Multiplex imaging of live breast cancer tumour models through tissue using handheld surface enhanced spatially offset resonance Raman spectroscopy (SESORRS)

Advancing SERS as a quantitative technique: challenges, considerations, and correlative approaches to aid validation

Surface-enhanced Raman scattering (SERS) remains a significant area of research since it's discovery 50 years ago. The surface-based technique has been used in a wide variety of fields, most prominently in chemical detection, cellular imaging and medical diagnostics, offering high sensitivity and specificity when probing and quantifying a chosen analyte or monitoring nanoparticle uptake and accumulation. However, despite its promise, SERS is mostly confined to academic laboratories and is not recognised as a gold standard analytical technique. This is due to the variations that are observed in SERS measurements, mainly caused by poorly characterised SERS substrates, lack of universal calibration methods and uncorrelated results. To convince the wider scientific community that SERS should be a routinely used analytical technique, the field is now focusing on methods that will increase the reproducibility of the SERS signals and how to validate the results with more well-established techniques. This review explores the difficulties experienced by SERS users, the methods adopted to reduce variation and suggestions of best practices and strategies that should be adopted if one is to achieve absolute quantification.

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.

SERS in 3D cell models: a powerful tool in cancer research

Unraveling the cellular and molecular mechanisms underlying tumoral processes is fundamental for the diagnosis and treatment of cancer. In this regard, three-dimensional (3D) cancer cell models more realistically mimic tumors compared to conventional 2D cell cultures and are more attractive for performing such studies. Nonetheless, the analysis of such architectures is challenging because most available techniques are destructive, resulting in the loss of biochemical information. On the contrary, surface-enhanced Raman spectroscopy (SERS) is a non-invasive analytical tool that can record the structural fingerprint of molecules present in complex biological environments. The implementation of SERS in 3D cancer models can be leveraged to track therapeutics, the production of cancer-related metabolites, different signaling and communication pathways, and to image the different cellular components and structural features. In this review, we highlight recent progress in the use of SERS for the evaluation of cancer diagnosis and therapy in 3D tumoral models. We outline strategies for the delivery and design of SERS tags and shed light on the possibilities this technique offers for studying different cellular processes, through either biosensing or bioimaging modalities. Finally, we address current challenges and future directions, such as overcoming the limitations of SERS and the need for the development of user-friendly and robust data analysis methods. Continued development of SERS 3D bioimaging and biosensing systems, techniques, and analytical strategies, can provide significant contributions for early disease detection, novel cancer therapies, and the realization of patient-tailored medicine.

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.

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.

Advancing Brain Research through Surface-Enhanced Raman Spectroscopy (SERS): Current Applications and Future Prospects

Surface-enhanced Raman spectroscopy (SERS) has recently emerged as a potent analytical technique with significant potential in the field of brain research. This review explores the applications and innovations of SERS in understanding the pathophysiological basis and diagnosis of brain disorders. SERS holds significant advantages over conventional Raman spectroscopy, particularly in terms of sensitivity and stability. The integration of label-free SERS presents promising opportunities for the rapid, reliable, and non-invasive diagnosis of brain-associated diseases, particularly when combined with advanced computational methods such as machine learning. SERS has potential to deepen our understanding of brain diseases, enhancing diagnosis, monitoring, and therapeutic interventions. Such advancements could significantly enhance the accuracy of clinical diagnosis and further our understanding of brain-related processes and diseases. This review assesses the utility of SERS in diagnosing and understanding the pathophysiological basis of brain disorders such as Alzheimer's and Parkinson's diseases, stroke, and brain cancer. Recent technological advances in SERS instrumentation and techniques are discussed, including innovations in nanoparticle design, substrate materials, and imaging technologies. We also explore prospects and emerging trends, offering insights into new technologies, while also addressing various challenges and limitations associated with SERS in brain research.

