Spatially offset Raman spectroscopy for biomedical applications

Raman spectrometer with vertical flow method for solutions containing organic solvents

The vertical flow (VF) method improves generation and collection efficiency in Raman spectroscopy. It enhances all Raman signals, including undesired signals of organic solvents having a considerably large Raman cross section. We constructed a Raman spectrometer using the VF method to overcome this drawback and introduced a spatial line rejection mask to eliminate unnecessary bands. In addition, the design of the VF unit was improved to resist organic solvents. A VF unit with a 60-µm pinhole enhanced the signal 168 times. The spatial mask effectively eliminated the large Raman bands of the solvent and enabled a longer exposure time. The increase in the dynamic range improved the signal-to-noise ratio by 10 % in methanol and acetonitrile measurements. Raman spectrometer with the VF method and spatial mask enables us to record the Raman spectrum of solute molecules without the disturbance of solvent bands.

Label-Free Fiber-Optic Raman Spectroscopy for Intravascular Coronary Atherosclerosis and Plaque Detection

The rupture of atherosclerotic plaques remains one of the leading causes of morbidity and mortality worldwide. The plaques have certain pathological characteristics including a fibrous cap, inflammation, and extensive lipid deposition in a lipid core. Various invasive and noninvasive imaging techniques can interrogate structural aspects of atheroma; however, the composition of the lipid core in coronary atherosclerosis and plaques cannot be accurately detected. Fiber-optic Raman spectroscopy has the capability of in vivo rapid and accurate biomarker detection as an emerging omics technology. Previous studies demonstrated that an intravascular Raman spectroscopic technique may assess and manage the therapeutic and medication strategies intraoperatively. The Raman spectral information identified plaque depositions consisting of lipids, triglycerides, and cholesterol esters as the major components by comparing normal region and early plaque formation region with histology. By focusing on the composition of plaques, we could identify the subgroups of plaques accurately and rapidly by Raman spectroscopy. Collectively, this fiber-optic Raman spectroscopy opens up new opportunities for coronary atherosclerosis and plaque detection, which would assist optimal surgical strategy and instant postoperative decision-making. In this paper, we will review the advancement of label-free fiber-optic Raman probe spectroscopy and its applications of coronary atherosclerosis and atherosclerotic plaque detection.

Spatially Offset Raman Spectroscopy toward In Vivo Assessment of the Adipose Tissue in Cardiometabolic Pathologies

Spatially offset Raman spectroscopy (SORS) enhanced the capabilities of Raman spectroscopy for the depth-resolved analysis of biological and diffusely scattering samples. This technique offers selective probing of subsurface layers, providing molecular insights without invasive procedures. While SORS has found application in biomedical research, up to now, studies have focused mainly on the detection of mineralization of bones and tissues. Herein, for the first time, SORS is used to assess the soft, organic tissue beneath the skin's surface. In this study, we demonstrate the diagnostic utility of a hand-held SORS device for evaluating the chemical composition of the adipose tissue. We compared perigonadal white adipose tissue (gWAT) in a murine model of atherosclerosis, heart failure, and high-fat diet (HFD) induced obesity. Our results reveal distinct chemical differences in gWAT between HFD-fed and control mice, showcasing the potential of SORS for intravital adipose tissue phenotype characterization. Furthermore, our findings underscore the effectiveness of SORS as a valuable tool for noninvasive assessment of the adipose tissue composition, holding potential diagnostic significance for metabolic disorders.

Live chicken egg embryos as an alternative in vivo tumour model for deep surface enhanced Raman spectroscopy

Live chicken egg embryos offer new opportunities for evaluation and continuous monitoring of tumour growth for in vivo studies compared to traditional rodent models. Here, we report the first use of surface enhanced Raman scattering (SERS) mapping and surface enhanced spatially offset Raman scattering (SESORS) for the detection and localisation of targeted gold nanoparticles in live chicken egg embryos bearing a glioblastoma tumour.

Regulation of gut microbiota and serum neurotransmitters in mice by Streptococcus thermophilus GA8- and Lacticaseibacillus rhamnosus HAO9-fermented milk containing high levels of gamma-aminobutyric acid

BACKGROUND

Gamma-aminobutyric acid (GABA) is an important neurotransmitter in the human body, with several negative emotions reported as being associated with GABA dysregulation. This study investigates the safety and modulatory effects of GABA-enriched milk, fermented by Streptococcus thermophilus GA8 and Lacticasebacillus rhamnosus HAO9, on the gut microbiota and neurotransmitter profiles in mice.

RESULTS

Through rigorous culturing and fermentation processes, we achieved consistent GABA production in milk, with concentrations reaching 4.6 and 8.5 g L-1 for GA8-fermented and co-fermented milk, respectively, after 48 h. Using SPF male C57BL/6J mice, we administered either mono-culture or combined-culture milk treatments and monitored physiological impacts. The treatments did not affect mouse body weight but induced significant changes in gut microbiota composition. Beta diversity analysis revealed distinct microbial profiles between treatment groups, highlighting fermentation-specific microbial shifts, such as an increase in Verrucomicrobia for the GA8 group and a modulation in Saccharibacteria_genera_incertae_sedis for the GA8 + HAO9 group. Serum neurotransmitter levels were elevated in both treatment groups, with significant increases in l-glutamine, l-tryptophan and, notably, serotonin hydrochloride in the GA8 + HAO9 group. Correlation analysis identified a positive association between specific bacterial genera and neurotransmitter levels, suggesting a probiotic effect on neuroactive substances.

CONCLUSION

These findings suggest that fermented milk has potential as a probiotic supplement for mood improvement and stress relief, highlighting its role in modulating the gut-brain axis. © 2024 Society of Chemical Industry.

