Determining ideal offsets of spatially offset Raman spectroscopy for transcutaneous measurements-A Monte Carlo study

Spatially offset Raman spectroscopy (SORS) is valuable for noninvasive bone assessment but requires a clearer understanding of how offset distances influence detection depth. To address this, our study devised a forward-adjoint Monte Carlo multi-layer (MCML) model to simulate photon paths in SORS, aiming to determine optimal offsets for various tissue types. We examined photon migration at offsets between 0 and 15 mm against layered phantoms of differing thicknesses and compositions to optimize the signal-to-noise ratio for bone layers. The findings highlight that optimal offsets are contingent on tissue characteristics: a metacarpal beneath 2.5 mm of tissue had an ideal offset of 6.7 mm, while a tibia with 5 mm of soft tissue required 10-11 mm. This precise calibration of SORS via MCML modeling promises substantial improvements in bone health diagnostics and potential for expansive medical applications.

Raman spectroscopy coupled with chemometrics for identification of adulteration and fraud in muscle foods: a review

Muscle foods, valued for their significant nutrient content such as high-quality protein, vitamins, and minerals, are vulnerable to adulteration and fraud, stemming from dishonest vendor practices and insufficient market oversight. Traditional analytical methods, often limited to laboratory-scale., may not effectively detect adulteration and fraud in complex applications. Raman spectroscopy (RS), encompassing techniques like Surface-enhanced RS (SERS), Dispersive RS (DRS), Fourier transform RS (FTRS), Resonance Raman spectroscopy (RRS), and Spatially offset RS (SORS) combined with chemometrics, presents a potent approach for both qualitative and quantitative analysis of muscle food adulteration. This technology is characterized by its efficiency, rapidity, and noninvasive nature. This paper systematically summarizes and comparatively analyzes RS technology principles, emphasizing its practicality and efficacy in detecting muscle food adulteration and fraud when combined with chemometrics. The paper also discusses the existing challenges and future prospects in this field, providing essential insights for reviews and scientific research in related fields.

Physicochemical understanding of biomineralization by molecular vibrational spectroscopy: From mechanism to nature

The process and mechanism of biomineralization and relevant physicochemical properties of mineral crystals are remarkably sophisticated multidisciplinary fields that include biology, chemistry, physics, and materials science. The components of the organic matter, structural construction of minerals, and related mechanical interaction, etc., could help to reveal the unique nature of the special mineralization process. Herein, the paper provides an overview of the biomineralization process from the perspective of molecular vibrational spectroscopy, including the physicochemical properties of biomineralized tissues, from physiological to applied mineralization. These physicochemical characteristics closely to the hierarchical mineralization process include biological crystal defects, chemical bonding, atomic doping, structural changes, and content changes in organic matter, along with the interface between biocrystals and organic matter as well as the specific mechanical effects for hardness and toughness. Based on those observations, the special physiological properties of mineralization for enamel and bone, as well as the possible mechanism of pathological mineralization and calcification such as atherosclerosis, tumor micro mineralization, and urolithiasis are also reviewed and discussed. Indeed, the clearly defined physicochemical properties of mineral crystals could pave the way for studies on the mechanisms and applications.

Two-layer reconstruction of Raman spectra in diffusive media based on an analytical model in the time domain

We derive and validate an analytical model that describes the migration of Raman scattered photons in two-layer diffusive media, based on the diffusion equation in the time domain. The model is derived under a heuristic approximation that background optical properties are identical on the excitation and Raman emission wavelengths. Methods for the reconstruction of two-layer Raman spectra have been developed, tested in computer simulations and validated on tissue-mimicking phantom measurements data. Effects of different parameters were studied in simulations, showing that the thickness of the top layer and number of detected photon counts have the most significant impact on the reconstruction. The concept of quantitative, mathematically rigorous reconstruction using the proposed model was finally proven on experimental measurements, by successfully separating the spectra of silicone and calcium carbonate (calcite) layers, showing the potential for further development and eventual application in clinical diagnostics.

Non-Invasive Detection, Precise Localization, and Perioperative Navigation of In Vivo Deep Lesions Using Transmission Raman Spectroscopy

Non-invasive detection and precise localization of deep lesions have attracted significant attention for both fundamental and clinical studies. Optical modality techniques are promising with high sensitivity and molecular specificity, but are limited by shallow tissue penetration and the failure to accurately determine lesion depth. Here the authors report in vivo ratiometric surface-enhanced transmission Raman spectroscopy (SETRS) for non-invasive localization and perioperative surgery navigation of deep sentinel lymph nodes in live rats. The SETRS system uses ultrabright surface-enhanced Raman spectroscopy (SERS) nanoparticles with a low detection limit of 10 pM and a home-built photosafe transmission Raman spectroscopy setup. The ratiometric SETRS strategy is proposed based on the ratio of multiple Raman spectral peaks for obtaining lesion depth. Via this strategy, the depth of the phantom lesions in ex vivo rat tissues is precisely determined with a mean-absolute-percentage-error of 11.8%, and the accurate localization of a 6-mm-deep rat popliteal lymph node is achieved. The feasibility of ratiometric SETRS allows the successful perioperative navigation of in vivo lymph node biopsy surgery in live rats under clinically safe laser irradiance. This study represents a significant step toward the clinical translation of TRS techniques, providing new insights for the design and implementation of in vivo SERS applications.

Noninvasive Monitoring to Detect Dehydration: Are We There Yet?

The need for hydration monitoring is significant, especially for the very young and elderly populations who are more vulnerable to becoming dehydrated and suffering from the effects that dehydration brings. This need has been among the drivers of considerable effort in the academic and commercial sectors to provide a means for monitoring hydration status, with a special interest in doing so outside the hospital or clinical setting. This review of emerging technologies provides an overview of many technology approaches that, on a theoretical basis, have sensitivity to water and are feasible as a routine measurement. We review the evidence of technical validation and of their use in humans. Finally, we highlight the essential need for these technologies to be rigorously evaluated for their diagnostic potential, as a necessary step to meet the need for hydration monitoring outside of the clinical environment.