Multiplexing potential of NIR resonant and non-resonant Raman reporters for bio-imaging applications

Multiplexed imaging, which allows for the interrogation of multiple molecular features simultaneously, is vital for addressing numerous challenges across biomedicine. Optically unique surface-enhanced Raman scattering (SERS) nanoparticles (NPs) have the potential to serve as a vehicle to achieve highly multiplexed imaging in a single acquisition, which is non-destructive, quantitative, and simple to execute. When using laser excitation at 785 nm, which allows for a lower background from biological tissues, near infrared (NIR) dyes can be used as Raman reporters to provide high Raman signal intensity due to the resonance effect. This class of imaging agents are known as surface-enhanced resonance Raman scattering (SERRS) NPs. Investigators have predominantly utilized two classes of Raman reporters in their nanoparticle constructs for use in biomedical applications: NIR-resonant and non-resonant Raman reporters. Herein, we investigate the multiplexing potential of five non-resonant SERS: BPE, 44DP, PTT, PODT, and BMMBP, and five NIR resonant SERRS NP flavors with heptamethine cyanine dyes: DTTC, IR-770, IR-780, IR-792, and IR-797, which have been extensively used for biomedical imaging applications. Although SERRS NPs display high Raman intensities, due to their resonance properties, we observed that non-resonant SERS NP concentrations can be quantitated by the intensity of their unique emissions with higher accuracy. Spectral unmixing of five-plex mixtures revealed that the studied non-resonant SERS NPs maintain their detection limits more robustly as compared to the NIR resonant SERRS NP flavors when introducing more components into a mixture.

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.

Challenges and opportunities for SERS in the infrared: materials and methods

In the wake of a global, heightened interest towards biomarker and disease detection prompted by the SARS-CoV-2 pandemic, surface enhanced Raman spectroscopy (SERS) positions itself again at the forefront of biosensing innovation. But is it ready to move from the laboratory to the clinic? This review presents the challenges associated with the application of SERS to the biomedical field, and thus, to the use of excitation sources in the near infrared, where biological windows allow for cell and through-tissue measurements. Two main tackling strategies will be discussed: (1) acting on the design of the enhancing substrate, which includes manipulation of nanoparticle shape, material, and supramolecular architecture, and (2) acting on the spectral collection set-up. A final perspective highlights the upcoming scientific and technological bets that need to be won in order for SERS to stably transition from benchtop to bedside.

Machine learning using convolutional neural networks for SERS analysis of biomarkers in medical diagnostics

Surface-enhanced Raman spectroscopy (SERS) has wide diagnostic applications because of narrow spectral features that allow multiplexed analysis. Machine learning (ML) has been used for non-dye-labeled SERS spectra but has not been applied to SERS dye-labeled materials with known spectral shapes. Here, we compare the performances of spectral decomposition, support vector regression, random forest regression, partial least squares regression, and convolutional neural network (CNN) for SERS "spectral unmixing" from a multiplexed mixture of 7 SERS-active "nanorattles" loaded with different dyes for mRNA biomarker detection. We showed that CNN most accurately determined relative contributions of each distinct dye-loaded nanorattle. CNN and comparative models were then used to analyze SERS spectra from a singleplexed, point-of-care assay detecting an mRNA biomarker for head and neck cancer in 20 samples. The CNN, trained on simulated multiplexed data, determined the correct dye contributions from the singleplex assay with RMSElabel = 6.42 × 10-2. These results demonstrate the potential of CNN-based ML to advance SERS-based diagnostics.

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.