In Situ Imaging of Subcutaneous Drug Delivery Systems Using Microspatially Offset Low-Frequency Raman Spectroscopy

The noninvasive in situ monitoring of the status of drug retention and implant integrity of subcutaneous implants would allow optimization of therapy and avoid periods of subtherapeutic delivery kinetics. A proof-of principle study was conducted to determine the use of microspatially offset low-frequency Raman spectroscopy (micro-SOLFRS) for nonintrusive in situ analysis of subcutaneous drug delivery systems. Caffeine was used as the model drug, and it was embedded in a circular-shape Soluplus matrix via vacuum compression molding. For the exploratory analysis, prototype implants were positioned underneath skin tissue samples, and various caffeine concentrations (1-50% w/w) and micro-SOLFRS displacement settings (Δz = 0-8 mm) were tested from the pseudo three-dimensional (3D)-imaging perspective. This format allowed the optimization of real-time micro-SOLFRS analysis of implants through skin tissue that was embedded in an agarose hydrogel. Notably, this analytical approach allowed the temporal and spatial erosion of the implant and solid-state transformations of caffeine to be distinguished. The spectrometric results correlated with complementary high-performance liquid chromatography (HPLC) determination of changes in drug concentration, illustrating drug dissipation/diffusion characteristics. The discovered capability of micro-SOLFRS for in situ measurements of drugs and implants makes it attractive for biomedical diagnostics that, ultimately, could result in development of a new point-of-care technology.

In vivo imaging using surface enhanced spatially offset raman spectroscopy (SESORS): balancing sampling frequency to improve overall image acquisition

In the field of optical imaging, the ability to image tumors at depth with high selectivity and specificity remains a challenge. Surface enhanced resonance Raman scattering (SERRS) nanoparticles (NPs) can be employed as image contrast agents to specifically target cells in vivo; however, this technique typically requires time-intensive point-by-point acquisition of Raman spectra. Here, we combine the use of "spatially offset Raman spectroscopy" (SORS) with that of SERRS in a technique known as "surface enhanced spatially offset resonance Raman spectroscopy" (SESORRS) to image deep-seated tumors in vivo. Additionally, by accounting for the laser spot size, we report an experimental approach for detecting both the bulk tumor, subsequent delineation of tumor margins at high speed, and the identification of a deeper secondary region of interest with fewer measurements than are typically applied. To enhance light collection efficiency, four modifications were made to a previously described custom-built SORS system. Specifically, the following parameters were increased: (i) the numerical aperture (NA) of the lens, from 0.2 to 0.34; (ii) the working distance of the probe, from 9 mm to 40 mm; (iii) the NA of the fiber, from 0.2 to 0.34; and (iv) the fiber diameter, from 100 μm to 400 μm. To calculate the sampling frequency, which refers to the number of data point spectra obtained for each image, we considered the laser spot size of the elliptical beam (6 × 4 mm). Using SERRS contrast agents, we performed in vivo SESORRS imaging on a GL261-Luc mouse model of glioblastoma at four distinct sampling frequencies: par-sampling frequency (12 data points collected), and over-frequency sampling by factors of 2 (35 data points collected), 5 (176 data points collected), and 10 (651 data points collected). In comparison to the previously reported SORS system, the modified SORS instrument showed a 300% improvement in signal-to-noise ratios (SNR). The results demonstrate the ability to acquire distinct Raman spectra from deep-seated glioblastomas in mice through the skull using a low power density (6.5 mW/mm2) and 30-times shorter integration times than a previous report (0.5 s versus 15 s). The ability to map the whole head of the mouse and determine a specific region of interest using as few as 12 spectra (6 s total acquisition time) is achieved. Subsequent use of a higher sampling frequency demonstrates it is possible to delineate the tumor margins in the region of interest with greater certainty. In addition, SESORRS images indicate the emergence of a secondary tumor region deeper within the brain in agreement with MRI and H&E staining. In comparison to traditional Raman imaging approaches, this approach enables improvements in the detection of deep-seated tumors in vivo through depths of several millimeters due to improvements in SNR, spectral resolution, and depth acquisition. This approach offers an opportunity to navigate larger areas of tissues in shorter time frames than previously reported, identify regions of interest, and then image the same area with greater resolution using a higher sampling frequency. Moreover, using a SESORRS approach, we demonstrate that it is possible to detect secondary, deeper-seated lesions through the intact skull.

Biosensing Platforms for Cardiac Biomarker Detection

Myocardial infarction (MI) is a cardiovascular disease that occurs when there is an elevated demand for myocardial oxygen as a result of the rupture or erosion of atherosclerotic plaques. Globally, the mortality rates associated with MI are steadily on the rise. Traditional diagnostic biomarkers employed in clinical settings for MI diagnosis have various drawbacks, prompting researchers to investigate fast, precise, and highly sensitive biosensor platforms and technologies. Biosensors are analytical devices that combine biological elements with physicochemical transducers to detect and quantify specific compounds or analytes. These devices play a crucial role in various fields including healthcare, environmental monitoring, food safety, and biotechnology. Biosensors developed for the detection of cardiac biomarkers are typically electrochemical, mass, and optical biosensors. Nanomaterials have emerged as revolutionary components in the field of biosensing, offering unique properties that significantly enhance the sensitivity and specificity of the detection systems. This review provides a comprehensive overview of the advancements and applications of nanomaterial-based biosensing systems. Beginning with an exploration of the fundamental principles governing nanomaterials, we delve into their diverse properties, including but not limited to electrical, optical, magnetic, and thermal characteristics. The integration of these nanomaterials as transducers in biosensors has paved the way for unprecedented developments in analytical techniques. Moreover, the principles and types of biosensors and their applications in cardiovascular disease diagnosis are explained in detail. The current biosensors for cardiac biomarker detection are also discussed, with an elaboration of the pros and cons of existing platforms and concluding with future perspectives.

