ABSTRACT
Spatially offset Raman spectroscopy (SORS) is typically used to non-invasively investigate stratified samples that possess features on a millimeter scale, whereas micro-SORS usually deals with micrometer-thick layered samples. However, there are many instances where these boundaries are intertwined, sometimes indicating the possibility of using both techniques as well as circumstances that present mutual exclusion to their applicability. The aim of this study is to establish an application protocol that provides better insight into their suitability for deployment in various scenarios. The differences and similarities between the two approaches are investigated highlighting their strengths and limitations considering both theoretical and practical aspects. Diverse available parameters entail prospects and restrictions of both techniques and give rise to specific instrumental effects, namely, the overlap between the collection and excitation areas, the percentage of collected area for a given spatial offset, and the accuracy in the definition of the spatial offset (spread effect). These aspects are studied and exemplified on mockup samples relevant to the field of cultural heritage. The samples are characterized by high compositional complexity comprising features ranging from micrometer to millimeter scales. The conclusions reached are also relevant to other scientific areas such as biomedical, forensic, or energy harvest.
ABSTRACT
Honey authentication is a complex process which traditionally requires costly and time-consuming analytical techniques not readily available to the producers. This study aimed to develop non-invasive sensor methods coupled with a multivariate data analysis to detect the type and percentage of exogenous sugar adulteration in UK honeys. Through-container spatial offset Raman spectroscopy (SORS) was employed on 17 different types of natural honeys produced in the UK over a season. These samples were then spiked with rice and sugar beet syrups at the levels of 10%, 20%, 30%, and 50% w/w. The data acquired were used to construct prediction models for 14 types of honey with similar Raman fingerprints using different algorithms, namely PLS-DA, XGBoost, and Random Forest, with the aim to detect the level of adulteration per type of sugar syrup. The best-performing algorithm for classification was Random Forest, with only 1% of the pure honeys misclassified as adulterated and <3.5% of adulterated honey samples misclassified as pure. Random Forest was further employed to create a classification model which successfully classified samples according to the type of adulterant (rice or sugar beet) and the adulteration level. In addition, SORS spectra were collected from 27 samples of heather honey (24 Calluna vulgaris and 3 Erica cinerea) produced in the UK and corresponding subsamples spiked with high fructose sugar cane syrup, and an exploratory data analysis with PCA and a classification with Random Forest were performed, both showing clear separation between the pure and adulterated samples at medium (40%) and high (60%) adulteration levels and a 90% success at low adulteration levels (20%). The results of this study demonstrate the potential of SORS in combination with machine learning to be applied for the authentication of honey samples and the detection of exogenous sugars in the form of sugar syrups. A major advantage of the SORS technique is that it is a rapid, non-invasive method deployable in the field with potential application at all stages of the supply chain.
ABSTRACT
Noninvasive detection of surface-enhanced Raman spectroscopy (SERS) signals from deep within tissue represents a common challenge in many biological and clinical applications including disease diagnosis and therapy monitoring. Such signals are typically weak and not readily discernible from often much larger Raman and fluorescence background signals (e.g., from surrounding tissue). Consequently, suboptimal sensitivity in the detection of SERS signals is often achieved in these situations. Similar issues can arise in SERS measurements in other diffusely scattering samples and complex matrices. Here, we propose a novel concept, active SERS, for the efficient retrieval of SERS signals from deep within complex matrices such as biological tissues that mitigates these issues. It relies on applying an external perturbation to the sample to alter the SERS signal from nanoparticles (NPs) deep inside the matrix. A measurement with and without, or before and after, such perturbation then can provide powerful contrasting data enabling an effective elimination of the matrix signals to reveal more clearly the desired SERS signal without the interfering background and associated artifacts. The concept is demonstrated using ultrasound (US) as an external source of perturbation and SERS NPs inserted deep within a heterogeneous tissue phantom mimicking a cluster of NPs accumulated within a small target lesion. The overall SERS signal intensity induced by the applied US perturbation decreased by â¼21% and the SERS signal contrast was considerably improved by eliminating subtraction artifacts present in a conventional measurement performed at a neighboring spatial location in a heterogeneous tissue sample. Although the technique was demonstrated with SERS gold NPs with a standard Raman label, it is envisaged that active SERS NPs (both the nanoscale metal geometry and Raman label) could be specifically designed to deliver an augmented response to the external stimulus to further enhance the achievable SERS signal contrast and yield even greater improvement in detection sensitivity. The method was demonstrated using transmission Raman spectroscopy; however, it is also applicable to other Raman implementations including spatially offset Raman spectroscopy and conventional Raman spectroscopy performed both at depth and at surfaces of complex matrices.
