 whose tetrahedral structure is sensitive to the molecular environment and temperature. Compared to fluorescence-based approaches, this Raman-based strategy for temperature measurement does not suffer fluorophore instability, which can be significant under continuous laser irradiation. We demonstrate that irradiation of human breast cancer MCF7 cells targeted with MoS2 nanosheets causes a relevant photothermal effect, which is particularly high in the presence of MoS2 nanosheet aggregates. Laser-induced heating is strongly localized near such particles which, in turn, tend to accumulate near the cytoplasmic membrane. Globally, our experimental outcomes are expected to be important for tuning the nanosheet fabrication process.

Structural determination of model phospholipid membranes by Raman spectroscopy: Laboratory experiment

In an upper-division interdisciplinary laboratory experiment, students use Raman spectroscopy to highlight how the overall structure and conformational order of lipid bilayers can be influenced by their individual phospholipid composition. Students prepare a supported lipid bilayer, as a model cell membrane, by spreading liposomes made of various phospholipids on a solid support. The characterization of phospholipid bilayers, a major component of cellular membranes, can advance our fundamental understanding of important biological phenomena, with significant implications in various fields including drug delivery and development. We use Raman spectroscopy as an analytical tool to investigate the structural and packing properties of model cell membranes. The spectral frequency, intensity, and line-width of lipid Raman bands are extremely sensitive to structural alterations. This experimental module effectively exposes students to the fundamentals of Raman spectroscopy and teaches students the importance of interdisciplinary education as they integrate concepts from chemical structure, molecular interactions, and analytical spectroscopic techniques to gain a more holistic understanding of biological membrane properties.

Raman Spectroscopy: A Personalized Decision-Making Tool on Clinicians' Hands for In Situ Cancer Diagnosis and Surgery Guidance

Accurate in situ diagnosis and optimal surgical removal of a malignancy constitute key elements in reducing cancer-related morbidity and mortality. In surgical oncology, the accurate discrimination between healthy and cancerous tissues is critical for the postoperative care of the patient. Conventional imaging techniques have attempted to serve as adjuvant tools for in situ biopsy and surgery guidance. However, no single imaging modality has been proven sufficient in terms of specificity, sensitivity, multiplexing capacity, spatial and temporal resolution. Moreover, most techniques are unable to provide information regarding the molecular tissue composition. In this review, we highlight the potential of Raman spectroscopy as a spectroscopic technique with high detection sensitivity and spatial resolution for distinguishing healthy from malignant margins in microscopic scale and in real time. A Raman spectrum constitutes an intrinsic "molecular finger-print" of the tissue and any biochemical alteration related to inflammatory or cancerous tissue state is reflected on its Raman spectral fingerprint. Nowadays, advanced Raman systems coupled with modern instrumentation devices and machine learning methods are entering the clinical arena as adjunct tools towards personalized and optimized efficacy in surgical oncology.

Application and Progress of Raman Spectroscopy in Male Reproductive System

Raman spectroscopy is a fast-developing, unmarked, non-invasive, non-destructive technique which allows for real-time scanning and sampling of biological samples in situ, reflecting the subtle biochemical composition alterations of tissues and cells through the variations of spectra. It has great potential to identify pathological tissue and provide intraoperative assistance in clinic. Raman spectroscopy has made many exciting achievements in the study of male reproductive system. In this review, we summarized literatures about the application and progress of Raman spectroscopy in male reproductive system from PubMed and Ovid databases, using MeSH terms associated to Raman spectroscopy, prostate, testis, seminal plasma and sperm. The existing challenges and development opportunities were also discussed and prospected.

Calibration Technique for Suppressing Residual Etalon Artifacts in Slit-Averaged Raman Spectroscopy

Back-illuminated charged-coupled device (BI-CCD) arrays increase quantum efficiency but also amplify etaloning, a multiplicative, wavelength-dependent fixed-pattern effect. When spectral data from hundreds of BI-CCD rows are combined, the averaged spectrum will generally appear etalon-free. This can mask substantial etaloning at the row level, even if the BI-CCD has been treated to suppress the effect. This paper compares two methods of etalon correction, one with simple averaging and one with row-by-row calibration using a fluorescence standard. Two BI-CCD arrays, both roughened by the supplier to reduce etaloning, were used to acquire Raman spectra of murine bone specimens. For one array, etaloning was the dominant source of noise under the exposure conditions chosen, even for the averaged spectrum across all rows; near-infrared-excited Raman peaks were noticeably affected. In this case, row-by-row calibration improved the spectral quality of the average spectrum. The other CCD's performance was shot-noise limited and therefore received no benefit from the extra calibration. The different results highlight the importance of checking for and correcting row-level fixed pattern when measuring weak Raman signals in the presence of a large fluorescence background.

Raman Studies on Surface-Imprinted Polymers to Distinguish the Polymer Surface, Imprints, and Different Bacteria

Molecularly imprinted polymers (MIPs) are widely used as robust biomimetic recognition layers in sensing devices targeting a wide variety of analytes including microorganisms such as bacteria. Assessment of imprinting success and selectivity toward the target is of great importance in MIP quality control. We generated Escherichia coli-imprinted poly(styrene-co-DVB) as a model system for bacteria-imprinted polymers via surface imprinting using a glass stamp with covalently immobilized E. coli. Confocal Raman Microscopy was successfully employed to visualize bacteria, imprints, and polymer and to distinguish them from each other. The method has proven highly feasible for assessing if imprinting had been successful. In addition, we developed a method for selectivity investigation of bacteria MIPs based on combining Confocal Raman Microscopy and Partial Least Squares Discriminant Analysis (PLS-DA). The Raman spectra of E. coli and Bacillus cereus were acquired on E. coli-imprinted poly(styrene-co-DVB) and used to establish a PLS-DA model for differentiating between the bacteria species. Model validation demonstrated a correct classification of 95% of Raman spectra, indicating sufficient accuracy of the model for future use in MIP selectivity studies. Simultaneous differentiation of 3 bacteria species (E. coli, B. cereus, and Lactococcus lactis) on E. coli-imprinted poly(styrene-co-DVB) proved more difficult, which might be due to the limited depth resolution of the confocal Raman microscope resulting in the presence of interfering signals from the polymer substrate. It might be possible to overcome this obstacle by selective enhancement of the Raman signals originating from bacteria surfaces, such as tip enhanced Raman spectroscopy.