Calibration of Dual-Channel Raman Spectrometer via Optical Frequency Comb

The portable Raman spectrometer boasts portability, rapid analysis, and high flexibility. It stands as a crucial and powerful technical tool for analyzing the chemical composition of samples, whether biological or non-biological, across diverse fields. To improve the resolution of grating spectrometers and ensure a wide spectral range, many spectrometer systems have been designed with double-grating structures. However, the impact of external forces, such as installation deviations and inevitable collisions, may cause differences between the actual state of the internal spectrometer components and their theoretical values. Therefore, spectrometers must be calibrated to establish the relationship between the wavelength and the pixel positions. The characteristic peaks of commonly used calibration substances are primarily distributed in the 200-2000 cm-1 range. The distribution of characteristic peaks in other wavenumber ranges is sparse, especially for spectrometers with double-channel spectral structures and wide spectral ranges. This uneven distribution of spectral peaks generates significant errors in the polynomial fitting results used to calibrate spectrometers. Therefore, to satisfy the calibration requirements of a dual-channel portable Raman spectrometer with a wide spectral range, this study designed a calibration method based on an optical frequency comb, which generates dense and uniform comb-like spectral signals at equal intervals. The method was verified experimentally and compared to the traditional calibration method of using a mercury-argon lamp. The results showed that the error bandwidth of the calibration results of the proposed method was significantly smaller than that of the mercury-argon lamp method, thus demonstrating a substantial improvement in the calibration accuracy.

In Vivo Assessment of Bone Quality Without X-rays

PURPOSE OF REVIEW

This review summarizes recent advances in the assessment of bone quality using non-X-ray techniques.

RECENT FINDINGS

Quantitative ultrasound (QUS) provides multiple measurements of bone characteristics based on the propagation of sound through bone, the attenuation of that sound, and different processing techniques. QUS parameters and model predictions based on backscattered signals can discriminate non-fracture from fracture cases with accuracy comparable to standard bone mineral density (BMD). With advances in magnetic resonance imaging (MRI), bound water and pore water, or a porosity index, can be quantified in several long bones in vivo. Since such imaging-derived measurements correlate with the fracture resistance of bone, they potentially provide new BMD-independent predictors of fracture risk. While numerous measurements of mineral, organic matrix, and bound water by Raman spectroscopy correlate with the strength and toughness of cortical bone, the clinical assessment of person's bone quality using spatially offset Raman spectroscopy (SORS) requires advanced spectral processing techniques that minimize contaminating signals from fat, skin, and blood. Limiting exposure of patients to ionizing radiation, QUS, MRI, and SORS has the potential to improve the assessment of fracture risk and track changes of new therapies that target bone matrix and micro-structure.

Spectral effects and enhancement quantification in healthy human saliva with surface-enhanced Raman spectroscopy using silver nanopillar substrates

OBJECTIVES

Raman spectroscopy as a diagnostic tool for biofluid applications is limited by low inelastic scattering contributions compared to the fluorescence background from biomolecules. Surface-enhanced Raman spectroscopy (SERS) can increase Raman scattering signals, thereby offering the potential to reduce imaging times. We aimed to evaluate the enhancement related to the plasmonic effect and quantify the improvements in terms of spectral quality associated with SERS measurements in human saliva.

METHODS

Dried human saliva was characterized using spontaneous Raman spectroscopy and SERS. A fabrication protocol was implemented leading to the production of silver (Ag) nanopillar substrates by glancing angle deposition. Two different imaging systems were used to interrogate saliva from 161 healthy donors: a custom single-point macroscopic system and a Raman micro-spectroscopy instrument. Quantitative metrics were established to compare spontaneous RS and SERS measurements: the Raman spectroscopy quality factor (QF), the photonic count rate (PR), the signal-to-background ratio (SBR).

RESULTS

SERS measurements acquired with an excitation energy four times smaller than with spontaneous RS resulted in improved QF, PR values an order of magnitude larger and a SBR twice as large. The SERS enhancement reached 100×, depending on which Raman bands were considered.

CONCLUSIONS

Single-point measurement of dried saliva with silver nanopillars substrates led to reproducible SERS measurements, paving the way to real-time tools of diagnosis in human biofluids.

Current Trends of Raman Spectroscopy in Clinic Settings: Opportunities and Challenges

Early clinical diagnosis, effective intraoperative guidance, and an accurate prognosis can lead to timely and effective medical treatment. The current conventional clinical methods have several limitations. Therefore, there is a need to develop faster and more reliable clinical detection, treatment, and monitoring methods to enhance their clinical applications. Raman spectroscopy is noninvasive and provides highly specific information about the molecular structure and biochemical composition of analytes in a rapid and accurate manner. It has a wide range of applications in biomedicine, materials, and clinical settings. This review primarily focuses on the application of Raman spectroscopy in clinical medicine. The advantages and limitations of Raman spectroscopy over traditional clinical methods are discussed. In addition, the advantages of combining Raman spectroscopy with machine learning, nanoparticles, and probes are demonstrated, thereby extending its applicability to different clinical phases. Examples of the clinical applications of Raman spectroscopy over the last 3 years are also integrated. Finally, various prospective approaches based on Raman spectroscopy in clinical studies are surveyed, and current challenges are discussed.