Subject(s)
Internet , Spectrum Analysis, Raman , Spectrum Analysis, Raman/methods , Humans , Databases, FactualABSTRACT
This study explores the possibility of using microspatially offset Raman spectroscopy (micro-SORS) imaging to reconstruct noninvasively letters and figures hidden by opaque layers. Micro-SORS experiments were conducted on mockup samples that mimic real situations encountered in the cultural heritage field, such as sealed letters with inaccessible text and original documents. Subsurface images were obtained using both the characteristic Raman bands of the hidden compounds and their different optical properties from the remaining matrix. In the latter case, contrast obtained through observing a difference in the overall spectral intensity and fluorescence profile rather than any specific Raman bands were used to track the images within the hidden layer. This approach opens new prospects for the use of micro-SORS in heritage science, with applications in the field that include the study of objects covered by opaque overlayers not only through their Raman signatures but also through differences in their optical properties (e.g., fluorescence emission, absorption).
ABSTRACT
Substandard (including degraded) and falsified (SF) vaccines are a relatively neglected issue with serious global implications for public health. This has been highlighted during the rapid and widespread rollout of COVID-19 vaccines. There has been increasing interest in devices to screen for SF non-vaccine medicines including tablets and capsules to empower inspectors and standardise surveillance. However, there has been very limited published research focussed on repurposing or developing new devices for screening for SF vaccines. To our knowledge, rapid diagnostic tests (RDTs) have not been used for this purpose but have important potential for detecting falsified vaccines. We performed a proof-in-principle study to investigate their diagnostic accuracy using a diverse range of RDT-vaccine/falsified vaccine surrogate pairs. In an initial assessment, we demonstrated the utility of four RDTs in detecting seven vaccines. Subsequently, the four RDTs were evaluated by three blinded assessors with seven vaccines and four falsified vaccines surrogates. The results provide preliminary data that RDTs could be used by multiple international organisations, national medicines regulators and vaccine manufacturers/distributors to screen for falsified vaccines in supply chains, aligned with the WHO global 'Prevent, Detect and Respond' strategy.
Subject(s)
Counterfeit Drugs , Vaccines , Humans , Rapid Diagnostic Tests , COVID-19 Vaccines , Public HealthABSTRACT
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.
Subject(s)
Artificial Intelligence , Neural Networks, Computer , Principal Component Analysis , Spectrum Analysis, Raman/methodsABSTRACT
Preventing, detecting, and responding to substandard and falsified vaccines is of critical importance for ensuring the safety, efficacy, and public trust in vaccines. This is of heightened importance in context of public health crisis, such as the COVID-19 pandemic, in which extreme world-wide shortages of vaccines provided a fertile ground for exploitation by falsifiers. Here, a proof-of-concept study explored the feasibility of using a handheld Spatially Offset Raman Spectroscopy (SORS) device to authenticate COVID-19 vaccines through rapid analysis of unopened vaccine vials. The results show that SORS can verify the chemical identity of dominant excipients non-invasively through vaccine vial walls. The ability of SORS to identify potentially falsified COVID-19 vaccines was demonstrated by measurement of surrogates for falsified vaccines contained in vaccine vials. In all cases studied, the SORS technique was able to differentiate between surrogate samples from the genuine COVISHIELD™ vaccine. The genuine vaccines tested included samples from six batches across two manufacturing sites to account for any potential variations between batches or manufacturing sites. Batch and manufacturing site variations were insignificant. In conjunction with existing security features, for example on labels and packaging, SORS provided an intrinsic molecular fingerprint of the dominant excipients of the vaccines. The technique could be extended to other COVID-19 and non-COVID-19 vaccines, as well as other liquid medicines. As handheld and portable SORS devices are commercially available and widely used for other purposes, such as airport security, they are rapidly deployable non-invasive screening tools for vaccine authentication.