Simultaneous Thermal and Spectroscopic Screening of Morphologically Complex Theranostic Gold Nanoparticles

Gold nanoparticles absorb light energy and convert it to thermal energy that transfers to the surrounding environment, making them potentially useful for the hyperthermic treatments well known as photothermal therapy (PTT). Further, it is well documented that noble metal nanoparticles are capable of significantly enhancing the Raman scattering of molecules attached to their surfaces, a technique which is termed surface-enhanced Raman scattering (SERS). SERS combined with PTT has the ability to locate nanoparticles at depth and trigger heat production, providing an effective methodology to both seek and destroy diseased tissues. While PTT and SERS are often used in tandem and there are several ways of individually measuring SERS and thermal output, there is currently no method available that pre-screens both properties prior to in vitro or in vivo application. In this work, we have designed a 3D printed platform capable of coupling a commercially available Raman probe to a sample cuvette for SERS and heat output to be monitored simultaneously. We have compared the performance of morphologically complex gold nanoparticles, nanostars (AuNSs) and nanoplates (AuNPLs), which are both well utilized in SERS and photothermal experiments; and measured the SERS activity originating from common Raman reporter analytes 4-mercaptobenzoic acid (MBA) and 1,4-benzenedithiol (BDT). We were able to show that the system effectively measures the thermal output and SERS activity of the particles and can evaluate the effect that multiple irradiation cycles have on the SERS signal.

Depth prediction of nanotags in tissue using surface enhanced spatially offset Raman scattering (SESORS)

A model for the prediction of the depth of two 'flavours' of surface enhanced Raman scattering (SERS) active nanotags embedded within porcine tissue is demonstrated using ratiometric analysis. Using a handheld spatially offset Raman (SORS) instrument, SESORS signals could be detected from nanotags at depths down to 48 mm for the first time using a backscattering SORS geometry.

Noninvasive and Highly Multiplexed Five-Color Tumor Imaging of Multicore Near-Infrared Resonant Surface-Enhanced Raman Nanoparticles In Vivo

In vivo multiplexed imaging aims for noninvasive monitoring of tumors with multiple channels without excision of the tissue. While most of the preclinical imaging has provided a number of multiplexing channels up to three, Raman imaging with surface-enhanced Raman scattering (SERS) nanoparticles was suggested to offer higher multiplexing capability originating from their narrow spectral width. However, in vivo multiplexed SERS imaging is still in its infancy for multichannel visualization of tumors, which require both sufficient multiplicity and high sensitivity concurrently. Here we create multispectral palettes of gold multicore-near-infrared (NIR) resonant Raman dyes-silica shell SERS (NIR-SERRS) nanoparticle oligomers and demonstrate noninvasive and five-plex SERS imaging of the nanoparticle accumulation in tumors of living mice. We perform the five-plex ratiometric imaging of tumors by varying the administered ratio of the nanoparticles, which simulates the detection of multiple biomarkers with different expression levels in the tumor environment. Furthermore, since this method does not require the excision of tumor tissues at the imaging condition, we perform noninvasive and longitudinal imaging of the five-color nanoparticles in the tumors, which is not feasible with current ex vivo multiplexed tissue analysis platforms. Our work surpasses the multiplicity limit of previous preclinical tumor imaging methods while keeping enough sensitivity for tumor-targeted in vivo imaging and could enable the noninvasive assessment of multiple biological targets within the tumor microenvironment in living subjects.

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.

In Vivo Fiber Optic Raman Spectroscopy of Muscle in Preclinical Models of Amyotrophic Lateral Sclerosis and Duchenne Muscular Dystrophy

Neuromuscular diseases result in muscle weakness, disability, and, in many instances, death. Preclinical models form the bedrock of research into these disorders, and the development of in vivo and potentially translational biomarkers for the accurate identification of disease is crucial. Spontaneous Raman spectroscopy can provide a rapid, label-free, and highly specific molecular fingerprint of tissue, making it an attractive potential biomarker. In this study, we have developed and tested an in vivo intramuscular fiber optic Raman technique in two mouse models of devastating human neuromuscular diseases, amyotrophic lateral sclerosis, and Duchenne muscular dystrophy (SOD1G93A and mdx, respectively). The method identified diseased and healthy muscle with high classification accuracies (area under the receiver operating characteristic curves (AUROC): 0.76-0.92). In addition, changes in diseased muscle over time were also identified (AUROCs 0.89-0.97). Key spectral changes related to proteins and the loss of α-helix protein structure. Importantly, in vivo recording did not cause functional motor impairment and only a limited, resolving tissue injury was seen on high-resolution magnetic resonance imaging. Lastly, we demonstrate that ex vivo muscle from human patients with these conditions produced similar spectra to those observed in mice. We conclude that spontaneous Raman spectroscopy of muscle shows promise as a translational research tool.