Fundamentals and Applications of Raman-Based Techniques for the Design and Development of Active Biomedical Materials

Raman spectroscopy is an analytical method based on light-matter interactions that can interrogate the vibrational modes of matter and provide representative molecular fingerprints. Mediated by its label-free, non-invasive nature, and high molecular specificity, Raman-based techniques have become ubiquitous tools for in situ characterization of materials. This review comprehensively describes the theoretical and practical background of Raman spectroscopy and its advanced variants. The numerous facets of material characterization that Raman scattering can reveal, including biomolecular identification, solid-to-solid phase transitions, and spatial mapping of biomolecular species in bioactive materials, are highlighted. The review illustrates the potential of these techniques in the context of active biomedical material design and development by highlighting representative studies from the literature. These studies cover the use of Raman spectroscopy for the characterization of both natural and synthetic biomaterials, including engineered tissue constructs, biopolymer systems, ceramics, and nanoparticle formulations, among others. To increase the accessibility and adoption of these techniques, the present review also provides the reader with practical recommendations on the integration of Raman techniques into the experimental laboratory toolbox. Finally, perspectives on how recent developments in plasmon- and coherently-enhanced Raman spectroscopy can propel Raman from underutilized to critical for biomaterial development are provided.

Spatially Offset Raman Spectroscopy Combined with Attention-Based LSTM for Freshness Evaluation of Shrimp

Optical detection of the freshness of intact in-shell shrimps is a well-known difficult task due to shell occlusion and its signal interference. The spatially offset Raman spectroscopy (SORS) is a workable technical solution for identifying and extracting subsurface shrimp meat information by collecting Raman scattering images at different distances from the offset laser incidence point. However, the SORS technology still suffers from physical information loss, difficulties in determining the optimum offset distance, and human operational errors. Thus, this paper presents a shrimp freshness detection method using spatially offset Raman spectroscopy combined with a targeted attention-based long short-term memory network (attention-based LSTM). The proposed attention-based LSTM model uses the LSTM module to extract physical and chemical composition information of tissue, weight the output of each module by an attention mechanism, and come together as a fully connected (FC) module for feature fusion and storage dates prediction. Modeling predictions by collecting Raman scattering images of 100 shrimps within 7 days. The R², RMSE, and RPD of the attention-based LSTM model achieved 0.93, 0.48, and 4.06, respectively, which is superior to the conventional machine learning algorithm with manual selection of the optimal spatially offset distance. This method of automatically extracting information from SORS data by Attention-based LSTM eliminates human error and enables fast and non-destructive quality inspection of in-shell shrimp.

Open-sourced Raman spectroscopy data processing package implementing a baseline removal algorithm validated from multiple datasets acquired in human tissue and biofluids

SIGNIFICANCE

Standardized data processing approaches are required in the field of bio-Raman spectroscopy to ensure information associated with spectral data acquired by different research groups, and with different systems, can be compared on an equal footing.

AIM

An open-sourced data processing software package was developed, implementing algorithms associated with all steps required to isolate the inelastic scattering component from signals acquired using Raman spectroscopy devices. The package includes a novel morphological baseline removal technique (BubbleFill) that provides increased adaptability to complex baseline shapes compared to current gold standard techniques. Also incorporated in the package is a versatile tool simulating spectroscopic data with varying levels of Raman signal-to-background ratios, baselines with different morphologies, and varying levels of stochastic noise.

RESULTS

Application of the BubbleFill technique to simulated data demonstrated superior baseline removal performance compared to standard algorithms, including iModPoly and MorphBR. The data processing workflow of the open-sourced package was validated in four independent in-human datasets, demonstrating it leads to inter-systems data compatibility.

CONCLUSIONS

A new open-sourced spectroscopic data pre-processing package was validated on simulated and real-world in-human data and is now available to researchers and clinicians for the development of new clinical applications using Raman spectroscopy.

Review: Emerging Eye-Based Diagnostic Technologies for Traumatic Brain Injury

The study of ocular manifestations of neurodegenerative disorders, Oculomics, is a growing field of investigation for early diagnostics, enabling structural and chemical biomarkers to be monitored overtime to predict prognosis. Traumatic brain injury (TBI) triggers a cascade of events harmful to the brain, which can lead to neurodegeneration. TBI, termed the "silent epidemic" is becoming a leading cause of death and disability worldwide. There is currently no effective diagnostic tool for TBI, and yet, early-intervention is known to considerably shorten hospital stays, improve outcomes, fasten neurological recovery and lower mortality rates, highlighting the unmet need for techniques capable of rapid and accurate point-of-care diagnostics, implemented in the earliest stages. This review focuses on the latest advances in the main neuropathophysiological responses and the achievements and shortfalls of TBI diagnostic methods. Validated and emerging TBI-indicative biomarkers are outlined and linked to ocular neuro-disorders. Methods detecting structural and chemical ocular responses to TBI are categorised along with prospective chemical and physical sensing techniques. Particular attention is drawn to the potential of Raman spectroscopy as a non-invasive sensing of neurological molecular signatures in the ocular projections of the brain, laying the platform for the first tangible path towards alternative point-of-care diagnostic technologies for TBI.

Miniaturized 7-in-1 fiber-optic Raman probe

This Letter reports a miniature 7-in-1 fiber-optic Raman probe that eliminates the inelastic background Raman signal from a long-fused silica fiber. Its foremost purpose is to enhance a method for investigating extraordinarily tiny substances and effectively capturing Raman inelastic backscattered signals using optical fibers. We successfully used our home-built fiber taper device to combine seven multimode fibers into a single fiber taper with a probe diameter of approximately 35 µm. By experimentally comparing the traditional bare fiber-based Raman spectroscopy system with the miniaturized tapered fiber-optic Raman sensor using liquid solutions, the novel probe's capability is demonstrated. We observed that the miniaturized probe effectively removed the Raman background signal originating from the optical fiber and confirmed expected outcomes for a series of common Raman spectra.

Assessing the quality of stored red blood cells using handheld Spatially Offset Raman spectroscopy with multisource correlation analysis

In this work we employ Spatially Offset Raman Spectroscopy (SORS) to non-invasively identify storage-related changes in red blood cell concentrate (RCC) in-situ within standard plastic transfusion bags. To validate the measurements, we set up a parallel study comparing both bioanalytical data (obtained by blood-gas analysis, hematology analysis and spectrophotometric assays), and Raman spectrometry data from the same blood samples. We then employ Multisource Correlation Analysis (MuSCA) to correlate the different types of data in RCC. Our analysis confirmed a strong correlation of glucose, methemoglobin and oxyhemoglobin with their respective bioassay values in RCC units. Finally, by combining MuSCA with k-means clustering, we assessed changes in all Raman wavenumbers during cold storage in both RCC Raman data from the current study and parallel RCC supernatant Raman data previously acquired from the same units. Direct RCC quality monitoring during storage, would help to establish a basis for improved inventory management of blood products in blood banks and hospitals based on analytical data.