Subject(s)
COVID-19 , Spectrum Analysis, Raman , Humans , Spectrum Analysis, Raman/methods , COVID-19 Vaccines , Excipients , Pandemics , COVID-19/prevention & controlABSTRACT
Raman spectroscopy has found its way into a wide range of applications and is successfully applied for qualitative and quantitative studies. Despite significant technical progress over the last few decades, there are still some challenges that limit its more widespread usage. This paper presents a holistic approach to addressing simultaneously the problems of fluorescence interference, sample heterogeneity, and laser-induced sample heating. Long wavelength shifted excitation Raman difference spectroscopy (SERDS) at 830â nm excitation combined with wide-area illumination and sample rotation is presented as a suitable approach for the investigation of selected wood species. Wood as a natural specimen represents a well-suited model system for our study as it is fluorescent, heterogeneous, and susceptible to laser-induced modifications. Two different subacquisition times (50 and 100â ms) and two sample rotation speeds (12 and 60â r/min) were exemplarily assessed. Results demonstrate that SERDS can effectively separate the Raman spectroscopic fingerprints of the wood species balsa, beech, birch, hickory, and pine from intense fluorescence interference. Sample rotation in conjunction with 1â mm-diameter wide-area illumination was suitable to obtain representative SERDS spectra of the wood species within 4.6â s. Using partial least squares discriminant analysis, a classification accuracy of 99.4% for the five investigated wood species was realized. This study highlights the large potential of SERDS combined with wide-area illumination and sample rotation for the effective analysis of fluorescent, heterogeneous, and thermally sensitive specimens in a wide range of application areas.
Subject(s)
Spectrum Analysis, Raman , Wood , Spectrum Analysis, Raman/methods , Lighting , Rotation , Discriminant AnalysisABSTRACT
In this work we demonstrate an advanced concept of a charge-shifting charge-coupled device (CCD) read-out combined with shifted excitation Raman difference spectroscopy (SERDS) capable of operating at up to 10â kHz acquisition rates for the effective mitigation of fast-evolving interfering backgrounds in Raman spectroscopy. This rate is 10-fold faster than that achievable with an instrument we described previously and is overall 1000-fold faster than possible with conventional spectroscopic CCDs capable of operating at up to â¼10 Hz rates. The speed enhancement was realized by incorporating a periodic mask at the internal slit of an imaging spectrometer permitting a smaller shift of the charge on the CCD (8 pixels) to be required during the cyclic shifting process compared with the earlier design which employed an 80-pixel shift. The higher acquisition speed enables the more accurate sampling of the two SERDS spectral channels, enabling it to effectively tackle highly challenging situations with rapidly evolving interfering fluorescence backgrounds. The performance of the instrument is evaluated for heterogeneous fluorescent samples which are moved rapidly in front of the detection system aiming at the differentiation of chemical species and their quantification. The performance of the system is compared with that of the earlier 1â kHz design and a conventional CCD operated at its maximum rate of 5.4 Hz as previously. In all situations tested, the newly developed 10â kHz system outperformed the earlier variants. The 10â kHz instrument can benefit a number of prospective applications including: disease diagnosis where high sensitivity mapping of complex biological matrices in the presence of natural fluorescence bleaching restricts achievable limits of detection; accurate data acquisition from moving heterogeneous samples (or moving a handheld instrument in front of the sample during data acquisition) or data acquisition under varying ambient light conditions (e.g., due to casting shadows, sample or instrument movement). Other beneficial scenarios include monitoring rapidly evolving Raman signals in the presence of largely static background signals such as in situations where a heterogeneous sample is moving rapidly in front of a detection system (e.g., a conveyor belt) in the presence of static ambient light.