Spatially offset Raman spectroscopy for biomedical applications

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

Multiplex micro-SERS imaging of cancer-related markers in cells and tissues using poly(allylamine)-coated Au@Ag nanoprobes

Surface-enhanced Raman scattering (SERS) nanoprobes based on Au@Ag core@shell nanoparticles coated with poly(allylamine) were functionalized with small targeting molecules to evaluate simultaneously the level of expression of two cancer-related markers, both in cells and in tissues. The Au@Ag nanoparticles provide a high SERS signal enhancement in the visible range when combined with resonant Raman-active molecules. The poly(allylamine) coating plays a dual key role in (i) protecting the metal surface against the complex biological medium, leading to a stable signal of the Raman-active molecules, and (ii) enabling specific biofunctionalization through its amine functions. Using small targeting molecules linked to the polymer coating, two different nanoprobes (duplex approach) were designed. Each was able to specifically target a particular cancer-related marker: folate receptors (FRs) and sialic acid (SA). We demonstrate that the level of expression of these targeted markers can be evaluated following the SERS signal of the probes incubated on cells or tissues. The potential overexpression of folate receptors and of sialic acid was evaluated and measured in breast and ovarian cancerous tissue sections. In addition, FR and/or SA overexpression in the tumor region can be visualized with high contrast with respect to the healthy region and with high spatial accuracy consistent with histology by SERS imaging of the nanoprobe signal. Owing to the unique spectral signature of the designed nanoprobes, this approach offers an efficient tool for the spatially resolved, in situ measurement of the expression level of several cancer-related markers in tumors at the same time.Graphical abstract.

Present and Future of Surface-Enhanced Raman Scattering

The discovery of the enhancement of Raman scattering by molecules adsorbed on nanostructured metal surfaces is a landmark in the history of spectroscopic and analytical techniques. Significant experimental and theoretical effort has been directed toward understanding the surface-enhanced Raman scattering (SERS) effect and demonstrating its potential in various types of ultrasensitive sensing applications in a wide variety of fields. In the 45 years since its discovery, SERS has blossomed into a rich area of research and technology, but additional efforts are still needed before it can be routinely used analytically and in commercial products. In this Review, prominent authors from around the world joined together to summarize the state of the art in understanding and using SERS and to predict what can be expected in the near future in terms of research, applications, and technological development. This Review is dedicated to SERS pioneer and our coauthor, the late Prof. Richard Van Duyne, whom we lost during the preparation of this article.

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

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

Determination of inclusion depth in ex vivo animal tissues using surface enhanced deep Raman spectroscopy

This work presents recent developments in spatially offset and transmission Raman spectroscopy for noninvasive detection and depth prediction of a single SERS inclusion located deep inside ex vivo biological tissues. The concept exploits the differential attenuation of Raman bands brought about by their different absorption due to tissue constituents enabling to predict the inclusion depth. Four different calibration models are tested and evaluated to predict the depth of surface enhanced Raman scattering labelled nanoparticles, within an up to 40 mm slab of porcine tissue. An external measurement carried out in transmission mode, with a noninvasively built model on the analysed sample, is shown to be insensitive to variations of the overall thickness of the tissue yielding an average root-mean-square error of prediction of 6.7%. The results pave the way for future noninvasive deep Raman spectroscopy in vivo enabling to localise cancer biomarkers for an early diagnosis of multiple diseases.