Visible-light and near-infrared fluorescence and surface-enhanced Raman scattering point-of-care sensing and bio-imaging: a review

This review article deals with the concepts, principles and applications of visible-light and near-infrared (NIR) fluorescence and surface-enhanced Raman scattering (SERS) in in vitro point-of-care testing (POCT) and in vivo bio-imaging. It has discussed how to utilize the biological transparency windows to improve the penetration depth and signal-to-noise ratio, and how to use surface plasmon resonance (SPR) to amplify fluorescence and SERS signals. This article has highlighted some plasmonic fluorescence and SERS probes. It has also reviewed the design strategies of fluorescent and SERS sensors in the detection of metal ions, small molecules, proteins and nucleic acids. Particularly, it has provided perspectives on the integration of fluorescent and SERS sensors into microfluidic chips as lab-on-chips to realize point-of-care testing. It has also discussed the design of active microfluidic devices and non-paper- or paper-based lateral flow assays for in vitro diagnostics. In addition, this article has discussed the strategies to design in vivo NIR fluorescence and SERS bio-imaging platforms for monitoring physiological processes and disease progression in live cells and tissues. Moreover, it has highlighted the applications of POCT and bio-imaging in testing toxins, heavy metals, illicit drugs, cancers, traumatic brain injuries, and infectious diseases such as COVID-19, influenza, HIV and sepsis.

Advances in Surface Enhanced Raman Spectroscopy for in Vivo Imaging in Oncology

In the last two decades, the application of surface enhanced Raman scattering (SERS) nanoparticles for preclinical cancer imaging has attracted increasing attention. Raman imaging with SERS nanoparticles offers unparalleled sensitivity, providing a platform for molecular targeting, and granting multiplexed and multimodal imaging capabilities. Recent progress has been facilitated not only by the optimization of the SERS contrast agents themselves, but also by the developments in Raman imaging approaches and instrumentation. In this article, we review the principles of Raman scattering and SERS, present advances in Raman instrumentation specific to cancer imaging, and discuss the biological means of ensuring selective in vivo uptake of SERS contrast agents for targeted, multiplexed, and multimodal imaging applications. We offer our perspective on areas that must be addressed in order to facilitate the clinical translation of SERS contrast agents for in vivo imaging in oncology.

Micro-Lensed Negative-Curvature Fibre Probe for Raman Spectroscopy

We developed a novel miniature micro-lensed fibre probe for Raman spectroscopy. The fibre probe consists of a single negative-curvature fibre (NCF) and a spliced, cleaved, micro-lensed fibre cap. Using a single NCF, we minimized the Raman background generated from the silica and maintained the diameter of the probe at less than 0.5 mm. In addition, the cap provided fibre closure by blocking the sample from entering the hollow parts of the fibre, enabling the use of the probe in in vivo applications. Moreover, the micro-lensed cap offered an improved collection efficiency (1.5-times increase) compared to a cleaved end-cap. The sensing capabilities of the micro-lensed probe were demonstrated by measuring different concentrations of glucose in aqueous solutions.

Quantitative analysis of binary and ternary organo-mineral solid dispersions by Raman spectroscopy for robotic planetary exploration missions on Mars

The Mars 2020 and ExoMars 2022, rover-based missions are specifically dedicated to the search for evidence of life and will both utilise Raman spectrometers on the surface of Mars. Raman spectroscopy is indeed a valuable analytical technique for planetary exploration that enables in situ characterisation of rocks and soils collected directly from the surface or retrieved as cores and subsequently crushed when extracted from the subsurface with a drill. On Mars, the miniaturised spectrometers will interrogate ancient geological deposits, in order to try and identify hydrated or aqueously altered minerals and organic matter to assess the habitability of Mars. While the identification of relevant hydrous minerals and organic components is the primary analytical objective of the missions, quantifying their abundances would be of particular significance for interpreting past geological conditions (e.g. formation or alteration processes) and for ascertaining the putative presence of biosignatures. Therefore, we have developed quantitative models that enable the quantification of both mineral proportions from crushed mixtures of geological components and spiked mixtures containing organic analytes dispersed in mineral matrices. Based on data normalisation with appropriate standards (internal and external), we demonstrate that robust quantitative models can be (1) applied for solid dispersions of various complexities relevant to planetary exploration; and (2) applied to different Raman set-ups, including an instrument representative of the ExoMars Raman Laser Spectrometer. With important Raman-active minerals (calcite, gypsum, baryte, quartz), we demonstrate that using a correction factor F_ϕ2/ϕ1, based on the ratio of apparent Raman scattering coefficients, the relative proportion of minerals in binary mixtures can be accurately determined. Regarding the organics, evaluated in clay-rich sediments (Fe-smectite) and crushed rocks of coarse-grained fraction (>100μm), we establish calibration curves in the concentration range 2-20 wt% for non-resonant compounds (L-cysteine, phthalic acid, adenine) and even lower (<1 wt%) for pre-resonant anthracene. Despite large levels of heterogeneity, the Raman analyses of these solid dispersions verify that quantitative Raman analyses can be performed in the context of robotic exploration studies.