Subject(s)
Spectrum Analysis, Raman , Spectrum Analysis, Raman/methods , Spectrometry, Fluorescence/methodsABSTRACT
Diffuse Raman spectroscopy (DRS) allows subsurface molecular analysis of optically turbid samples. Numerical modeling of light propagation was used as a method for improving the design of an DRS instrument to maximize the signal to noise ratio (SNR) while ensuring safe laser exposure parameters required for in-vivo measurements. Experimental validation of the model was performed on both phantom samples and disks implanted postmortem to mimic the typical response to foreign bodies (formation of a fibrotic capsule around an implant). A reduction of laser exposure of over 1500-fold was achieved over previous studies whilst maintaining the same Raman collection rates and reaching the safe power density of 3â mW/mm2. The validation of this approach in a subcutaneous implant in a mouse cadaver showed a further improvement of 1.5-fold SNR, with a thickness limit of detection for the fibrotic layer of 23 µm, under the same acquisition times. In the animal body, a thickness limit of detection of 16 µm was achieved. These results demonstrate the feasibility of numerical model-based optimization for DRS, and that the technique can be improved sufficiently to be used for in-vivo measurement of collagenous capsule formation as a result of the foreign body response in murine models.
ABSTRACT
The purpose of this study is to determine whether age-related changes to tendon matrix molecules can be detected using Raman spectroscopy. Raman spectra were collected from human Achilles (n = 8) and tibialis anterior (n = 8) tendon tissue excised from young (17 ± 3 years) and old (72 ± 7 years) age groups. Normalised Raman spectra underwent principal component analysis (PCA), to objectively identify differences between age groups and tendon types. Certain Raman band intensities were correlated with levels of advanced glycation end-product (AGE) collagen crosslinks, quantified using conventional destructive biochemistry techniques. Achilles and tibialis anterior tendons in the old age group demonstrated significantly higher overall Raman intensities and fluorescence levels compared to young tendons. PCA was able to distinguish young and old age groups and different tendon types. Raman intensities differed significantly for several bands, including those previously associated with AGE crosslinks, where a significant positive correlation with biochemical measures was demonstrated. Differences in Raman spectra between old and young tendon tissue and correlation with AGE crosslinks provides the basis for quantifying age-related chemical modifications to tendon matrix molecules in intact tissue. Our results suggest that Raman spectroscopy may provide a powerful tool to assess tendon health and vitality in the future.
Subject(s)
Achilles Tendon , Spectrum Analysis, Raman , Humans , Spectrum Analysis, Raman/methods , Collagen , Glycation End Products, Advanced , Muscle, SkeletalABSTRACT
Detection of solid tumours through tissue- from depths relevant to humans- has been a significant challenge for biomedical Raman spectroscopy. The combined use of surface enhanced Raman scattering (SERS) imaging agents with deep Raman spectroscopy (DRS), i.e., surface enhanced deep Raman spectroscopy (SEDRS), offer prospects for overcoming such obstacles. In this study, we investigated the maximum detection depth through which the retrieval of SERS signal of a passively targeted biphenyl-4-thiol tagged gold nanoparticle (NP) imaging agent, injected subcutaneously into a mouse bearing breast cancer tumour, was possible. A compact 830 nm set-up with a hand-held probe and the flexibility of switching between offset, transmission and conventional Raman modalities was developed for this study. In vivo injection of the above SERS NP primary dose allowed surface tumour detection, whereas additional post mortem NP booster dose was required for detection of deeply seated tumours through heterogeneous animal tissue (comprising of proteins, fat, bone, organs, blood, and skin). The highest detection depth of 71 mm was probed using transmission, translating into a ~40% increase in detection depth compared to earlier reports. Such improvements in detection depth along with the inherent Raman chemical sensitivity brings SEDRS one step closer to future clinical cancer imaging technology.