In vivo non-invasive monitoring of tissue development in 3D printed subcutaneous bone scaffolds using fibre-optic Raman spectroscopy

The development of novel biomaterials for regenerative therapy relies on the ability to assess tissue development, quality, and similarity with native tissue types in in vivo experiments. Non-invasive imaging modalities such as X-ray computed tomography offer high spatial resolution but limited biochemical information while histology and biochemical assays are destructive. Raman spectroscopy is a non-invasive, label-free and non-destructive technique widely applied for biochemical characterization. Here we demonstrate the use of fibre-optic Raman spectroscopy for in vivo quantitative monitoring of tissue development in subcutaneous calcium phosphate scaffolds in mice over 16 weeks. Raman spectroscopy was able to quantify the time dependency of different tissue components related to the presence, absence, and quantity of mesenchymal stem cells. Scaffolds seeded with stem cells produced 3-5 times higher amount of collagen-rich extracellular matrix after 16 weeks implantation compared to scaffolds without. These however, showed a 2.5 times higher amount of lipid-rich tissue compared to implants with stem cells. Ex vivo micro-computed tomography and histology showed stem cell mediated collagen and bone development. Histological measures of collagen correlated well with Raman derived quantifications (correlation coefficient in vivo 0.74, ex vivo 0.93). In the absence of stem cells, the scaffolds were largely occupied by adipocytes. The technique developed here could potentially be adapted for a range of small animal experiments for assessing tissue engineering strategies at the biochemical level.

Tomographic Imaging and Localization of Nanoparticles in Tissue Using Surface-Enhanced Spatially Offset Raman Spectroscopy

A fundamental question crucial to surface-enhanced spatially offset Raman spectroscopy (SESORS) imaging and implementing it in a clinical setting for in vivo diagnostic purposes is whether a SESORS image can be used to determine the exact location of an object within tissue? To address this question, multiple experimental factors pertaining to the optical setup in imaging experiments using an in-house-built point-collection-based spatially offset Raman spectroscopy (SORS) system were investigated to determine those critical to the three-dimensional (3D) positioning capability of SESORS. Here, we report the effects of the spatial offset magnitude and geometry on locating nanoparticles (NPs) mixed with silica powder as an imaging target through tissue and outline experimental techniques to allow for the correct interpretation of SESORS images to ascertain the correct location of NPs in the two-dimensional x, y-imaging plane at depth. More specifically, the effect of "linear offset-induced image drag" is presented, which refers to a spatial distortion in SESORS images caused by the magnitude and direction of the linear offset and highlight the need for an annular SORS collection geometry during imaging to neutralize these asymmetric effects. Additionally, building on these principles, the concept of "ratiometric SESORS imaging" is introduced for the location of buried inclusions in three dimensions. Together these principles are vital in developing a methodology for the location of surface-enhanced Raman scattering-active inclusions in three dimensions. This approach utilizes the relationship between the magnitude of the spatial offset, the probed depth, and ratiometric analysis of the NP and tissue Raman intensities to ultimately image and spatially discriminate between two distinct NP flavors buried at different depths within a 3D model for the first time. This research demonstrates how to accurately identify multiple objects at depth in tissue and their location using SESORS which addresses a key capability in moving SESORS closer to use in biomedical applications.

Raman studies of the adipose tissue: Current state-of-art and future perspectives in diagnostics

The last decades revealed that the adipose tissue shows an unexplored therapeutic potential. In particular, targeting the perivascular adipose tissue (PVAT), that surrounds blood vessels, can prevent cardiovascular pathologies and browning of the adipose tissue can become an effective strategy against obesity. Therefore, new analytical tools are necessary to analyze this tissue. This review reports on the recent developments of various Raman-based techniques for the identification and quantification of the adipose tissue compared to conventional analytical methods. In particular, the emphasis is on analysis of PVAT, investigation of pathological changes of the adipose tissue in model systems and possibilities for its characterization in the clinical context. Overall, the review critically discusses the potential and limitations of Raman techniques in adipose tissue-targeted diagnostics and possible future anti-obesity therapies.

Featuring few essential Raman spectroscopic signatures between heterogeneous cells

Here we demonstrate it is instructive to quantify cell Raman spectroscopy by sparse regularization. To be able to extract the specific spectral differences in a heterogeneous cell system with great spectroscopic similarities derived from many common biomolecular components, the maximum information entropy probability was proposed and exemplified by identifying normal lymphocytes from leukemia cells. The essential spectroscopic features were observed to locate at three Raman peaks whose spectral signatures were commensurate. The applicability of the extracted features was acknowledged by that the predicted identification accuracy of up to 93% was still achieved when only two peaks were loaded into decision tree model, which may provide the possibility of a clinically rapid hematological malignancy detection.

To focus-match or not to focus-match inverse spatially offset Raman spectroscopy: a question of light penetration

The ability to identify the contents of a sealed container, without the need to extract a sample, is desirable in applications ranging from forensics to product quality control. One technique suited to this is inverse spatially offset Raman spectroscopy (ISORS) which illuminates a sample of interest with an annular beam of light and collects Raman scattering from the center of the ring, thereby retrieving the chemical signature of the contents while suppressing signal from the container. Here we explore in detail the relative benefits of a recently developed variant of ISORS, called focus-matched ISORS. In this variant, the Fourier relationship between the annular beam and a tightly focused Bessel beam is exploited to focus the excitation light inside the sample and to match the focal point of excitation and collection optics to increase the signal from the contents without compromising the suppression of the container signal. Using a flexible experimental setup which can realize both traditional and focus-matched ISORS, and Monte-Carlo simulations, we elucidate the relative advantages of the two techniques for a range of optical properties of sample and container.

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.

Raman spectroscopy-based water measurements identify the origin of MRI T2 signal in human articular cartilage zones and predict histopathologic score

We investigated for the first time zonal-dependent water distribution in articular cartilage by Raman spectroscopy (RS). We further investigated the association of histopathologic score with RS- and magnetic resonance imaging (MRI)-based water measurements. Cadaveric human cartilage plugs (N = 16) with different osteoarthritis (OA) severity were used. Water content distribution in cartilage zones was probed using RS- and MRI-based techniques. Histopathologic scoring was performed by two independent observers blindly. Moderate associations existed between RS- and MRI-based water measurements across all cartilage zones. RS-based analysis of different water compartments helped assign the origin of the T2 signal collected from the various cartilage zones. RS-based water parameters significantly correlated with OA-severity score, whereas MRI-based water measurements did not. RS can probe different water compartments in cartilage zones and predict up to 66% of the variation observed in the histopathologic score. RS-based water measurement could be developed further to assess cartilage quality in the clinic.