Developing an Algorithm for Discriminating Oral Cancerous and Normal Tissues Using Raman Spectroscopy

The aim of this study was to investigate the clinical potential of Raman spectroscopy (RS) in detecting oral squamous cell carcinoma (OSCC) in tumor and healthy tissues in surgical resection specimens during surgery. Raman experiments were performed on cryopreserved specimens from patients with OSCC. Univariate and multivariate analysis was performed based on the fingerprint region (700-1800 cm-1) of the Raman spectra. One hundred thirty-one ex-vivo Raman experiments were performed on 131 surgical resection specimens obtained from 67 patients. The principal component analysis (PCA) and partial least square (PLS) methods with linear discriminant analysis (LDA) were applied on an independent validation dataset. Both models were able to differentiate between the tissue types, but PLS-LDA showed 100% accuracy, sensitivity, and specificity. In this study, Raman measurements of fresh resection tissue specimens demonstrated that OSCC had significantly higher nucleic acid, protein, and several amino acid contents than adjacent healthy tissues. The specific spectral information obtained in this study can be used to develop an in vivo Raman spectroscopic method for the tumor-free resection boundary during surgery.

DNA Fingerprint Analysis of Raman Spectra Captures Global Genomic Alterations in Imatinib-Resistant Chronic Myeloid Leukemia: A Potential Single Assay for Screening Imatinib Resistance

Monitoring the development of resistance to the tyrosine kinase inhibitor (TKI) imatinib in chronic myeloid leukemia (CML) patients in the initial chronic phase (CP) is crucial for limiting the progression of unresponsive patients to terminal phase of blast crisis (BC). This study for the first time demonstrates the potential of Raman spectroscopy to sense the resistant phenotype. Currently recommended resistance screening strategy include detection of BCR-ABL1 transcripts, kinase domain mutations, complex chromosomal abnormalities and BCR-ABL1 gene amplification. The techniques used for these tests are expensive, technologically demanding and have limited availability in resource-poor countries. In India, this could be a reason for more patients reporting to clinics with advanced disease. A single method which can identify resistant cells irrespective of the underlying mechanism would be a practical screening strategy. During our analysis of imatinib-sensitive and -resistant K562 cells, by array comparative genomic hybridization (aCGH), copy number variations specific to resistant cells were detected. aCGH is technologically demanding, expensive and therefore not suitable to serve as a single economic test. We therefore explored whether DNA finger-print analysis of Raman hyperspectral data could capture these alterations in the genome, and demonstrated that it could indeed segregate imatinib-sensitive and -resistant cells. Raman spectroscopy, due to availability of portable instruments, ease of spectrum acquisition and possibility of centralized analysis of transmitted data, qualifies as a preliminary screening tool in resource-poor countries for imatinib resistance in CML. This study provides a proof of principle for a single assay for monitoring resistance to imatinib, available for scrutiny in clinics.

Looking for a perfect match: multimodal combinations of Raman spectroscopy for biomedical applications

Raman spectroscopy has shown very promising results in medical diagnostics by providing label-free and highly specific molecular information of pathological tissue ex vivo and in vivo. Nevertheless, the high specificity of Raman spectroscopy comes at a price, i.e., low acquisition rate, no direct access to depth information, and limited sampling areas. However, a similar case regarding advantages and disadvantages can also be made for other highly regarded optical modalities, such as optical coherence tomography, autofluorescence imaging and fluorescence spectroscopy, fluorescence lifetime microscopy, second-harmonic generation, and others. While in these modalities the acquisition speed is significantly higher, they have no or only limited molecular specificity and are only sensitive to a small group of molecules. It can be safely stated that a single modality provides only a limited view on a specific aspect of a biological specimen and cannot assess the entire complexity of a sample. To solve this issue, multimodal optical systems, which combine different optical modalities tailored to a particular need, become more and more common in translational research and will be indispensable diagnostic tools in clinical pathology in the near future. These systems can assess different and partially complementary aspects of a sample and provide a distinct set of independent biomarkers. Here, we want to give an overview on the development of multimodal systems that use RS in combination with other optical modalities to improve the diagnostic performance.

Bimodal multispectral imaging system with cloud-based machine learning algorithm for real-time screening and detection of oral potentially malignant lesions and biopsy guidance

SIGNIFICANCE

Screening and early detection of oral potentially malignant lesions (OPMLs) are of great significance in reducing the mortality rates associated with head and neck malignancies. Intra-oral multispectral optical imaging of tissues in conjunction with cloud-based machine learning (CBML) can be used to detect oral precancers at the point-of-care (POC) and guide the clinician to the most malignant site for biopsy.

AIM

Develop a bimodal multispectral imaging system (BMIS) combining tissue autofluorescence and diffuse reflectance (DR) for mapping changes in oxygenated hemoglobin (HbO2) absorption in the oral mucosa, quantifying tissue abnormalities, and guiding biopsies.

APPROACH

The hand-held widefield BMIS consisting of LEDs emitting at 405, 545, 575, and 610 nm, 5MPx monochrome camera, and proprietary Windows-based software was developed for image capture, processing, and analytics. The DR image ratio (R610/R545) was compared with pathologic classification to develop a CBML algorithm for real-time assessment of tissue status at the POC.

RESULTS

Sensitivity of 97.5% and specificity of 92.5% were achieved for discrimination of OPML from patient normal in 40 sites, whereas 82% sensitivity and 96.6% specificity were obtained for discrimination of abnormal (OPML + SCC) in 89 sites. Site-specific algorithms derived for buccal mucosa (27 sites) showed improved sensitivity and specificity of 96.3% for discrimination of OPML from normal.

CONCLUSIONS

Assessment of oral cancer risk is possible by mapping of HbO2 absorption in tissues, and the BMIS system developed appears to be suitable for biopsy guidance and early detection of oral cancers.