A database of computed Raman spectra of inorganic compounds with accurate hybrid functionals

Raman spectroscopy is widely applied in identifying local structures in materials, but the interpretation of Raman spectra is non-trivial. An accurate computational database of reference spectra calculated with a consistent level of theory can significantly aid in interpreting measured Raman spectra. Here, we present a database of Raman spectra of inorganic compounds calculated with accurate hybrid functionals in density functional theory. Raman spectra were obtained by calculating dynamical matrices and polarizability tensors for structures from the Inorganic Crystal Structure Database. The calculated Raman spectra and other phonon properties (e.g., infrared spectra) are stored in a MongoDB database publicly shared through a web application. We assess the accuracy of our Raman calculations by statistically comparing ~80 calculated spectra with an existing experimental Raman database. To date, the database contains 161 compounds and is continuously growing as we add more materials computed with our automated workflow.

Guided principal component analysis (GPCA): a simple method for improving detection of a known analyte

There is increasing interest in the application of Raman spectroscopy in a medical setting, ranging from supporting real-time clinical decisions e.g. surgical margins to assisting pathologists with disease classification. However, there remain a number of barriers for adoption in the medical setting due to the increased complexity of probing highly heterogeneous, dynamic biological materials. This inherent challenge can also limit the deployment of higher level analytical approaches such as Artificial Intelligence (AI) including convolutional neural networks (CNN), as there is a lack of a ground truth required for training purposes i.e. in complex clinical samples. Principal component analysis (PCA) is an unsupervised data reduction approach (orthogonal linear transformation) that has been used extensively in spectroscopy for 30+ years, due to its capability to simplify analysis of complex spectroscopic data. However, due to PCA being unsupervised features will inherently appear mixed and their rank may vary between experiments. Here we propose Guided PCA (GPCA), a simple approach that allows PCA to be guided with spectral data to ensure a consistent rank of a key target moiety by the inclusion of a reference (guiding) spectrum to the data set. This simplifies analysis, increases robustness of PCA analysis and improves quantification and the limits of detection and decreases RMSE.

Assessment of spatially offset Raman spectroscopy to detect differences in bone matrix quality

Since spatially offset Raman spectroscopy (SORS) can acquire biochemical measurements of tissue quality through light scattering materials, we investigated the feasibility of this technique to acquire Raman bands related to the fracture resistance of bone. Designed to maximize signals at different offsets, a SORS probe was used to acquire spectra from cadaveric bone with and without skin-like tissue phantoms attenuating the light. Autoclaving the lateral side of femur mid-shafts from 5 female and 5 male donors at 100 °C and again at 120 °C reduced the yield stress of cortical beams subjected to three-point bending. It did not affect the volumetric bone mineral density or porosity. Without tissue phantoms, autoclaving affected more Raman characteristics of the organic matrix when determined by peak intensity ratios, but fewer matrix properties depended on the three offsets (5 mm, 6 mm, and 7 mm) when determined by band area ratios. The cut-off in the thickness of the tissue phantom layers was ∼4 mm for most properties, irrespective of offset. Matching trends when spectra were acquired without phantom layers between bone and the probe, ν1PO43-/Amide III and ν1PO43-/(proline + OH-proline) were higher and lower in the non-treated bone than in the autoclaved bone, respectively, when the thickness of tissue phantom layers was 4 mm. The layers, however, caused a loss of sensitivity to autoclaving-related changes in ν3CO3/ν1PO43- and crystallinity. Without advanced post-processing of Raman spectra, SORS acquisition through turbid layers can detect changes in Raman properties of bone that accompany a loss in bone strength.

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.

"Afterglow" Photodynamic Therapy Based on Carbon Dots Embedded Silica Nanoparticles for Nondestructive Teeth Whitening

Teeth staining is a common dental health challenge in many parts of the world. Traditional teeth whitening techniques often lead to enamel damage and soft tissue toxicity due to the use of bioincompatible whitening reagents and continuous strong light irradiation. Herein, an "afterglow" photodynamic therapy (aPDT) for teeth whitening is proposed, which is realized by energy transition pathways of intersystem crossing. The covalent and hydrogen bonds formed by carbon dots embedded in silica nanoparticles (CDs@SiO2) facilitate the passage of energy through intersystem crossing (ISC), thereby extending the half-life of reactive oxygen species (ROS). The degradation efficiency of aPDT on dyes was higher than 95% in all cases. It can thoroughly whiten teeth by eliminating stains deep in the enamel without damaging the enamel structure and causing any tissue toxicity. This study illustrates the superiority of aPDT for dental whitening and the approach to exploring carbon-dots-based nanostructures in the treatment of oral diseases.

Practices, Potential, and Perspectives for Detecting Predisease Using Raman Spectroscopy

Raman spectroscopy shows great potential for practical clinical applications. By analyzing the structure and composition of molecules through real-time, non-destructive measurements of the scattered light from living cells and tissues, it offers valuable insights. The Raman spectral data directly link to the molecular composition of the cells and tissues and provides a "molecular fingerprint" for various disease states. This review focuses on the practical and clinical applications of Raman spectroscopy, especially in the early detection of human diseases. Identifying predisease, which marks the transition from a healthy to a disease state, is crucial for effective interventions to prevent disease onset. Raman spectroscopy can reveal biological processes occurring during the transition states and may eventually detect the molecular dynamics in predisease conditions.

The Emerging Role of Raman Spectroscopy as an Omics Approach for Metabolic Profiling and Biomarker Detection toward Precision Medicine

Omics technologies have rapidly evolved with the unprecedented potential to shape precision medicine. Novel omics approaches are imperative toallow rapid and accurate data collection and integration with clinical information and enable a new era of healthcare. In this comprehensive review, we highlight the utility of Raman spectroscopy (RS) as an emerging omics technology for clinically relevant applications using clinically significant samples and models. We discuss the use of RS both as a label-free approach for probing the intrinsic metabolites of biological materials, and as a labeled approach where signal from Raman reporters conjugated to nanoparticles (NPs) serve as an indirect measure for tracking protein biomarkers in vivo and for high throughout proteomics. We summarize the use of machine learning algorithms for processing RS data to allow accurate detection and evaluation of treatment response specifically focusing on cancer, cardiac, gastrointestinal, and neurodegenerative diseases. We also highlight the integration of RS with established omics approaches for holistic diagnostic information. Further, we elaborate on metal-free NPs that leverage the biological Raman-silent region overcoming the challenges of traditional metal NPs. We conclude the review with an outlook on future directions that will ultimately allow the adaptation of RS as a clinical approach and revolutionize precision medicine.