Non-Destructive Spatial Mapping of Glycosaminoglycan Loss in Native and Degraded Articular Cartilage Using Confocal Raman Microspectroscopy

Articular cartilage is a collagen-rich tissue that provides a smooth, lubricated surface for joints and is also responsible for load bearing during movements. The major components of cartilage are water, collagen, and proteoglycans. Osteoarthritis is a degenerative disease of articular cartilage, in which an early-stage indicator is the loss of proteoglycans from the collagen matrix. In this study, confocal Raman microspectroscopy was applied to study the degradation of articular cartilage, specifically focused on spatially mapping the loss of glycosaminoglycans (GAGs). Trypsin digestion was used as a model for cartilage degradation. Two different scanning geometries for confocal Raman mapping, cross-sectional and depth scans, were applied. The chondroitin sulfate coefficient maps derived from Raman spectra provide spatial distributions similar to histological staining for glycosaminoglycans. The depth scans, during which subsurface data were collected without sectioning the samples, can also generate spectra and GAG distributions consistent with Raman scans of the surface-to-bone cross sections. In native tissue, both scanning geometries demonstrated higher GAG content at the deeper zone beneath the articular surface and negligible GAG content after trypsin degradation. On partially digested samples, both scanning geometries detected an ∼100 μm layer of GAG depletion. Overall, this research provides a technique with high spatial resolution (25 μm pixel size) to measure cartilage degradation without tissue sections using confocal Raman microspectroscopy, laying a foundation for potential in vivo measurements and osteoarthritis diagnosis.

Raman spectroscopic analysis of skin as a diagnostic tool for Human African Trypanosomiasis

Human African Trypanosomiasis (HAT) has been responsible for several deadly epidemics throughout the 20th century, but a renewed commitment to disease control has significantly reduced new cases and motivated a target for the elimination of Trypanosoma brucei gambiense-HAT by 2030. However, the recent identification of latent human infections, and the detection of trypanosomes in extravascular tissues hidden from current diagnostic tools, such as the skin, has added new complexity to identifying infected individuals. New and improved diagnostic tests to detect Trypanosoma brucei infection by interrogating the skin are therefore needed. Recent advances have improved the cost, sensitivity and portability of Raman spectroscopy technology for non-invasive medical diagnostics, making it an attractive tool for gambiense-HAT detection. The aim of this work was to assess and develop a new non-invasive diagnostic method for T. brucei through Raman spectroscopy of the skin. Infections were performed in an established murine disease model using the animal-infective Trypanosoma brucei brucei subspecies. The skin of infected and matched control mice was scrutinized ex vivo using a confocal Raman microscope with 532 nm excitation and in situ at 785 nm excitation with a portable field-compatible instrument. Spectral evaluation and Principal Component Analysis confirmed discrimination of T. brucei-infected from uninfected tissue, and a characterisation of biochemical changes in lipids and proteins in parasite-infected skin indicated by prominent Raman peak intensities was performed. This study is the first to demonstrate the application of Raman spectroscopy for the detection of T. brucei by targeting the skin of the host. The technique has significant potential to discriminate between infected and non-infected tissue and could represent a unique, non-invasive diagnostic tool in the goal for elimination of gambiense-HAT as well as for Animal African Trypanosomiasis (AAT).

Human African Trypanosomiasis (HAT), also known as sleeping sickness, is a disease caused by the parasite Trypanosoma brucei and has been responsible for the death of millions of people across Africa in the 20^th century. It is also a major economic burden for countries endemic for trypanosomiasis, affecting livestock productivity in rural areas (Animal African Trypanosomiasis). A long-term international collaboration with the help of the World Health Organisation has resulted in the rate of human infection decreasing to less than 1000 new cases per year. However, the human disease continues to spread within remote villages. Current diagnosis is based on the detection of parasites in blood and serum samples, but this is challenging during chronic human infections with low or non-detectable parasitaemia. However, the recent discovery of extravascular skin-dwelling trypanosomes indicates that a reservoir of infection remains undetected, threatening the effort to eliminate the disease. In this study we have targeted the skin as a site for diagnosis using Raman spectroscopy and demonstrate that this method showed great promise in the laboratory, laying the foundation for field studies to examine its potential to strengthen current diagnostic strategies for detecting HAT cases.

Advancing Raman spectroscopy from research to clinic: Translational potential and challenges

Raman spectroscopy has emerged as a non-invasive and versatile diagnostic technique due to its ability to provide molecule-specific information with ultrahigh sensitivity at near-physiological conditions. Despite exhibiting substantial potential, its translation from optical bench to clinical settings has been impacted by associated limitations. This perspective discusses recent clinical and biomedical applications of Raman spectroscopy and technological advancements that provide valuable insights and encouragement for resolving some of the most challenging hurdles.

A New Look into Cancer-A Review on the Contribution of Vibrational Spectroscopy on Early Diagnosis and Surgery Guidance

Simple Summary

Cancer is a leading cause of death worldwide, with the detection of the disease in its early stages, as well as a correct assessment of the tumour margins, being paramount for a successful recovery. While breast cancer is one of most common types of cancer, head and neck cancer is one of the types of cancer with a lower prognosis and poor aesthetic results. Vibrational spectroscopy detects molecular vibrations, being sensitive to different sample compositions, even when the difference was slight. The use of spectroscopy in biomedicine has been extensively explored, since it allows a broader assessment of the biochemical fingerprint of several diseases. This literature review covers the most recent advances in breast and head and neck cancer early diagnosis and intraoperative margin assessment, through Raman and Fourier transform infrared spectroscopies. The rising field of spectral histopathology was also approached. The authors aimed at expounding in a more concise and simple way the challenges faced by clinicians and how vibrational spectroscopy has evolved to respond to those needs for the two types of cancer with the highest potential for improvement regarding an early diagnosis, surgical margin assessment and histopathology.