Non-invasive In Vivo Imaging of Cancer Using Surface-Enhanced Spatially Offset Raman Spectroscopy (SESORS)

Rationale: The goal of imaging tumors at depth with high sensitivity and specificity represents a significant challenge in the field of biomedical optical imaging. 'Surface enhanced Raman scattering' (SERS) nanoparticles (NPs) have been employed as image contrast agents and can be used to specifically target cells in vivo. By tracking their unique "fingerprint" spectra, it becomes possible to determine their precise location. However, while the detection of SERS NPs is very sensitive and specific, conventional Raman spectroscopy imaging devices are limited in their inability to probe through tissue depths of more than a few millimetres, due to scattering and absorption of photons by biological tissues. Here, we combine the use of "Spatially Offset Raman spectroscopy" (SORS) with that of "surface-enhanced resonance Raman spectroscopy" (SERRS) in a technique known as "surface enhanced spatially offset resonance Raman spectroscopy" (SESO(R)RS) to image deep-seated glioblastoma multiforme (GBM) tumors in vivo in mice through the intact skull. Methods: A SORS imaging system was built in-house. Proof of concept SORS imaging was achieved using a PTFE-skull-tissue phantom. Imaging of GBMs in the RCAS-PDGF/N-tva transgenic mouse model was achieved through the use of gold nanostars functionalized with a resonant Raman reporter to create SERRS nanostars. These were then encapsulated in a thin silica shell and functionalized with a cyclic-RGDyK peptide to yield integrin-targeting SERRS nanostars. Non-invasive in vivo SORS image acquisition of the integrin-targeted nanostars was then performed in living mice under general anesthesia. Conventional non-SORS imaging was used as a direct comparison. Results: Using a low power density laser, GBMs were imaged via SESORRS in mice (n = 5) and confirmed using MRI and histopathology. The results demonstrate that via utilization of the SORS approach, it is possible to acquire clear and distinct Raman spectra from deep-seated GBMs in mice in vivo through the skull. SESORRS images generated using classical least squares outlined the tumors with high precision as confirmed via MRI and histology. Unlike SESORRS, conventional Raman imaging of the same areas did not provide a clear delineation of the tumor. Conclusion: To the best of our knowledge this is the first report of in vivo SESO(R)RS imaging. In a relevant brain tumor mouse model we demonstrate that this technique can overcome the limitations of conventional Raman imaging with regards to penetration depth. This work therefore represents a significant step forward in the potential clinical translation of SERRS nanoparticles for high precision cancer imaging.

Surface-Enhanced Raman Scattering Tags for Three-Dimensional Bioimaging and Biomarker Detection

We have recently witnessed a major improvement in the quality of nanoparticles encoded with Raman-active molecules (SERS tags). Such progress relied mainly on a major improvement of fabrication methods for building-blocks, resulting in widespread application of this powerful tool in various fields, with the potential to replace commonly used techniques, such as those based on fluorescence. We present hereby a brief Perspective on surface enhanced Raman scattering (SERS) tags, regarding their composition, morphology, and structure, and describe our own selection from the current state-of-the-art. We then focus on the main bioimaging applications of SERS tags, showing a gradual evolution from two-dimensional studies to three-dimensional analysis. Recent improvements in sensitivity and multiplexing ability have enabled great advancements toward in vivo applications, e.g., highlighting tumor boundaries to guide surgery. In addition, the high level of biomolecule sensitivity reached by SERS tags promises an expansion toward biomarker detection in cases for which traditional methods offer limited reliability, as a consequence of the frequently low analyte concentrations.

Surface enhanced resonance Raman spectroscopy (SERRS) for probing through plastic and tissue barriers using a handheld spectrometer

Through tissue imaging of a live breast cancer tumour model using handheld surface enhanced resonance Raman spectroscopy (SERRS).

Towards establishing a minimal nanoparticle concentration for applications involving surface enhanced spatially offset resonance Raman spectroscopy (SESORRS) in vivo

Detection of SERRS nanotags at picomolar concentrations through 5 mm of tissue using SESORS.