Subject(s)
Metal Nanoparticles , Neoplasms , Animals , Bone and Bones , Gold/chemistry , Metal Nanoparticles/chemistry , Mice , Spectrum Analysis, Raman/methodsABSTRACT
The development of new effective cancer treatment methods has attracted much attention, mainly due to the limited efficacy and considerable side effects of currently used cancer treatment methods such as radiation therapy and chemotherapy. Photothermal therapy based on the use of plasmonically resonant metallic nanoparticles has emerged as a promising technique to eradicate cancer cells selectively. In this method, plasmonic nanoparticles are first preferentially uptaken by a tumor and then selectively heated by exposure to laser radiation with a specific plasmonic resonant wavelength, to destroy the tumor whilst minimizing damage to adjacent normal tissue. However, several parameters can limit the effectiveness of photothermal therapy, resulting in insufficient heating and potentially leading to cancer recurrence. One of these parameters is the patient's pain sensation during the treatment, if this is performed without use of anesthetic. Pain can restrict the level of applicable laser radiation, cause an interruption to the treatment course and, as such, affect its efficacy, as well as leading to a negative patient experience and consequential general population hesitancy to this type of therapy. Since having a comfortable and painless procedure is one of the important treatment goals in the clinic, along with its high effectiveness, and due to the relatively low number of studies devoted to this specific topic, we have compiled this review. Moreover, non-invasive and painless methods for temperature measurement during photothermal therapy (PTT), such as Raman spectroscopy and nanothermometry, will be discussed in the following. Here, we firstly outline the physical phenomena underlying the photothermal therapy, and then discuss studies devoted to photothermal cancer treatment concerning pain management and pathways for improved efficiency of photothermal therapy whilst minimizing pain experienced by the patient.
ABSTRACT
The dye distribution within a photo-electrode is a key parameter in determining the performances of dye-sensitized photon-to-electron conversion devices, such as dye-sensitized solar cells (DSSCs). A traditional, depth profiling investigation by destructive means including cross-sectional sampling is unsuitable for large quality control applications in manufacturing processes. Therefore, a non-destructive monitoring of the dye depth profile is required, which is the first step toward a non-destructive evaluation of the internal degradation of the device in the field. Here, we present a conceptual demonstration of the ability to monitor the dye depth profile within the light active layer of DSSCs by non-destructive means with high chemical specificity using a recently developed non-destructive/non-invasive Raman method, micro-spatially offset Raman spectroscopy (micro-SORS). Micro-SORS is able to probe through turbid materials, providing the molecular identification of compounds located under the surface, without the need of resorting to a cross-sectional analysis. The study was performed on the photo-electrode of DSSCs. This represents the first demonstration of the micro-SORS concept in the solar cell area as well as, more generally, the application of micro-SORS to the thinnest layer to date. A sample set has been prepared with varying concentrations of the dye and the thickness of the matrix consisting of a titanium dioxide layer. The results showed that micro-SORS can unequivocally discriminate between the homogeneous and inhomogeneous dye depth profiles. Moreover, micro-SORS outcomes have been compared with the results obtained with destructive time-of-flight secondary ion mass spectrometry measurements. The results of the two techniques are in good agreement, confirming the reliability of micro-SORS analysis. Therefore, this study is expected to pave the way for establishing a wider and more effective monitoring capability in this important field.
Subject(s)
Coloring Agents , Cross-Sectional Studies , Electrodes , Reproducibility of Results , TitaniumABSTRACT
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.
Subject(s)
Lasers , Spectrum Analysis, Raman , Polymers , Spectrum Analysis, Raman/methodsABSTRACT
Spatially offset Raman spectroscopy (SORS) is a technique for interrogating the subsurface composition of turbid samples noninvasively. This study generically addresses a fundamental question relevant to a wide range of SORS studies, which is how deep SORS probes for any specific spatial offset when analyzing a turbid sample or, in turn, what magnitude of spatial offset one should select to probe a specific depth. This issue is addressed by using Monte Carlo simulations, under the assumption of negligible absorption, which establishes that the key parameter governing the extent of the probed zone for a point-like illumination and point-like collection SORS geometry is the reduced scattering coefficient of the medium. This can either be deduced from literature data or directly estimated from a SORS measurement by evaluating the Raman intensity profile from multiple spatial offsets. Once this is known, the extent of the probed zone can be determined for any specific SORS spatial offset using the Monte Carlo simulation results presented here. The proposed method was tested using experimental data on stratified samples by analyzing the signal detected from a thin layer that was moved through a stack of layers using both non-absorbing and absorbing samples. The proposed simple methodology provides important additional information on SORS measurements with direct relevance to a wide range of SORS applications including biomedical, pharmaceutical, security, forensics, and cultural heritage.