Abstract

In 2020, approximately 10 million people died of cancer, rendering this disease the second leading cause of death worldwide. Detecting cancer in its early stages is paramount for patients’ prognosis and survival. Hence, the scientific and medical communities are engaged in improving both therapeutic strategies and diagnostic methodologies, beyond prevention. Optical vibrational spectroscopy has been shown to be an ideal diagnostic method for early cancer diagnosis and surgical margins assessment, as a complement to histopathological analysis. Being highly sensitive, non-invasive and capable of real-time molecular imaging, Raman and Fourier transform infrared (FTIR) spectroscopies give information on the biochemical profile of the tissue under analysis, detecting the metabolic differences between healthy and cancerous portions of the same sample. This constitutes tremendous progress in the field, since the cancer-prompted morphological alterations often occur after the biochemical imbalances in the oncogenic process. Therefore, the early cancer-associated metabolic changes are unnoticed by the histopathologist. Additionally, Raman and FTIR spectroscopies significantly reduce the subjectivity linked to cancer diagnosis. This review focuses on breast and head and neck cancers, their clinical needs and the progress made to date using vibrational spectroscopy as a diagnostic technique prior to surgical intervention and intraoperative margin assessment.

Calcitonin Gene-Related Peptide Influences Bone-Tendon Interface Healing Through Osteogenesis: Investigation in a Rabbit Partial Patellectomy Model

Background:

Calcitonin gene-related peptide (CGRP), which has been shown to play an important role in osteogenesis during fracture repair, is also widely distributed throughout the tendon and ligament. Few studies have focused on the role of CGRP in repair of the bone-tendon interface (BTI).

Purpose:

To explore the effect of CGRP expression on BTI healing in a rabbit partial patellectomy model.

Study Design:

Controlled laboratory study.

Methods:

A total of 60 mature rabbits were subjected to a partial patellectomy and then randomly assigned to CGRP, CGRP-antagonist, and control groups. In the CGRP-antagonist group, the CGRP receptor antagonist BIBN4096BS was administered to block CGRP receptors. The patella–patellar tendon complex was harvested at 8 and 16 weeks postoperatively and subjected to radiographic, microlaser Raman spectroscopy, histologic, and biomechanical evaluation.

Results:

Radiographic data showed that local CGRP expression improved the growth parameters of newly formed bone, including area and volumetric bone mineral density (P < .05 for both). Raman spectroscopy revealed that the relative bone mineral composition increased in the CGRP group compared with in the control group and the CGRP-antagonist group (P < .05 for both). Histologic testing revealed that the CGRP group demonstrated better integration, characterized by well-developed trabecular bone expansion from the residual patella and marrow cavity formation, at the 8- and 16-week time points. Mechanical testing demonstrated that the failure load, ultimate strength, and stiffness in the CGRP group were significantly higher than those in the control group (P < .05 for all), whereas these parameters in the CGRP-antagonist group were significantly lower compared with those in the control group at 16 weeks after surgery (P < .05 for all).

Conclusion:

Increasing the local concentration of CGRP in the early stages of BTI healing enhanced osteogenesis in a rabbit partial patellectomy model and promoted healing of the BTI injury, whereas treatment using a CGRP antagonist had the opposite effect. However, exogenous CGRP expression did not induce novel bone remolding.

Clinical Relevance:

CGRP may have potential as a new therapy for BTI injuries or may be added to postoperative regimens to facilitate healing.

Non-Invasive Identification of Nutrient Components in Grain

Digital farming is a modern agricultural concept that aims to maximize the crop yield while simultaneously minimizing the environmental impact of farming. Successful implementation of digital farming requires development of sensors to detect and identify diseases and abiotic stresses in plants, as well as to probe the nutrient content of seeds and identify plant varieties. Experimental evidence of the suitability of Raman spectroscopy (RS) for confirmatory diagnostics of plant diseases was previously provided by our team and other research groups. In this study, we investigate the potential use of RS as a label-free, non-invasive and non-destructive analytical technique for the fast and accurate identification of nutrient components in the grains from 15 different rice genotypes. We demonstrate that spectroscopic analysis of intact rice seeds provides the accurate rice variety identification in ~86% of samples. These results suggest that RS can be used for fully automated, fast and accurate identification of seeds nutrient components.

Comparison of functional and discrete data analysis regimes for Raman spectra

Raman spectral data are best described by mathematical functions; however, due to the spectroscopic measurement setup, only discrete points of these functions are measured. Therefore, we investigated the Raman spectral data for the first time in the functional framework. First, we approximated the Raman spectra by using B-spline basis functions. Afterwards, we applied the functional principal component analysis followed by the linear discriminant analysis (FPCA-LDA) and compared the results with those of the classical principal component analysis followed by the linear discriminant analysis (PCA-LDA). In this context, simulation and experimental Raman spectra were used. In the simulated Raman spectra, normal and abnormal spectra were used for a classification model, where the abnormal spectra were built by shifting one peak position. We showed that the mean sensitivities of the FPCA-LDA method were higher than the mean sensitivities of the PCA-LDA method, especially when the signal-to-noise ratio is low and the shift of the peak position is small. However, for a higher signal-to-noise ratio, both methods performed equally. Additionally, a slight improvement of the mean sensitivity could be shown if the FPCA-LDA method was applied to experimental Raman data.

A New Frontier for Nondestructive Spatial Analysis of Pharmaceutical Solid Dosage Forms: Spatially Offset Low-Frequency Raman Spectroscopy

A new Raman subtechnique, spatially offset low-frequency Raman spectroscopy (SOLFRS), is demonstrated via an analysis of pharmaceutical solid dosage forms. Several different model systems comprised of celecoxib (a popular anti-inflammatory drug), α-lactose anhydrous stable form, α-lactose monohydrate, and polyvinylpyrrolidone (PVP) were used to represent tangible scenarios for the application of SOLFRS. Additionally, the challenges and limitations were highlighted in relation to its real-time use, and potential solutions to address them were also provided. Lastly, the future directions for this new variation of Raman spectroscopic technique were briefly discussed, including its potential for broader application in pharmaceutical analysis and other research fields.