Nanograting-Enhanced Optical Fibers for Visible and Infrared Light Collection at Large Input Angles

The efficient incoupling of light into particular fibers at large angles is essential for a multitude of applications; however, this is difficult to achieve with commonly used fibers due to low numerical aperture. Here, we demonstrate that commonly used optical fibers functionalized with arrays of metallic nanodots show substantially improved large-angle light-collection performances at multiple wavelengths. In particular, we show that at visible wavelengths, higher diffraction orders contribute significantly to the light-coupling efficiency, independent of the incident polarization, with a dominant excitation of the fundamental mode. The experimental observation is confirmed by an analytical model, which directly suggests further improvement in incoupling efficiency through the use of powerful nanostructures such as metasurface or dielectric gratings. Therefore, our concept paves the way for high-performance fiber-based optical devices and is particularly relevant within the context of endoscopic-type applications in life science and light collection within quantum technology.

Bioreactor design and validation for manufacturing strategies in tissue engineering

The fields of regenerative medicine and tissue engineering offer new therapeutic options to restore, maintain or improve tissue function following disease or injury. To maximize the biological function of a tissue-engineered clinical product, specific conditions must be maintained within a bioreactor to allow the maturation of the product in preparation for implantation. Specifically, the bioreactor should be designed to mimic the mechanical, electrochemical and biochemical environment that the product will be exposed to in vivo. Real-time monitoring of the functional capacity of tissue-engineered products during manufacturing is a critical component of the quality management process. The present review provides a brief overview of bioreactor engineering considerations. In addition, strategies for bioreactor automation, in-line product monitoring and quality assurance are discussed.

SP, N. M, Barik AK, Pai KM, Unnikrishnan VK, George SD, Kartha VB, Chidangil S. Photonics of human saliva: potential optical methods for the screening of abnormal health conditions and infections

Human saliva can be treated as a pool of biological markers able to reflect on the state of personal health. Recent years have witnessed an increase in the use of optical devices for the analysis of body fluids. Several groups have carried out studies investigating the potential of saliva as a non-invasive and reliable clinical specimen for use in medical diagnostics. This brief review aims to highlight the optical technologies, mainly surface plasmon resonance (SPR), Raman, and Fourier transform infrared (FTIR) spectroscopy, which are being used for the probing of saliva for diverse biomedical applications. Advances in bio photonics offer the promise of unambiguous, objective and fast detection of abnormal health conditions and viral infections (such as COVID-19) from the analysis of saliva.

Morpho-molecular signal correlation between optical coherence tomography and Raman spectroscopy for superior image interpretation and clinical diagnosis

The combination of manifold optical imaging modalities resulting in multimodal optical systems allows to discover a larger number of biomarkers than using a single modality. The goal of multimodal imaging systems is to increase the diagnostic performance through the combination of complementary modalities, e.g. optical coherence tomography (OCT) and Raman spectroscopy (RS). The physical signal origins of OCT and RS are distinctly different, i.e. in OCT it is elastic back scattering of photons, due to a change in refractive index, while in RS it is the inelastic scattering between photons and molecules. Despite those diverse characteristics both modalities are also linked via scattering properties and molecular composition of tissue. Here, we investigate for the first time the relation of co-registered OCT and RS signals of human bladder tissue, to demonstrate that the signals of these complementary modalities are inherently intertwined, enabling a direct but more importantly improved interpretation and better understanding of the other modality. This work demonstrates that the benefit for using two complementary imaging approaches is, not only the increased diagnostic value, but the increased information and better understanding of the signal origins of both modalities. This evaluation confirms the advantages for using multimodal imaging systems and also paves the way for significant further improved understanding and clinically interpretation of both modalities in the future.

Raman Spectroscopic Assessment of Myocardial Viability in Langendorff-Perfused Ischemic Rat Hearts

Spontaneous Raman spectroscopy, which senses changes in cellular contents of reduced cytochrome c, could be a powerful tool for label-free evaluation of ischemic hearts. However, undetermined is whether it is applicable to evaluation of myocardial viability in ischemic hearts. To address this issue, we investigated sequential changes in Raman spectra of the subepicardial myocardium in the Langendorff-perfused rat heart before and during ligation of the left coronary artery and its subsequent release and re-ligation. Under 532-nm wavelength excitation, the Raman peak intensity of reduced cytochrome c at 747 cm^-1 increased quickly after the coronary ligation, and reached a quasi-steady state within 30 min. Subsequent reperfusion of the heart after a short-term (30-min) ligation that simulates reversible conditions resulted in quick recovery of the peak intensity to the baseline. Further re-ligation resulted in resurgence of the peak intensity to nearly the identical value to the first ischemia value. In contrast, reperfusion after prolonged (120-min) ligation that assumes irreversible states resulted in incomplete recovery of the peak intensity, and re-ligation resulted in inadequate resurgence. Electron microscopic observations confirmed the spectral findings. Together, the Raman spectroscopic measurement for cytochrome c could be applicable to evaluation of viability of the ischemic myocardium without labeling.

Dual-wavelength wide area illumination Raman difference spectroscopy for remote detection of chemicals

Remote Raman instruments have become powerful analytical tools in some special environments. However, ambient daylight is the main limitation in the data acquisition process. To suppress daylight background interference and obtain a high signal-to-background ratio (SBR), we develop a dual-wavelength wide area illumination Raman difference spectroscopy (WAIRDS) system for daytime remote detection. In the WAIRDS system, a wide area illumination scheme and shifted-excitation Raman difference spectroscopy method are used to improve the reliability of collected Raman spectra. Measurements of polystyrene indicate that the WAIRDS system can be operated to obtain background-free Raman spectra under different levels of daylight background interference. The remote results show that the improvement in SBR is about three- to fivefold, and the system can work at distances of up to 9.2 m on a sunny afternoon. Moreover, to be close to the actual detection, the system is used for mineral and explosive raw material detection during daytime measurement. Measurements show that the WAIRDS system will be a useful tool for many remote applications in the future.