ABSTRACT
We propose a new method for estimating the reduced scattering coefficient, µs', of turbid homogeneous samples using Spatially Offset Raman Spectroscopy (SORS). The concept is based around the variation of Raman signal with SORS spatial offset that is strongly µs'-dependent, as such, permitting the determination of µs'. The evaluation is carried out under the assumptions that absorption is negligible at the laser and Raman wavelengths and µs' is approximately the same for those two wavelengths. These conditions are often satisfied for samples analyzed in the NIR region of the spectrum where SORS is traditionally deployed. Through a calibration procedure on a PTFE model sample, it was possible to estimate the µs' coefficient of different turbid samples with an error (RMSEP) below 18%. The knowledge of µs' in the NIR range is highly valuable for facilitating accurate numerical simulations to optimize illumination and collection geometries in SORS, to derive in-depth information about the properties of SORS measurements or in other photon applications, dependent on photon propagation in turbid media with general impact across fields such as biomedical, pharmaceutical, security, forensic, and cultural sciences.
ABSTRACT
The desire for portable Raman spectrometers is continuously driving the development of novel spectrometer architectures where miniaturisation can be achieved without the penalty of a poorer detection performance. Spatial heterodyne spectrometers are emerging as potential candidates for challenging the dominance of traditional grating spectrometers, thanks to their larger etendue and greater potential for miniaturisation. This paper provides a generic analytical model for estimating and comparing the detection performance of Raman spectrometers based on grating spectrometer and spatial heterodyne spectrometer designs by deriving the analytical expressions for the performance estimator (signal-to-noise ratio, SNR) for both types of spectrometers. The analysis shows that, depending on the spectral characteristics of the Raman light and on the values of some instrument-specific parameters, the ratio of the SNR estimates for the two spectrometers (RSNR) can vary as much as by two orders of magnitude. Limit cases of these equations are presented for a subset of spectral regimes which are of practical importance in real-life applications of Raman spectroscopy. In particular, under the experimental conditions where the background signal is comparable or larger than the target Raman line and shot noise is the dominant noise contribution, the value of RSNR is, to a first order of approximation, dependent solely on the relative values of each spectrometer's etendue and on the number of row pixels in the detector array. For typical values of the key instrument-specific parameters (e.g., etendue, number of pixels, spectral bandwidth), the analysis shows that spatial heterodyne spectrometer-based Raman spectrometers have the potential to compete with compact grating spectrometer designs for delivering in a much smaller footprint (10-30 times) levels of detection performance that are approximately only five to ten times poorer.
ABSTRACT
Obtaining molecular information deeper within optically turbid samples is valuable in many applications. However, in many cases this is challenging, in particular when the sample elicits strong laser-induced fluorescence emission. Here, we investigated the use of time-gated and micro-spatially offset Raman spectroscopy (micro-SORS) based on spectral multiplexing detection to obtain sub-surface molecular analysis and imaging for both fluorescing and non-fluorescing samples. The multiplexed spectral detection achieved with a digital micromirror device (DMD) allowed fast acquisition of the time-gated signals to enable three-dimensional Raman mapping (raster scanning in the lateral x,y plane and using time-of-flight calibration for the axial z-direction). Sub-millimeter resolution molecular depth mapping was achieved with dwell times on the order of seconds per pixel. To suppress fluorescence backgrounds and enhance Raman bands, time-gated Raman spectroscopy was combined with micro-SORS to recover Raman signals of red pigments placed behind a layer of optically turbid material. Using a defocusing micro-SORS approach, both fluorescence and Raman signals from the surface layers were further suppressed, which enhanced the Raman signals from the deeper sublayers containing the pigment. These results demonstrate that time-gated Raman spectroscopy based on spectral multiplexed detection, and in combination with micro-SORS, is a powerful technique for sub-surface molecular analysis and imaging, which may find practical applications in medical imaging, cultural heritage, forensics, and industry.