Improved prediction of femoral fracture toughness in mice by combining standard medical imaging with Raman spectroscopy

Bone fragility and fracture risk are assessed by measuring the areal bone mineral density (aBMD) using dual-energy X-ray absorptiometry (DXA). While aBMD correlates with bone strength, it is a poor predictor of fragility fracture risk. Alternatively, fracture toughness assesses the bone's resistance to crack propagation and fracture, making it a suitable bone quality metric. Here, we explored how femoral midshaft measurements from DXA, micro-computed tomography (µCT), and Raman spectroscopy could predict fracture toughness. We hypothesized that ovariectomy (OVX) decreases aBMD and fracture toughness compared to controls and we can optimize a multivariate assessment of bone quality by combining results from X-ray and Raman spectroscopy. Female mice underwent an OVX (n = 5) or sham (n = 5) surgery at 3 months of age. Femurs were excised 3 months after ovariectomy and assessed with Raman spectroscopy, µCT, and DXA. Subsequently, a notch was created on the anterior side of the mid-diaphysis of the femurs. Three-point bending induced a controlled fracture that initiated at the notch. The OVX mice had a significantly lower aBMD, cortical thickness, and fracture toughness when compared to controls (p < 0.05). A leave one out cross-validated (LOOCV) partial least squares regression (PLSR) model based only on the combination of aBMD and cortical thickness showed no significant predictive correlations with fracture toughness, whereas a PLSR model based on principal components derived from the full Raman spectra yielded significant prediction (r² = 0.71, p < 0.05). Further, the PLSR model was improved by incorporating aBMD, cortical thickness, and principal components from Raman spectra (r² = 0.92, p < 0.001). This exploratory study demonstrates combining X-ray with Raman spectroscopy leads to a more accurate assessment of bone fracture toughness and could be a useful diagnostic tool for the assessment of fragility fracture risk.

Spatially offset Raman spectroscopy for biomedical applications

In recent years, Raman spectroscopy has undergone major advancements in its ability to probe deeply through turbid media such as biological tissues. This progress has been facilitated by the advent of a range of specialist techniques based around spatially offset Raman spectroscopy (SORS) to enable non-invasive probing of living tissue through depths of up to 5 cm. This represents an improvement in depth penetration of up to two orders of magnitude compared to what can be achieved with conventional Raman methods. In combination with the inherently high molecular specificity of Raman spectroscopy, this has therefore opened up entirely new prospects for a range of new analytical applications across multiple fields including medical diagnosis and disease monitoring. This article discusses SORS and related variants of deep Raman spectroscopy such as transmission Raman spectroscopy (TRS), micro-SORS and surface enhanced spatially offset Raman spectroscopy (SESORS), and reviews the progress made in this field during the past 5 years including advances in non-invasive cancer diagnosis, monitoring of neurotransmitters, and assessment of bone disease.

Calibration transfer between modelled and commercial pharmaceutical tablet for API quantification using backscattering NIR, Raman and transmission Raman spectroscopy (TRS)

Backscattering NIR, Raman (BSR) and transmission Raman spectroscopy (TRS) coupled with chemometrics have shown to be rapid and non-invasive tools for the quantification of active pharmaceutical ingredient (API) content in tablets. However, the developed models are generally specifically related to the measurement conditions and sample characteristics. In this study, a number of calibration transfer methods, including DS, PDS, DWPDS, GLSW and SST, were evaluated for the spectra correction between modelled tablets produced in the laboratory and commercial samples. Results showed that the NIR and BSR spectra of commercial tablet corrected by DWPDS and PDS, respectively, enabled accurate API predictions with the high ratio of prediction error to deviation (RPD_P) values of 2.33 and 3.03. The most successfully approach was achieved with DS corrected TRS data and SiPLS modelling (161 variables) and yielded RMSE_P of 0.72 %, R²_P of 0.946 and RPD_P of 4.35. The proposed calibration transfer strategy offers the opportunities to analyse samples produced in different conditions; in the future, its implication will find extensively process control and quality assurance applications and benefit all possible users in the entire pharmaceutical industry.

Introduction to Infrared and Raman-Based Biomedical Molecular Imaging and Comparison with Other Modalities

Molecular imaging has rapidly developed to answer the need of image contrast in medical diagnostic imaging to go beyond morphological information to include functional differences in imaged tissues at the cellular and molecular levels. Vibrational (infrared (IR) and Raman) imaging has rapidly emerged among the molecular imaging modalities available, due to its label-free combination of high spatial resolution with chemical specificity. This article presents the physical basis of vibrational spectroscopy and imaging, followed by illustration of their preclinical in vitro applications in body fluids and cells, ex vivo tissues and in vivo small animals and ending with a brief discussion of their clinical translation. After comparing the advantages and disadvantages of IR/Raman imaging with the other main modalities, such as magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography/single-photon emission-computed tomography (PET/SPECT), ultrasound (US) and photoacoustic imaging (PAI), the design of multimodal probes combining vibrational imaging with other modalities is discussed, illustrated by some preclinical proof-of-concept examples.

Investigating the feasibility of spatially offset Raman spectroscopy for in-vivo monitoring of bone healing in rat calvarial defect models

A wide range of biomaterials and tissue-engineered scaffolds are being investigated to support and stimulate bone healing in animal models. Using phantoms and rat cadavers, we investigated the feasibility of using spatially offset Raman spectroscopy (SORS) to monitor changes in collagen concentration at levels similar to those expected to occur in vivo during bone regeneration (0-0.84 g/cm³ ). A partial least squares (PLS) regression model was developed to quantify collagen concentration in plugs consisting of mixtures or collagen and hydroxyapatite (predictive power of ±0.16 g/cm³ ). The PLS model was then applied on SORS spectra acquired from rat cadavers after implanting the collagen: hydroxyapatite plugs in drilled skull defects. The PLS model successfully predicting the profile of collagen concentration, but with an increased predictive error of ±0.30 g/cm³ . These results demonstrate the potential of SORS to quantify collagen concentrations, in the range relevant to those occurring during new bone formation.

Low resolution Raman: the impact of spectral resolution on limit of detection and imaging speed in hyperspectral imaging

The majority of problems in analytical Raman spectroscopy are mathematically over-determined, where many more spectral variables are measured than analytic outputs (such as chemical concentrations) are calculated. Thus, to improve spectral throughput and simplify system design, some researchers have explored the use of low resolution Raman systems for cell or tissue classification, achieving accuracy independent of spectral resolution. However, the tradeoffs inherent in this approach have not been systematically studied. Here, we theoretically and experimentally explore the relationship between spectral resolution and analytical error. We show that decreased spectral resolution leads to spectral signal-to-noise ratio and therefore more reliable results and lower limits of detection for equivalent integration times in blind unmixing of hyperspectral images. Our theoretical analysis demonstrates that the primary benefit of low resolution Raman spectroscopy is in overcoming detector noise (such as thermal or electronic noise). Therefore, the benefits are most pronounced when utilizing lower-grade, uncooled detectors. Therefore, using a low-cost CMOS camera we experimentally demonstrate the ability of low resolution Raman spectroscopy to achieve substantially improved imaging performance compared to fully-resolved Raman spectral imaging, paving the way for cost-effective, pervasive Raman spectroscopy.