Optical Biomarkers for the Diagnosis of Osteoarthritis through Raman Spectroscopy: Radiological and Biochemical Validation Using Ex Vivo Human Cartilage Samples

Osteoarthritis (OA) is the most common rheumatic disease, characterized by progressive articular cartilage degradation. Raman spectroscopy (RS) has been recently proposed as a label-free tool to detect molecular changes in musculoskeletal tissues. We used cartilage samples derived from human femoral heads to perform an ex vivo study of different Raman signals and ratios, related to major and minor molecular components of articular cartilage, hereby proposed as candidate optical biomarkers for OA. Validation was performed against the radiological Kellgren-Lawrence (K-L) grading system, as a gold standard, and cross-validated against sulfated glycosaminoglycans (sGAGs) and total collagens (Hyp) biochemical contents. Our results showed a significant decrease in sGAGs (SGAGs, A1063 cm^-1/A1004 cm^-1) and proteoglycans (PGs, A1375 cm^-1/A1004 cm^-1) and a significant increase in collagen disorganization (ColD/F, A1245 cm^-1/A1270 cm^-1), with OA severity. These were correlated with sGAGs or Hyp contents, respectively. Moreover, the SGAGs/HA ratio (A1063 cm^-1/A960 cm^-1), representing a functional matrix, rich in proteoglycans, to a mineralized matrix-hydroxyapatite (HA), was significantly lower in OA cartilage (K-L I vs. III-IV, p < 0.05), whilst the mineralized to collagenous matrix ratio (HA/Col, A960 cm^-1/A920 cm^-1) increased, being correlated with K-L. OA samples showed signs of tissue mineralization, supported by the presence of calcium crystals-related signals, such as phosphate, carbonate, and calcium pyrophosphate dihydrate (MGP, A960 cm^-1/A1004 cm^-1, MGC, A1070 cm^-1/A1004 cm^-1 and A1050 cm^-1/A1004 cm^-1). Finally, we observed an increase in lipids ratio (IL, A1450 cm^-1/A1670 cm^-1) with OA severity. As a conclusion, we have described the molecular fingerprint of hip cartilage, validating a panel of optical biomarkers and the potential of RS as a complementary diagnostic tool for OA.

Nondestructive molecular imaging by Raman spectroscopy vs. marker detection by MALDI IMS for an early diagnosis of HCC

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths worldwide with a steadily increasing mortality rate. Fast diagnosis at early stages of HCC is of key importance for the improvement of patient survival rates. In this regard, we combined two imaging techniques with high potential for HCC diagnosis in order to improve the prediction of liver cancer. In detail, Raman spectroscopic imaging and matrix-assisted laser desorption ionization imaging mass spectrometry (MALDI IMS) were applied for the diagnosis of 36 HCC tissue samples. The data were analyzed using multivariate methods, and the results revealed that Raman spectroscopy alone showed a good capability for HCC tumor identification (sensitivity of 88% and specificity of 80%), which could not be improved by combining the Raman data with MALDI IMS. In addition, it could be shown that the two methods in combination can differentiate between well-, moderately- and poorly-differentiated HCC using a linear classification model. MALDI IMS not only classified the HCC grades with a sensitivity of 100% and a specificity of 80%, but also showed significant differences in the expression of glycerophospholipids and fatty acyls during HCC differentiation. Furthermore, important differences in the protein, lipid and collagen compositions of differentiated HCC were detected using the model coefficients of a Raman based classification model. Both Raman and MALDI IMS, as well as their combination showed high potential for resolving concrete questions in liver cancer diagnosis.

Combined negative dielectrophoresis with a flexible SERS platform as a novel strategy for rapid detection and identification of bacteria

Surface-enhanced Raman spectroscopy (SERS) is a vibrational method successfully applied in analytical chemistry, molecular biology and medical diagnostics. In this article, we demonstrate the combination of the negative dielectrophoretic (nDEP) phenomenon and a flexible surface-enhanced Raman platform for quick isolation (3 min), concentration and label-free identification of bacteria. The platform ensures a strong enhancement factor, high stability and reproducibility for the SERS response of analyzed samples. By introducing radial dielectrophoretic forces directed at the SERS platform, we can efficiently execute bacterial cell separation, concentration and deposition onto the SERS-active surface, which simultaneously works as a counter electrode and thus enables such hybrid DEP-SERS device vibration-based detection. Additionally, we show the ability of our DEP-SERS system to perform rapid, cultivation-free, direct detection of bacteria in urine and apple juice samples. The device provides new opportunities for the detection of pathogens.

Raman spectroscopic study of cervical precancerous lesions and cervical cancer

Early detection of cervical lesions, accurate diagnosis of cervical lesions, and timely and effective therapy can effectively avoid the occurrence of cervical cancer or improve the survival rate of patients. In this paper, the spectra of tissue sections of cervical inflammation (n = 60), CIN (cervical intraepithelial neoplasia) I (n = 30), CIN II (n = 30), CIN III (n = 30), cervical squamous cell carcinoma (n = 30), and cervical adenocarcinoma (n = 30) were collected by a confocal Raman micro-spectrometer (LabRAM HR Evolution, Horiba France SAS, Villeneuve d’Ascq, France). The Raman spectra of six kinds of cervical tissues were analyzed, the dominant Raman peaks of different kinds of tissues were summarized, and the differences in chemical composition between the six tissue samples were compared. An independent sample t test (p ≤ 0.05) was used to analyze the difference of average relative intensity of Raman spectra of six types of cervical tissues. The difference of relative intensity of Raman spectra of six kinds of tissues can reflect the difference of biochemical components in six kinds of tissues and the characteristic of biochemical components in different kinds of tissues. The classification models of cervical inflammation, CIN I, CIN II, CIN III, cervical squamous cell carcinoma, and cervical adenocarcinoma were established by using a support vector machine (SVM) algorithm. Six types of cervical tissues were classified and identified with an overall diagnostic accuracy of 85.7%. This study laid a foundation for the application of Raman spectroscopy in the clinical diagnosis of cervical precancerous lesions and cervical cancer.

