High wavenumber Raman spectroscopy for intraoperative assessment of breast tumour margins.

Optimal oncological results and patient outcomes are achieved in surgery for early breast cancer with breast conserving surgery (BCS) where this is appropriate. A limitation of BCS occurs when cancer is present at, or close, to the resection margin - termed a 'positive' margin - and re-excision is recommended to reduce recurrence rate. This is occurs in 17% of BCS in the UK and there is therefore a critical need for a way to assess margin status intraoperatively to ensure complete excision with adequate margins at the first operation. This study presents the potential of high wavenumber (HWN) Raman spectroscopy to address this. Freshly excised specimens from thirty patients undergoing surgery for breast cancer were measured using a surface Raman probe, and a multivariate classification model to predict normal versus tumour was developed from the data. This model achieved 77.1% sensitivity and 90.8% specificity following leave one patient out cross validation, with the defining features being differences in water content and lipid versus protein content. This demonstrates the feasibility of HWN Raman spectroscopy to facilitate future intraoperative margin assessment at specific locations. Clinical utility of the approach will require further research.

Exploration of utility of combined optical photothermal infrared and Raman imaging for investigating the chemical composition of microcalcifications in breast cancer.

Microcalcifications play an important role in cancer detection. They are evaluated by their radiological and histological characteristics but it is challenging to find a link between their morphology, their composition and the nature of a specific type of breast lesion. Whilst there are some mammographic features that are either typically benign or typically malignant often the appearances are indeterminate. Here, we explore a large range of vibrational spectroscopic and multiphoton imaging techniques in order to gain more information about the composition of the microcalcifications. For the first time, we validated the presence of carbonate ions in the microcalcifications by O-PTIR and Raman spectroscopy at the same time, the same location and the same high resolution (0.5 µm). Furthermore, the use of multiphoton imaging allowed us to create stimulated Raman histology (SRH) images which mimic histological images with all chemical information. In conclusion, we established a protocol for efficiently analysing the microcalcifications by iteratively refining the area of interest.

Surface enhanced deep Raman detection of cancer tumour through 71 mm of heterogeneous tissue.

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.

Infrared Spectroscopic Analysis in the Differentiation of Epithelial Misplacement From Adenocarcinoma in Sigmoid Colonic Adenomatous Polyps.

Purpose: The differential diagnosis of epithelial misplacement from invasive cancer in the colon is a challenging endeavour, augmented by the introduction of bowel cancer population screening. The main aim of the work is to test, as a proof-of concept study, the ability of the infrared spectroscopic imaging approach to differentiate epithelial misplacement from adenocarcinoma in sigmoid colonic adenomatous polyps. Methods: Ten samples from each of the four diagnostic groups, normal colonic mucosa, adenomatous polyps with low grade dysplasia, epithelial misplacement in adenomatous polyps and adenocarcinoma, were analysed using IR spectroscopic imaging and data processing methods. IR spectral images were subjected to data pre-processing and cluster analysis based segmentation to identify epithelial, connective tissue and stromal regions. Statistical analysis was carried out using principal component analysis and linear discriminant analysis based cross validation, to classify spectral features according to the pathology, and the diagnostic attributes were compared. Results: The combined 4-group classification model on an average showed a sensitivity of 64%, a specificity of 88% and an accuracy of 76% for prediction based on a 'single spectrum', whilst a 'majority-vote' prediction on an average showed a sensitivity of 73%, a specificity of 90% and an accuracy of 82%. The 2-group model, for the differential diagnosis of epithelial misplacement versus adenocarcinoma, showed an average sensitivity and specificity of 82.5% for prediction based on a 'single spectrum' whilst a 'majority-vote' classification showed an average sensitivity and specificity of 90%. A 92% area under the curve (AUC) value was obtained when evaluating the classifier using the Receiver Operating Characteristics (ROC) curves. Conclusions: IR spectroscopy shows promise in its ability to differentiate epithelial misplacement from adenocarcinoma in tissue sections, considered as one of the most challenging endeavours in population-wide diagnostic histopathology. Further studies with larger series, including cases with challenging diagnostic features are required to ascertain the capability of this modern digital pathology approach. In the long-term, IR spectroscopy based pathology which is relatively low-cost and rapid, could be a promising endeavour to consider for integration into the existing histopathology pathway, in particular for population based screening programmes where large number of samples are scrutinised.

Multiphoton imaging and Raman spectroscopy of the bovine vertebral endplate.

The interface between the intervertebral disc and the vertebral body is important to the discs' biomechanics and physiology, and is widely implicated in its pathology. This study aimed to explore biochemically and structurally the bony endplate, cartilage endplate and intervertebral disc, below the nucleus and below the annulus in healthy bovine tails. Multiphoton imaging and spontaneous Raman spectroscopy were employed. Raman spectroscopy provided relative quantification of mineral and matrix components across the vertebral endplate and its adjacent areas with microscopic spatial resolution. Microscopy utilising second-harmonic generation (SHG) and two-photon fluorescence (TPF) allowed for the structural identification of distinct endplate regions. The cartilage endplate was revealed as structurally distinct from both the bone and disc, supporting its biomechanical function as a transition zone between the soft and hard tissue components. The collagen fibres were continuous across the tidemark which defines the interface between the mineralised and non-mineralised regions of the endplate. Raman spectroscopy revealed gradients in phosphate and carbonate content through the depth of the endplate and also differences beneath the nucleus and annulus consistent with a higher rate of remodelling under the annulus.