Smart Gold Nanostructures for Light Mediated Cancer Theranostics: Combining Optical Diagnostics with Photothermal Therapy

Nanotheranostics, which combines optical multiplexed disease detection with therapeutic monitoring in a single modality, has the potential to propel the field of nanomedicine toward genuine personalized medicine. Currently employed mainstream modalities using gold nanoparticles (AuNPs) in diagnosis and treatment are limited by a lack of specificity and potential issues associated with systemic toxicity. Light-mediated nanotheranostics offers a relatively non-invasive alternative for cancer diagnosis and treatment by using AuNPs of specific shapes and sizes that absorb near infrared (NIR) light, inducing plasmon resonance for enhanced tumor detection and generating localized heat for tumor ablation. Over the last decade, significant progress has been made in the field of nanotheranostics, however the main biological and translational barriers to nanotheranostics leading to a new paradigm in anti-cancer nanomedicine stem from the molecular complexities of cancer and an incomplete mechanistic understanding of utilization of Au-NPs in living systems. This work provides a comprehensive overview on the biological, physical and translational barriers facing the development of nanotheranostics. It will also summarise the recent advances in engineering specific AuNPs, their unique characteristics and, importantly, tunability to achieve the desired optical/photothermal properties.

Noninvasive Detection of Differential Water Content Inside Biological Samples Using Deep Raman Spectroscopy

Here we conceptually demonstrate the capability of deep Raman spectroscopy to noninvasively monitor changes in the water content within biological tissues. Water was added by injection into an isolated tissue volume (a 20 mm diameter disk of 5 mm thickness) representing a 20% increase in the overall mass, which was equivalent to a 5% increase in the water/tissue content. The elevated water content was detected through a larger volume of tissue with a total thickness of approximately 12 mm and a spiked tissue segment located in its center using transmission Raman spectroscopy (TRS) by monitoring the change of the OH (∼3390 cm^-1) Raman band area (3350-3550 cm^-1 spectral region) after being normalized to the neighboring CH stretching band. The tissue sample was raster scanned with TRS to yield a spatial map of the water concentration within the sample encompassing the spiked tissue zone. The mapping revealed the presence and location of the spiked region. The results provide the first conceptual demonstration using a deep Raman-based architecture, which can be used noninvasively for the detection of an elevated water content deep within biological tissues. It is envisaged that this concept could play a role in rapid in vivo detection and localization of cancerous lesions (generally exhibiting a higher water content) beneath the tissue surface.

Two dimensional ZIF-derived ultra-thin Cu-N/C nanosheets as high performance oxygen reduction electrocatalysts for high-performance Zn-air batteries

Bottom-up construction of transition copper-nitrogen-carbon (Cu-N-C) electrocatalysts with high-performance and long-term durability for the oxygen reduction reaction (ORR) still remains a great challenge. Herein, we propose a temperature-controlled synthesis strategy with confinement effect for fabrication of a novel two-dimensional dual-metal (Cu/Zn) zeolitic imidazolate framework material, which presents an ultrathin nanosheet morphology after high-temperature thermal treatment (denoted as Cu-N-UNS). By controlling the reaction temperature as well as regulating the ratio of metal ions and taking advantages of the confinement effect of surfactants, the rationally designed ultra-thin carbon layer not only prevents aggregation of transition Cu particles and avoids direct contact with reactants and electrolyte solutions to enhance the durability of electrocatalysts, but also shortens the electronic transmission path between the active transition metal species and carbon surface. Therefore, the electrocatalyst exhibits excellent electrocatalytic performance for the ORR (E1/2 ≈ 0.898 V), which is superior to those of state-of-the-art benchmark noble-metal electrocatalysts. Moreover, the even distribution of Cu-N-C and existence of N-Cu2+-Cu0 active sites make a great contribution to the electrocatalyst activity. Notably, the Cu-N-UNS used as air electrodes for Zn-air batteries also exhibits a high peak power density of ≈134.7 mW cm-2 at a current density of ≈231.9 mA cm-2 with remarkable durability.

Feasibility of Voltage-Applied SERS Measurement of Bile Juice as an Effective Analytical Scheme to Enhance Discrimination between Gall Bladder (GB) Polyp and GB Cancer

A unique surface-enhanced Raman scattering (SERS) measurement scheme to discriminate gall bladder (GB) polyp and GB cancer by analysis of bile juice is proposed. Along with the high sensitivity of SERS, external voltage application during SERS measurement was incorporated to improve sample discriminability. For this purpose, Au nanodendrites were constructed on a screen-printed electrode (referred to as AuND@SPE), and Raman spectra of extracted aqueous phases from raw bile juice samples were acquired using the AuND@SPE at voltages from -300 to 300 mV. The sample spectra resembled that of bilirubin, possessing an open chain tetrapyrrole, showing that bilirubin derivatives in bile juice were mainly responsible for the observed peaks. Discrimination of GB polyp and GB cancer using just the normal SERS spectra was not achieved but became apparent when the spectra were acquired at a voltage of -100 mV. When voltage-applied SERS spectra of bilirubin and urobilinogen (one of bilirubin's derivatives) were examined, a sudden intensity elevation occurring at -100 mV was observed for urobilinogen but not bilirubin. Based on examination of corresponding cyclic voltammograms, the potential-driven strong adsorption of urobilinogen (no faradaic charge transfer) on AuND occurring at -100 mV induced a substantial increase in SERS intensity. It was presumed that the content of urobilinogen in the bile juice of a GB cancer patient would be higher than that of a GB polyp patient, and the contained urobilinogen was sensitively highlighted by applying -100 mV during SERS measurement, allowing clear discrimination of GB cancer against GB polyp.