The search for a unique Raman signature of amyloid-beta plaques in human brain tissue from Alzheimer's disease patients

Definite Alzheimer's disease (AD) diagnosis is commonly done on ex vivo brain tissue using immuno-histochemical staining to visualize amyloid-beta (Aβ) aggregates, also known as Aβ plaques. Raman spectroscopy has shown its potential for non-invasive and label-free determination of bio-molecular compositions, aiding the post-mortem diagnosis of pathological tissue. Here, we investigated whether conventional Raman spectroscopy could be used for the detection of amyloid beta deposits in fixed, ex vivo human brain tissue, taken from the frontal cortex region. We examined the spectra and spectral maps of three severe AD cases and two healthy control cases and compared their spectral outcome among each other as well as to recent results in the literature obtained with various spectroscopic techniques. After hyperspectral Raman mapping, Aβ plaques were visualized using Thioflavin-S staining on the exact same tissue sections. As a result, we show that tiny diffuse or tangled-like morphological structures, visible under microscopic conditions on unstained tissue and often but erroneously assumed to be deposits of Aβ, are instead usually an aggregation of highly auto-fluorescent lipofuscin granulates without any, or limited, plaque or plaque-like association. The occurrence of these auto-fluorescent particles is equally distributed in both AD and healthy control cases. Therefore, they cannot be used as possible criteria for Alzheimer's disease diagnosis. Furthermore, a unique plaque-specific/Aβ spectrum could not be determined even after possible spectral interferences were carefully removed.

Morpho-molecular ex vivo detection and grading of non-muscle-invasive bladder cancer using forward imaging probe based multimodal optical coherence tomography and Raman spectroscopy

Non-muscle-invasive bladder cancer affects millions of people worldwide, resulting in significant discomfort to the patient and potential death. Today, cystoscopy is the gold standard for bladder cancer assessment, using white light endoscopy to detect tumor suspected lesion areas, followed by resection of these areas and subsequent histopathological evaluation. Not only does the pathological examination take days, but due to the invasive nature, the performed biopsy can result in significant harm to the patient. Nowadays, optical modalities, such as optical coherence tomography (OCT) and Raman spectroscopy (RS), have proven to detect cancer in real time and can provide more detailed clinical information of a lesion, e.g. its penetration depth (stage) and the differentiation of the cells (grade). In this paper, we present an ex vivo study performed with a combined piezoelectric tube-based OCT-probe and fiber optic RS-probe imaging system that allows large field-of-view imaging of bladder biopsies, using both modalities and co-registered visualization, detection and grading of cancerous bladder lesions. In the present study, 119 examined biopsies were characterized, showing that fiber-optic based OCT provides a sensitivity of 78% and a specificity of 69% for the detection of non-muscle-invasive bladder cancer, while RS, on the other hand, provides a sensitivity of 81% and a specificity of 61% for the grading of low- and high-grade tissues. Moreover, the study shows that a piezoelectric tube-based OCT probe can have significant endurance, suitable for future long-lasting in vivo applications. These results also indicate that combined OCT and RS fiber probe-based characterization offers an exciting possibility for label-free and morpho-chemical optical biopsies for bladder cancer diagnostics.

Novel Quantitative Analysis Using Optical Imaging (VELscope) and Spectroscopy (Raman) Techniques for Oral Cancer Detection

In this study, we developed a novel quantitative analysis method to enhance the detection capability for oral cancer screening. We combined two different optical techniques, a light-based detection technique (visually enhanced lesion scope) and a vibrational spectroscopic technique (Raman spectroscopy). Materials and methods: Thirty-five oral cancer patients who went through surgery were enrolled. Thirty-five cancer lesions and thirty-five control samples with normal oral mucosa (adjacent to the cancer lesion) were analyzed. Thirty-five autofluorescence images and 70 Raman spectra were taken from 35 cancer and 35 control group cryopreserved samples. The normalized intensity and heterogeneity of the 70 regions of interest (ROIs) were calculated along with 70 averaged Raman spectra. Linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) were used with principal component analysis (PCA) to differentiate the cancer and control groups (normal). The classifications rates were validated using two different validation methods, leave-one-out cross-validation (LOOCV) and k-fold cross-validation. Results: The cryopreserved normal and tumor tissues were differentiated using the PCA-LDA and PCA-QDA models. The PCA-LDA of Raman spectroscopy (RS) had 82.9% accuracy, 80% sensitivity, and 85.7% specificity, while ROIs on the autofluorescence images were differentiated with 90% accuracy, 100% sensitivity, and 80% specificity. The combination of two optical techniques differentiated cancer and normal group with 97.14% accuracy, 100% sensitivity, and 94.3% specificity. Conclusion: In this study, we combined the data of two different optical techniques. Furthermore, PCA-LDA and PCA-QDA quantitative analysis models were used to differentiate tumor and normal groups, creating a complementary pathway for efficient tumor diagnosis. The error rates of RS and VELcope analysis were 17.10% and 10%, respectively, which was reduced to 3% when the two optical techniques were combined.

Development and evaluation of a hand-held fiber-optic Raman probe with an integrated autofocus unit

Current implementations of fiber-optic Raman spectroscopy probes are frequently based on non-contact probes with a fixed focus and thus and have to precisely maintain the probe-to-sample distance to ensure a sufficient signal collection. We propose and experimentally demonstrate a novel hand-held fiber-optic Raman probe design, which is based on a liquid lens autofocusing unit, combined with a distance sensor and an in-house developed algorithm to precisely determine the probe-to-sample distance. The reported probe significantly improves the signal stability even for hand-held operation, while reducing distance-dependent artifacts for the acquisition of Raman spectra and can improve the acquisition of Raman spectra in a variety of applications.

Experimental validation of a spectroscopic Monte Carlo light transport simulation technique and Raman scattering depth sensing analysis in biological tissue

SIGNIFICANCE

Raman spectroscopy (RS) applied to surgical guidance is attracting attention among scientists in biomedical optics. Offering a computational platform for studying depth-resolved RS and probing molecular specificity of different tissue layers is of crucial importance to increase the precision of these techniques and facilitate their clinical adoption.