Trends in digital detection for the quality and safety of herbs using infrared and Raman spectroscopy

Herbs have been used as natural remedies for disease treatment, prevention, and health care. Some herbs with functional properties are also used as food or food additives for culinary purposes. The quality and safety inspection of herbs are influenced by various factors, which need to be assessed in each operation across the whole process of herb production. Traditional analysis methods are time-consuming and laborious, without quick response, which limits industry development and digital detection. Considering the efficiency and accuracy, faster, cheaper, and more environment-friendly techniques are highly needed to complement or replace the conventional chemical analysis methods. Infrared (IR) and Raman spectroscopy techniques have been applied to the quality control and safety inspection of herbs during the last several decades. In this paper, we generalize the current application using IR and Raman spectroscopy techniques across the whole process, from raw materials to patent herbal products. The challenges and remarks were proposed in the end, which serve as references for improving herb detection based on IR and Raman spectroscopy techniques. Meanwhile, make a path to driving intelligence and automation of herb products factories.

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.

Rapid, label-free histopathological diagnosis of liver cancer based on Raman spectroscopy and deep learning

Biopsy is the recommended standard for pathological diagnosis of liver carcinoma. However, this method usually requires sectioning and staining, and well-trained pathologists to interpret tissue images. Here, we utilize Raman spectroscopy to study human hepatic tissue samples, developing and validating a workflow for in vitro and intraoperative pathological diagnosis of liver cancer. We distinguish carcinoma tissues from adjacent non-tumour tissues in a rapid, non-disruptive, and label-free manner by using Raman spectroscopy combined with deep learning, which is validated by tissue metabolomics. This technique allows for detailed pathological identification of the cancer tissues, including subtype, differentiation grade, and tumour stage. 2D/3D Raman images of unprocessed human tissue slices with submicrometric resolution are also acquired based on visualization of molecular composition, which could assist in tumour boundary recognition and clinicopathologic diagnosis. Lastly, the potential for a portable handheld Raman system is illustrated during surgery for real-time intraoperative human liver cancer diagnosis.

Using beam-offset optical coherence tomography to reconstruct backscattered photon profiles in scattering media

Raster scanning imaging technologies capture least scattered photons (LSPs) and reject multiple scattered photons (MSPs) in backscattered photons to image the underlying structures of a scattering medium. However, MSPs can still squeeze into the images, resulting in limited imaging depth, degraded contrast, and significantly reduced lateral resolution. Great efforts have been made to understand how MSPs affect imaging performance through modeling, but the techniques for visualizing the backscattered photon profile (BSPP) in scattering media during imaging are unavailable. Here, a method of reconstructing BSPP is demonstrated using beam-offset optical coherence tomography (OCT), in which OCT images are acquired at offset positions from the illumination beam. The separation of LSPs and MSPs based on the BSPP enables quantification of imaging depth, contrast, and lateral resolution, as well as access to the depth-resolved modulated transfer function (MTF). This approach presents great opportunities for better retrieving tissue optical properties, correctly interpreting images, or directly using MTF as the feedback for adaptive optical imaging.

Trace Analysis of Gases and Liquids with Spontaneous Raman Scattering Based on the Integrating Sphere Principle

Spontaneous Raman scattering is an attractive optical technique for the analysis of gases and liquids; however, their low densities and notoriously weak scattering cross sections demand an enhancement of the spontaneous Raman scattering signal for detection. Here, we have developed a simple but highly effective and fast technique to enhance the signal of spontaneous Raman scattering from gases and liquids. The technique is developed based on the principle of an integrating sphere, which realizes the multiple pass actions of low-energy pump light and the collection of all Raman scattered light for a sample volume of 2 mL. By measuring the ambient air sample with an exposure time of 180 s, we found the experimental detection limit of our spontaneous Raman scattering setup can reach 3 ppm. CH₄ (<2 ppm) in air can be also examined by increasing the exposure time to 300 s. The performance of our setup used for the analysis of trace gases is further illustrated by characterizing ethane, propane, butane, and pentane in methane as well as isotopes of carbon dioxide. The results reveal that the detection limit of our setup for liquids can be improved by nearly 4 orders of magnitude compared to that of confocal Raman scattering spectroscopy with the same experimental conditions.

Label-Free Detection of DNA via Surface-Enhanced Raman Spectroscopy Using Au@Ag Nanoparticles

DNA is a building block of life; surface-enhanced Raman spectroscopy (SERS) has been broadly applied in the detection of biomolecules but there are challenges in obtaining high-quality DNA SERS signals under non-destructive conditions. Here, we developed a novel label-free approach for DNA detection based on SERS, in which the Au@AgNPs core-shell structure was selected as the enhancement substrate, which not only solved the problem of the weak enhancement effect of gold nanoparticles but also overcame the disadvantage of the inhomogeneous shapes of silver nanoparticles, thereby improving the sensitivity and reproducibility of the SERS signals of DNA molecules. The method obtained SERS signals for four DNA bases (A, C, G, and T) without destroying the structure, then further detected and qualified different specific structures of DNA molecules. These results promote the application of SERS technology in the field of biomolecular detection.