Non-invasive identification of potato varieties and prediction of the origin of tuber cultivation using spatially offset Raman spectroscopy

High starch content, simplicity of cultivation, and high productivity make potatoes (Solanum tuberosum) a staple in the diet of people around the world. On average, potatoes are composed of 83% water and 12% carbohydrates, and the remaining 4% includes proteins, vitamins, and other trace elements. These proportions vary depending on the type of potato and location where they were cultivated. At the same time, the chemical composition determines the nutritional value of potato tubers and can be proved using various wet chemistry and spectroscopic methods. For instance, gravity measurements, as well as several different colorimetric assays, can be used to investigate the starch content. However, these approaches are indirect, often destructive, and time- and labor-consuming. This study reports on the use of Raman spectroscopy (RS) for completely non-invasive and non-destructive assessment of nutrient content of potato tubers. We also show that RS can be used to identify nine different potato varieties, as well as determine the origin of their cultivation. The portable nature of Raman-based identification of potato offers the possibility to perform such analysis directly upon potato harvesting to enable quick quality evaluation. Graphical abstract.

Defocused Spatially Offset Raman Spectroscopy in Media of Different Optical Properties for Biomedical Applications Using a Commercial Spatially Offset Raman Spectroscopy Device

In this study, we show how defocused spatially offset Raman spectroscopy (SORS) can be employed to recover chemical information from media of biomedical significance within sealed plastic transfusion and culture bags using a commercial SORS instrument. We demonstrate a simple approach to recover subsurface spectral information through a transparent barrier by optimizing the spatial offset of the defocused beam. The efficiency of the measurements is assessed in terms of the SORS ratio and signal-to-noise ratio (S/N) through a simple manual approach and an ordinary least squares model. By comparing the results for three different biological samples (red blood cell concentrate, pooled red cell supernatant and a suspension of Jurkat cells), we show that there is an optimum value of the offset parameter which yields the maximum S/N depending on the barrier material and optical properties of the ensemble contents. The approach was developed in the context of biomedical applications but is generally applicable to any three-layer system consisting of turbid content between transparent thin plastic barriers (i.e., front and back bag surfaces), particularly where the analyte of interest is dilute or not a strong scatterer.

Non-invasive depth determination of inclusion in biological tissues using spatially offset Raman spectroscopy with external calibration

Spatially Offset Raman Spectroscopy (SORS) allows chemical characterisation of biological tissues at depths enabling in vivo localization of biomarkers for early disease diagnosis.

From single cells to complex tissues in applications of surface-enhanced Raman scattering

This tutorial review explores how three of the most common methods for introducing nanoparticles to single cells for surface-enhanced Raman scattering measurements can be adapted for experiments with complex tissues.

Simple Defocused Fiber Optic Volume Probe for Subsurface Raman Spectroscopy in Turbid Media

We investigated the ability to perform deep subsurface Raman spectroscopy in turbid media using a simple fiber optic volume probe. Being able to collect Raman signals from regions deep within a biological sample provides the ability to noninvasively study underlying living tissue and tissue engineered constructs with high chemical specificity. Spatially offset Raman spectroscopy has shown great potential for obtaining subsurface Raman signals in biological samples. The applicability of the method for in vivo studies depends on the system complexity and small size probes are often desirable. Most real-time studies on human patients utilizing Raman spectroscopy have been performed with easy-to-handle miniaturized probes. Here we show both experimentally and theoretically that the sampling depth from a simple volume probe can be controlled by changing the probe to sample distance effectively suppressing Raman and fluorescence contributions from shallow sample layers while favoring the collection of signals from deeper layers. Relative spectral intensities as function of probe to sample distance were investigated for layered phantoms of poly(methyl methacrylate) and trans-stilbene and compared with theory. The volume probe was then utilized for the collection of spectra from phantoms mimicking in vivo transcutaneous measurement configurations of bone and engineered scaffold as well as from an ex vivo sample of bone and soft tissue. Together the results show that Raman fiber optic volume probes can be utilized for subsurface Raman spectroscopy in turbid media, providing a simple alternative to spatially offset Raman systems for, e.g., noninvasive monitoring and studying mineralized tissue and implanted scaffolds in vivo.

Applications of Raman spectroscopy in the development of cell therapies: state of the art and future perspectives

This comprehensive review article discusses current and future perspectives of Raman spectroscopy-based analyses of cell therapy processes and products.

Advanced Nanotechnology Leading the Way to Multimodal Imaging-Guided Precision Surgical Therapy

Surgical resection is the primary and most effective treatment for most patients with solid tumors. However, patients suffer from postoperative recurrence and metastasis. In the past years, emerging nanotechnology has led the way to minimally invasive, precision and intelligent oncological surgery after the rapid development of minimally invasive surgical technology. Advanced nanotechnology in the construction of nanomaterials (NMs) for precision imaging-guided surgery (IGS) as well as surgery-assisted synergistic therapy is summarized, thereby unlocking the advantages of nanotechnology in multimodal IGS-assisted precision synergistic cancer therapy. First, mechanisms and principles of NMs to surgical targets are briefly introduced. Multimodal imaging based on molecular imaging technologies provides a practical method to achieve intraoperative visualization with high resolution and deep tissue penetration. Moreover, multifunctional NMs synergize surgery with adjuvant therapy (e.g., chemotherapy, immunotherapy, phototherapy) to eliminate residual lesions. Finally, key issues in the development of ideal theranostic NMs associated with surgical applications and challenges of clinical transformation are discussed to push forward further development of NMs for multimodal IGS-assisted precision synergistic cancer therapy.

Optical Imaging Approaches to Investigating Radiation Resistance

Radiation therapy is frequently the first line of treatment for over 50% of cancer patients. While great advances have been made in improving treatment response rates and reducing damage to normal tissue, radiation resistance remains a persistent clinical problem. While hypoxia or a lack of tumor oxygenation has long been considered a key factor in causing treatment failure, recent evidence points to metabolic reprogramming under well-oxygenated conditions as a potential route to promoting radiation resistance. In this review, we present recent studies from our lab and others that use high-resolution optical imaging as well as clinical translational optical spectroscopy to shine light on the biological basis of radiation resistance. Two-photon microscopy of endogenous cellular metabolism has identified key changes in both mitochondrial structure and function that are specific to radiation-resistant cells and help promote cell survival in response to radiation. Optical spectroscopic approaches, such as diffuse reflectance and Raman spectroscopy have demonstrated functional and molecular differences between radiation-resistant and sensitive tumors in response to radiation. These studies have uncovered key changes in metabolic pathways and present a viable route to clinical translation of optical technologies to determine radiation resistance at a very early stage in the clinic.