AIM

The aim of this work was to present a rigorous analysis of inelastic scattering depth sampling and elucidate the relationship between sensing depth of the Raman effect and optical properties of the tissue under interrogation.

APPROACH

A new Monte Carlo (MC) package was developed to simulate absorption, fluorescence, elastic, and inelastic scattering of light in tissue. The validity of the MC algorithm was demonstrated by comparison with experimental Raman spectra in phantoms of known optical properties using nylon and polydimethylsiloxane as Raman-active compounds. A series of MC simulations were performed to study the effects of optical properties on Raman sensing depth for an imaging geometry consistent with single-point detection using a handheld fiber optics probe system.

RESULTS

The MC code was used to estimate the Raman sensing depth of a handheld fiber optics system. For absorption and reduced scattering coefficients of 0.001 and 1  mm  -  1, the sensing depth varied from 105 to 225  μm for a range of Raman probabilities from 10  -  6 to 10  -  3. Further, for a realistic Raman probability of 10  -  6, the sensing depth ranged between 10 and 600  μm for the range of absorption coefficients 0.001 to 1.4  mm  -  1 and reduced scattering coefficients of 0.5 to 30  mm  -  1.

CONCLUSIONS

A spectroscopic MC light transport simulation platform was developed and validated against experimental measurements in tissue phantoms and used to predict depth sensing in tissue. It is hoped that the current package and reported results provide the research community with an effective simulating tool to improve the development of clinical applications of RS.

Dual-modality optical coherence tomography and frequency-domain fluorescence lifetime imaging microscope system for intravascular imaging

SIGNIFICANCE

Detailed biochemical and morphological imaging of the plaque burdened coronary arteries holds the promise of improved understanding of atherosclerosis plaque development, ultimately leading to better diagnostics and therapies.

AIM

Development of a dual-modality intravascular catheter supporting swept-source optical coherence tomography (OCT) and frequency-domain fluorescence lifetime imaging (FD-FLIM) of endogenous fluorophores with UV excitation.

APPROACH

We instituted a refined approach to endoscope development that combines simulation in a commercial ray tracing program, fabrication, and a measurement method for optimizing ball-lens performance. With this approach, we designed and developed a dual-modality catheter endoscope based on a double-clad fiber supporting OCT through the core and fluorescence collection through the first cladding. We varied the relative percent of UV excitation launched into the core and first cladding to explore the potential resolution improvement for FD-FLIM. The developed catheter endoscope was optically characterized, including measurement of spatial resolution and fluorescent lifetimes of standard fluorophores. Finally, the system was demonstrated on fresh ex vivo human coronary arteries.

RESULTS

The developed endoscope was shown to have optical performance similar to predictions derived from the simulation approach. The FLIM resolution can be improved by over a factor of 4 by primarily illuminating through the core rather than the first cladding. However, time-dependent solarization losses need to be considered when choosing the relative percentage. We ultimately chose to illuminate with 7% of the power transmitting through the core. The resulting catheter endoscope had 40-μm lateral resolution for OCT and <100  μm lateral resolution for FD-FLIM. Images of ex vivo coronary arteries are consistent with expectations based on histopathology.

CONCLUSIONS

The results demonstrate that our approach for endoscope simulation produces reliable predictions of endoscope performance. Simulation results guided our development of a multimodal OCT/FD-FLIM catheter imaging system for investigating atherosclerosis in coronary arteries.

Special Section Guest Editorial: Fluorescence Lifetime Imaging, Optical Micromechanics, and Beyond

The editorial introduces the Journal of Biomedical Optics Special Section on Selected Topics in Biophotonics: Fluorescence Lifetime Imaging and Optical Micromechanics.

Image-guided tumor surgery: The emerging role of nanotechnology

Surgical resection is a mainstay treatment for solid tumors. Yet, methods to distinguish malignant from healthy tissue are primarily limited to tactile and visual cues as well as the surgeon's experience. As a result, there is a possibility that a positive surgical margin (PSM) or the presence of residual tumor left behind after resection may occur. It is well-documented that PSMs can negatively impact treatment outcomes and survival, as well as pose an economic burden. Therefore, surgical tumor imaging techniques have emerged as a promising method to decrease PSM rates. Nanoparticles (NPs) have unique characteristics to serve as optical contrast agents during image-guided surgery (IGS). Recently, there has been tremendous growth in the volume and types of NPs used for IGS, including clinical trials. Herein, we describe the most recent contributions of nanotechnology for surgical tumor identification. This article is categorized under: Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease Implantable Materials and Surgical Technologies > Nanoscale Tools and Techniques in Surgery Diagnostic Tools > in vivo Nanodiagnostics and Imaging.

Raman spectroscopy and neuroscience: from fundamental understanding to disease diagnostics and imaging

Neuroscience would directly benefit from more effective detection techniques, leading to earlier diagnosis of disease. The specificity of Raman spectroscopy is unparalleled, given that a molecular fingerprint is attained for each species. It also allows for label-free detection with relatively inexpensive instrumentation, minimal sample preparation, and rapid sample analysis. This review summarizes Raman spectroscopy-based techniques that have been used to advance the field of neuroscience in recent years.

Feature engineering applied to intraoperative in vivo Raman spectroscopy sheds light on molecular processes in brain cancer: a retrospective study of 65 patients

Raman spectroscopy is a promising tool for neurosurgical guidance and cancer research. Quantitative analysis of the Raman signal from living tissues is, however, limited. Their molecular composition is convoluted and influenced by clinical factors, and access to data is limited. To ensure acceptance of this technology by clinicians and cancer scientists, we need to adapt the analytical methods to more closely model the Raman-generating process. Our objective is to use feature engineering to develop a new representation for spectral data specifically tailored for brain diagnosis that improves interpretability of the Raman signal while retaining enough information to accurately predict tissue content. The method consists of band fitting of Raman bands which consistently appear in the brain Raman literature, and the generation of new features representing the pairwise interaction between bands and the interaction between bands and patient age. Our technique was applied to a dataset of 547 in situ Raman spectra from 65 patients undergoing glioma resection. It showed superior predictive capacities to a principal component analysis dimensionality reduction. After analysis through a Bayesian framework, we were able to identify the oncogenic processes that characterize glioma: increased nucleic acid content, overexpression of type IV collagen and shift in the primary metabolic engine. Our results demonstrate how this mathematical transformation of the Raman signal allows the first biological, statistically robust analysis of in vivo Raman spectra from brain tissue.