Reactive Species-Activatable AIEgens for Biomedical Applications

Precision medicine requires highly sensitive and specific diagnostic strategies with high spatiotemporal resolution. Accurate detection and monitoring of endogenously generated biomarkers at the very early disease stage is of extensive importance for precise diagnosis and treatment. Aggregation-induced emission luminogens (AIEgens) have emerged as a new type of excellent optical agents, which show great promise for numerous biomedical applications. In this review, we highlight the recent advances of AIE-based probes for detecting reactive species (including reactive oxygen species (ROS), reactive nitrogen species (RNS), reactive sulfur species (RSS), and reactive carbonyl species (RCS)) and related biomedical applications. The molecular design strategies for increasing the sensitivity, tuning the response wavelength, and realizing afterglow imaging are summarized, and theranostic applications in reactive species-related major diseases such as cancer, inflammation, and vascular diseases are reviewed. The challenges and outlooks for the reactive species-activatable AIE systems for disease diagnostics and therapeutics are also discussed. This review aims to offer guidance for designing AIE-based specifically activatable optical agents for biomedical applications, as well as providing a comprehensive understanding about the structure-property application relationships. We hope it will inspire more interesting researches about reactive species-activatable probes and advance clinical translations.

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.

Recent advances in the application of Raman spectroscopy for fish quality and safety analysis

Fish is one of the highly demanded aquatic products, and its quality and safety play a pivotal role in daily diet. However, the possible hazardous substance in perishable fish both in pre- and postharvest periods may decrease their values and pose a threat to public health. Laborious and expensive traditional methods drive the need of developing effective tools for detecting fish quality and safety properties in a rapid, nondestructive, and effective manner. Recent advances in Raman spectroscopy (RS) and surface-enhanced Raman scattering (SERS) have shown enormous potential in various aspects, which largely boost their applications in fish quality and safety evaluation. They have incomparable merits such as providing molecule fingerprint information and allowing for rapid, sensitive, and noninvasive detection with simple sample preparation. This review provides a comprehensive overview focusing on the applications of RS and SERS for fish quality assessment and safety inspection, highlighting the hazardous substance and illegal behavior both in preharvest (veterinary drug residues and environmental pollutants) and postharvest (freshness and illegal behavior) particularly. Moreover, challenges and prospects are also proposed to facilitate the vigorous development of RS and SERS. This review is aimed to emphasize potential opportunities for applying RS and SERS as promising techniques for routine food quality and safety detection. PRACTICAL APPLICATION: With these applications, it can be clearly indicated that RS and SERS are promising and powerful in fish quality and safety surveillance, thereby reducing the occurrence of commercial fraud and food safety issues. More efforts still should be concentrated on exploiting the high-performance Raman instruments, establishing a universal Raman database, developing reproducible SERS substrates and combing RS with other versatile spectral techniques to promote these technologies from laboratory to practice. It is hoped that this review should arouse more research interests in RS and SERS technologies for fish quality and safety surveillance, as well as provide more insights to make a breakthrough.

Model-Based Optimization of Laser Excitation and Detection Improves Spectral Contrast in Noninvasive Diffuse Raman Spectroscopy

Spatially offset Raman spectroscopy (SORS) is a powerful technique for subsurface molecular analysis of optically turbid samples. Numerical modeling of light propagation has been used to investigate opportunities for improving spectral contrast and signal to noise ratio when imaging regions of interest located 0-4.5 mm below the surface in polymer bulk material. Two- and three-dimensional modeling results demonstrate that when analyzing a certain region of interest (ROI) of finite lateral dimensions below the sample surface, offsetting both the laser source and detector in opposite directions from the central point of the ROI can increase the spectral contrast as compared to conventional SORS approach where the detector or the laser source is maintained at the central point (centered SORS). The outlined modeling results have been validated experimentally using a bulk polymer sample with a trans-stilbene ROI (cylinder) below the sample surface. The results show that modeling of the spatial configurations of laser excitation and detection points can be used to optimize the instrument configuration to achieve significant improvements (up to 2.25-fold) in performance over the conventional centered SORS. Such optimal solutions can then be implemented, for example, using robust fiber optic probes, moveable optics, or flexible spatial light modulator instruments for specific 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.

Raman microspectroscopy fingerprinting of organoid differentiation state

Background

Organoids, which are organs grown in a dish from stem or progenitor cells, model the structure and function of organs and can be used to define molecular events during organ formation, model human disease, assess drug responses, and perform grafting in vivo for regenerative medicine approaches. For therapeutic applications, there is a need for nondestructive methods to identify the differentiation state of unlabeled organoids in response to treatment with growth factors or pharmacologicals.

Methods

Using complex 3D submandibular salivary gland organoids developed from embryonic progenitor cells, which respond to EGF by proliferating and FGF2 by undergoing branching morphogenesis and proacinar differentiation, we developed Raman confocal microspectroscopy methods to define Raman signatures for each of these organoid states using both fixed and live organoids.

Results

Three separate quantitative comparisons, Raman spectral features, multivariate analysis, and machine learning, classified distinct organoid differentiation signatures and revealed that the Raman spectral signatures were predictive of organoid phenotype.

Conclusions

As the organoids were unlabeled, intact, and hydrated at the time of imaging, Raman spectral fingerprints can be used to noninvasively distinguish between different organoid phenotypes for future applications in disease modeling, drug screening, and regenerative medicine.

Supplementary Information

The online version contains supplementary material available at 10.1186/s11658-022-00347-3.

Salivary gland organoids have unique Raman signatures detectable with a confocal-based Raman imaging approach.

Raman signatures can be detected in unlabeled fixed or live organoids.

Raman spectral signatures effectively predict organoid phenotypes.

Raman-Guided Bronchoscopy: Feasibility and Detection Depth Studies Using Ex Vivo Lung Tissues and SERS Nanoparticle Tags

Image-guided and robotic bronchoscopy is currently under intense research and development for a broad range of clinical applications, especially for minimally invasive biopsy and surgery of peripheral pulmonary nodules or lesions that are frequently discovered by CT or MRI scans. Optical imaging and spectroscopic modalities at the near-infrared (NIR) window hold great promise for bronchoscopic navigation and guidance because of their high detection sensitivity and molecular/cellular specificity. However, light scattering and background interference are two major factors limiting the depth of tissue penetration of photons, and diseased lesions such as small tumors buried under the tissue surface often cannot be detected. Here we report the use of a miniaturized Raman device that is inserted into one of the bronchoscope channels for sensitive detection of “phantom” tumors using fresh pig lung tissues and surface-enhanced Raman scattering (SERS) nanoparticle tags. The ex vivo results demonstrate not only the feasibility of using Raman spectroscopy for endoscopic guidance, but also show that ultrabright SERS nanoparticles allow detection through a bronchial wall of 0.85 mm in thickness and a 5 mm-thick layer of lung tissue (approaching the fourth-generation airway). This work highlights the prospects and potential of Raman-guided bronchoscopy for minimally invasive imaging and detection of lung lesions.

The future of early cancer detection

A proactive approach to detecting cancer at an early stage can make treatments more effective, with fewer side effects and improved long-term survival. However, as detection methods become increasingly sensitive, it can be difficult to distinguish inconsequential changes from lesions that will lead to life-threatening cancer. Progress relies on a detailed understanding of individualized risk, clear delineation of cancer development stages, a range of testing methods with optimal performance characteristics, and robust evaluation of the implications for individuals and society. In the future, advances in sensors, contrast agents, molecular methods, and artificial intelligence will help detect cancer-specific signals in real time. To reduce the burden of cancer on society, risk-based detection and prevention needs to be cost effective and widely accessible.

Raman Spectroscopy in Prostate Cancer: Techniques, Applications and Advancements

Optical techniques are widely used tools in the visualisation of biological species within complex matrices, including biopsies, tissue resections and biofluids. Raman spectroscopy is an emerging analytical approach that probes the molecular signature of endogenous cellular biomolecules under biocompatible conditions with high spatial resolution. Applications of Raman spectroscopy in prostate cancer include biopsy analysis, assessment of surgical margins and monitoring of treatment efficacy. The advent of advanced Raman imaging techniques, such as stimulated Raman scattering, is creating opportunities for real-time in situ evaluation of prostate cancer. This review provides a focus on the recent preclinical and clinical achievements in implementing Raman-based techniques, highlighting remaining challenges for clinical applications. The research and clinical results achieved through in vivo and ex vivo Raman spectroscopy illustrate areas where these evolving technologies can be best translated into clinical practice.

PLGA-Gold Nanocomposite: Preparation and Biomedical Applications

A composite system consisting of both organic and inorganic nanoparticles is an approach to prepare a new material exhibiting “the best of both worlds”. In this review, we highlight the recent advances in the preparation and applications of poly(lactic-co-glycolic acid)-gold nanoparticles (PLGA-GNP). With its current clinically use, PLGA-based nanocarriers have promising pharmaceutical applications and can “extract and utilize” the fascinating optical and photothermal properties of encapsulated GNP. The resulting “golden polymeric nanocarrier” can be tracked, analyzed, and visualized using the encapsulated gold nanoprobes which facilitate a better understanding of the hosting nanocarrier’s pharmacokinetics and biological fate. In addition, the “golden polymeric nanocarrier” can reveal superior nanotherapeutics that combine both the photothermal effect of the encapsulated gold nanoparticles and co-loaded chemotherapeutics. To help stimulate more research on the development of nanomaterials with hybrid and exceptional properties, functionalities, and applications, this review provides recent examples with a focus on the available chemistries and the rationale behind encapsulating GNP into PLGA nanocarriers that has the potential to be translated into innovative, clinically applicable nanomedicine.

Improving SERS bioimaging of subcutaneous phantom in vivo with optical clearing

Surface-enhanced Raman scattering (SERS) has proven to be a promising technique for different types of imaging including preoperative and intraoperative in vivo tumor visualization. However, the strong scattering of the turbid tissue limits its use in subcutaneous areas. In this article, we used an optical clearing technique to improve the SERS signal from a subcutaneous tumor phantom. The phantom is a 2 mm sphere of calcium alginate with incorporated petal-like gap-enhanced Raman tags. The use of optical clearing increases the SERS signal target-to-background ratio for 5 times and allow to decrease the total imaging time for at least 10 times. In addition, SERS imaging assisted with optical clearing made it possible to more precisely determine the shape and boundaries of the implanted phantom. The combination of optical clearing and SERS is a promising strategy for the clinical imaging of subcutaneous objects that are usually shielded by dermal tissue.

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.

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.

Design and synthesis of gold nanostars-based SERS nanotags for bioimaging applications

Surface-enhanced Raman spectroscopy (SERS) nanotags hold a unique place among bioimaging contrast agents due to their fingerprint-like spectra, which provide one of the highest degrees of detection specificity. However, in order to achieve a sufficiently high signal intensity, targeting capabilities, and biocompatibility, all components of nanotags must be rationally designed and tailored to a specific application. Design parameters include fine-tuning the properties of the plasmonic core as well as optimizing the choice of Raman reporter molecule, surface coating, and targeting moieties for the intended application. This review introduces readers to the principles of SERS nanotag design and discusses both established and emerging protocols of their synthesis, with a specific focus on the construction of SERS nanotags in the context of bioimaging and theranostics.