Nanomedicine and Immunotherapy: A Step Further towards Precision Medicine for Glioblastoma

Owing to the advancement of technology combined with our deeper knowledge of human nature and diseases, we are able to move towards precision medicine, where patients are treated at the individual level in concordance with their genetic profiles. Lately, the integration of nanoparticles in biotechnology and their applications in medicine has allowed us to diagnose and treat disease better and more precisely. As a model disease, we used a grade IV malignant brain tumor (glioblastoma). Significant improvements in diagnosis were achieved with the application of fluorescent nanoparticles for intraoperative magnetic resonance imaging (MRI), allowing for improved tumor cell visibility and increasing the extent of the surgical resection, leading to better patient response. Fluorescent probes can be engineered to be activated through different molecular pathways, which will open the path to individualized glioblastoma diagnosis, monitoring, and treatment. Nanoparticles are also extensively studied as nanovehicles for targeted delivery and more controlled medication release, and some nanomedicines are already in early phases of clinical trials. Moreover, sampling biological fluids will give new insights into glioblastoma pathogenesis due to the presence of extracellular vesicles, circulating tumor cells, and circulating tumor DNA. As current glioblastoma therapy does not provide good quality of life for patients, other approaches such as immunotherapy are explored. To conclude, we reason that development of personalized therapies based on a patient's genetic signature combined with pharmacogenomics and immunogenomic information will significantly change the outcome of glioblastoma patients.

Towards development of a novel universal medical diagnostic method: Raman spectroscopy and machine learning

This review summarizes recent progress made using Raman spectroscopy and machine learning for potential universal medical diagnostic applications.

Clinical translational application of Raman spectroscopy to advance Benchside biochemical characterization to bedside diagnosis of esophageal diseases

Esophageal diseases result in significant mortality, morbidity, and health care costs worldwide. Current approaches to detect and monitor esophageal diseases have severe limitations. Advanced imaging technologies are being developed to complement current approaches to improve diagnostic, therapeutic and surveillance protocols in order to advance the field. Raman spectroscopy-based technologies hold promise to increase the sensitivity for detection of diseased and high-risk lesions in vitro and in vivo in real time. This technique allows for the investigation of microstructural changes and also facilitates the discovery of disease-specific biochemical alterations with the potential to provide novel insights into the pathobiology of these conditions. Raman spectroscopy has been increasingly applied in precancerous and cancerous esophageal conditions. However, its application in benign esophageal diseases is still in the early stages. Continuing its application in cancerous and precancerous conditions and expanding its use to benign esophageal disorders could lay a foundation for integration of this technology in clinical practice and diagnostic paradigms and development of an accurate and cost-effective tool for use in a clinical setting. Furthermore, Raman spectroscopy can also be used as an innovative technique to advance our understanding of the biochemical transformations associated with esophageal diseases and answer a myriad of fundamental questions in the field. In this review, we described the principles of Raman spectroscopy and instrumentation while providing an overview of current applications, challenges, and future directions in the context of esophageal diseases with an emphasis on its clinical translational application.

Line Scan Raman Microspectroscopy for Label-Free Diagnosis of Human Pituitary Biopsies

Pituitary adenomas are neoplasia of the anterior pituitary gland and can be subdivided into hormone-producing tumors (lactotroph, corticotroph, gonadotroph, somatotroph, thyreotroph or plurihormonal) and hormone-inactive tumors (silent or null cell adenomas) based on their hormonal status. We therefore developed a line scan Raman microspectroscopy (LSRM) system to detect, discriminate and hyperspectrally visualize pituitary gland from pituitary adenomas based on molecular differences. By applying principal component analysis followed by a k-nearest neighbor algorithm, specific hormone states were identified and a clear discrimination between pituitary gland and various adenoma subtypes was achieved. The classifier yielded an accuracy of 95% for gland tissue and 84–99% for adenoma subtypes. With an overall accuracy of 92%, our LSRM system has proven its potential to differentiate pituitary gland from pituitary adenomas. LSRM images based on the presence of specific Raman bands were created, and such images provided additional insight into the spatial distribution of particular molecular compounds. Pathological states could be molecularly differentiated and characterized with texture analysis evaluating Grey Level Cooccurrence Matrices for each LSRM image, as well as correlation coefficients between LSRM images.

Multivariate Analysis of Difference Raman Spectra of the Irradiated Nucleus and Cytoplasm Region of SH-SY5Y Human Neuroblastoma Cells

Previous works showed that spatially resolved Raman spectra of cytoplasm and nucleus region of single cells exposed to X-rays evidence different features. The present work aims to introduce a new approach to profit from these differences to deeper investigate X-ray irradiation effects on single SH-SY5Y human neuroblastoma cells. For this aim, Raman micro-spectroscopy was performed in vitro on single cells after irradiation by graded X-ray doses (2, 4, 6, 8 Gy). Spectra from nucleus and cytoplasm regions were selectively acquired. The examination by interval Principal Component Analysis (i-PCA) of the difference spectra obtained by subtracting each cytoplasm-related spectrum from the corresponding one detected at the nucleus enabled us to reveal the subtle modifications of Raman features specific of different spatial cell regions. They were discussed in terms of effects induced by X-ray irradiation on DNA/RNA, lipids, and proteins. The proposed approach enabled us to evidence some features not outlined in previous investigations.