Raman Nanotags-Guided Intraoperative Sentinel Lymph Nodes Precise Location with Minimal Invasion

The accurate positioning of sentinel lymph node (SLN) by tracers during surgery is an important prerequisite for SLN biopsy. A major problem of traditional tracers in SLN biopsy is the short surgery window due to the fast diffusion of tracers through the lymphatics, resulting in a misjudgment between SLN and second echelon lymph node (2nd LN). Here, a nontoxic Raman nanoparticle tracer, termed gap-enhanced Raman tags (GERTs), for the accurate intraoperative positioning of SLNs with a sufficient surgical time window is designed. In white New Zealand rabbit models, GERTs enable precise identification of SLNs within 10 min, as well as provide the surgeon with a more than 4 h time window to differentiate SLN and 2nd LN. In addition, the ultrahigh sensitivity of GERTs (detection limit is 0.5 × 10-12 m) allows detection of labeled SLNs before surgery, thereby providing preoperative positioning information for minimally invasive surgery. Comprehensive biosafety evaluations carried out in the context of the Food and Drug Administration and International Standard Organization demonstrate no significant toxicity of GERTs, which supports a promising clinical translation opportunity of GERTs for precise SLN identification in breast cancer.

Surface-enhanced Raman scattering (SERS) spectroscopy for prostate cancer diagnosis: A review

The present review focuses on the diagnosis of prostate cancer using surface enhanced Raman scattering (SERS) spectroscopy. On the basis of literature search, SERS-based analysis for prostate cancer detection of different sample types is reported in the present study. Prostate cancer is responsible for nearly one-tenth of all cell cancer deaths among men. Significant efforts have been dedicated to establish precise and sensitive monitoring techniques to detect prostate cancer biomarkers in different types of body samples. Among the various spectro-analytical techniques investigated to achieve this objective, SERS spectroscopy has been proven as a promising approach that provides noticeable enhancements of the Raman sensitivity when the target biomolecules interact with a nanostructured surface. The purpose of this review is to give a brief overview of the SERS-basedapproach and other spectro-analytical strategies being used for the detection and quantification of prostate cancer biomarkers. The revolutionary development of SERS methods for the diagnosis of prostate cancer has been discussed in more details based on the reported literature. It has been noticed that the SERS-based immunoassay presents reliable results for the prostate cancer quantification. The EC-SERS, which integrates electrochemistry with the SERS model, could also offer a potential ultrasensitive strategy, although its application in prostate cancer analysis has been still limited.

From Raman to SESORRS: moving deeper into cancer detection and treatment monitoring

Raman spectroscopy is a non-invasive technique that allows specific chemical information to be obtained from various types of sample. The detailed molecular information that is present in Raman spectra permits monitoring of biochemical changes that occur in diseases, such as cancer, and can be used for the early detection and diagnosis of the disease, for monitoring treatment, and to distinguish between cancerous and non-cancerous biological samples. Several techniques have been developed to enhance the capabilities of Raman spectroscopy by improving detection sensitivity, reducing imaging times and increasing the potential applicability for in vivo analysis. The different Raman techniques each have their own advantages that can accommodate the alternative detection formats, allowing the techniques to be applied in several ways for the detection and diagnosis of cancer. This feature article discusses the various forms of Raman spectroscopy, how they have been applied for cancer detection, and the adaptation of the techniques towards their use for in vivo cancer detection and in clinical diagnostics. Despite the advances in Raman spectroscopy, the clinical application of the technique is still limited and certain challenges must be overcome to enable clinical translation. We provide an outlook on the future of the techniques in this area and what we believe is required to allow the potential of Raman spectroscopy to be achieved for clinical cancer diagnostics.

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.

High-Resolution 18F-FDG PET/CT for Assessing Three-Dimensional Intraoperative Margins Status in Malignancies of the Head and Neck, a Proof-of-Concept

The surgical treatment of head and neck malignancies relies on the complete removal of tumoral tissue, while inadequate margins necessitate the use of adjuvant therapy. However, most positive margins are identified postoperatively as deep margins, and intraoperative identification of the deep positive margins could help achieve adequate surgical margins and decrease adjuvant therapies. To improve deep-margin identification, we investigated whether the use of high-resolution preclinical PET and CT could increase certainty about the surgical margins in three dimensions. Patients with a malignancy of the head and neck planned for surgical resection were administered a clinical activity of 4MBq/kg ¹⁸F-FDG approximately one hour prior to surgical initiation. Subsequently, the resected specimen was scanned with a micro-PET-CT imaging device, followed by histopathological assessment. Eight patients were included in the study and intraoperative PET/CT-imaging of 11 tumoral specimens and lymph nodes of three patients was performed. As a result of the increased resolution, differentiation between inflamed and dysplastic tissue versus malignant tissue was complicated in malignancies with increased peritumoral inflammation. The current technique allowed the three-dimensional delineation of ¹⁸F-FDG using submillimetric PET/CT imaging. While further optimization and patient stratification is required, clinical implementation could enable deep margin assessment in head and neck resection specimens.

Pseudo-3D Subsurface Imaging of Pharmaceutical Solid Dosage Forms Using Micro-spatially Offset Low-Frequency Raman Spectroscopy

A new combinatory Raman subtechnique of low-frequency and micro-spatially offset Raman spectroscopy (denoted micro-SOLFRS) is demonstrated via analysis of pharmaceutical solid dosage forms. A variety of different (multilayer/multicomponent) model systems comprising celecoxib, α-lactose (the anhydrous and monohydrate form), and polyvinylpyrrolidone (PVP) were probed to test the potency of this newly developed technique to, for example, provide qualitative and quantitative information on surface and subsurface layer characteristics, including their thicknesses as well as enable monitoring of surface-driven solid-state form transformations. A simultaneous collection of low- and, the more commonly used, mid-frequency data enabled a direct comparison between these spectral regions, where the low-frequency domain (hence, micro-SOLFRS) proved superior for every respective analysis carried out herein.