Spatially Offset Raman Spectroscopy-How Deep?

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.

Estimating the Reduced Scattering Coefficient of Turbid Media Using Spatially Offset Raman Spectroscopy.

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.

Predicting the Refractive Index of Tissue Models Using Light Scattering Spectroscopy.

In this work, we report the application of Raman microspectroscopy for analysis of the refractive index of a range of tissue phantoms. Using both a custom-developed setup with visible laser source and a commercial microspectrometer with near infrared laser, we measured the Raman spectra of gelatin hydrogels at various concentrations. By building a calibration curve from measured refractometry data and Raman scattering intensity for different vibrational modes of the hydrogel, we were able to predict the refractive indices of the gels from their Raman spectra. This work highlights the importance of a correlative approach through Brillouin-Raman microspectroscopy for the mechano-chemical analysis of biologically relevant samples.

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.

Viscoelastic properties of biopolymer hydrogels determined by Brillouin spectroscopy: A probe of tissue micromechanics.

Many problems in mechanobiology urgently require characterization of the micromechanical properties of cells and tissues. Brillouin light scattering has been proposed as an emerging optical elastography technique to meet this need. However, the information contained in the Brillouin spectrum is still a matter of debate because of fundamental problems in understanding the role of water in biomechanics and in relating the Brillouin data to low-frequency macroscopic mechanical parameters. Here, we investigate this question using gelatin as a model system in which the macroscopic physical properties can be manipulated to mimic all the relevant biological states of matter, ranging from the liquid to the gel and the glassy phase. We demonstrate that Brillouin spectroscopy is able to reveal both the elastic and viscous properties of biopolymers that are central to the structure and function of biological tissues.

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

Spatially offset Raman spectroscopy (SORS) allows chemical characterisation of biological tissues at depths of up to two orders of magnitude greater than conventional Raman spectroscopy. In this study, we demonstrate the use of SORS for the non-invasive prediction of depth of an inclusion within turbid media (e.g. biological tissues) using only external calibration data sets, thus extending our previous approach that required internal calibration. As with the previous methodology, the concept is based on relative changes in Raman band intensities of the inclusion that are directly related to the path length of Raman photons travelling through the medium thereby encoding the information of depth of the inclusion. However, here the calibration model is created using data only from external measurements performed at the tissue surface. This new approach facilitates a fully non-invasive methodology applicable potentially to in vivo medical diagnosis without any a priori knowledge. Monte Carlo simulations of photon propagation have been used to provide insight into the relationship between the spatial offset and the photon path lengths inside the tissues enabling one to derive a general scaling factor permitting the use of spatial offset measurements for the depth prediction. The approach was validated by predicting the depth of surface-enhanced Raman scattering (SERS) labelled nanoparticles (NPs) acting as inclusions inside a slab of ex vivo porcine tissue yielding an average root mean square error of prediction of 7.3% with respect to the overall tissue thickness. Our results pave the way for future non-invasive deep Raman spectroscopy in vivo by enabling, for example, the localisation of cancer lesions or cancer biomarkers in early disease diagnosis and targeted treatments.

Translation of an esophagus histopathological FT-IR imaging model to a fast quantum cascade laser modality.

The technical progress in fast quantum cascade laser (QCL) microscopy offers a platform where chemical imaging becomes feasible for clinical diagnostics. QCL systems allow the integration of previously developed FT-IR-based pathology recognition models in a faster workflow. The translation of such models requires a systematic approach, focusing only on the spectral frequencies that carry crucial information for discrimination of pathologic features. In this study, we optimize an FT-IR-based histopathological method for esophageal cancer detection to work with a QCL system. We explore whether the classifier's performance is affected by paraffin presence from tissue blocks compared to removing it chemically. Working with paraffin-embedded samples reduces preprocessing time in the lab and allows samples to be archived after analysis. Moreover, we test, whether the creation of a QCL model requires a preestablished FTIR model or can be optimized using solely QCL measurements.

Optical characterization of porcine tissues from various organs in the 650-1100†nm range using time-domain diffuse spectroscopy.

We present a systematic characterization of the optical properties (µa and µs') of nine representative ex vivo porcine tissues over a broadband spectrum (650-1100 nm). We applied time-resolved diffuse optical spectroscopy measurements for recovering the optical properties of porcine tissues depicting a realistic representation of the tissue heterogeneity and morphology likely to be found in different ex vivo tissues. The results demonstrate a large spectral and inter-tissue variation of optical properties. The data can be exploited for planning or simulating ex vivo experiments with various biophotonics techniques, or even to construct artificial structures mimicking specific pathologies exploiting the wide assortment in optical properties.

Characterization of colorectal mucus using infrared spectroscopy: a potential target for bowel cancer screening and diagnosis.

Biological materials presenting early signs of cancer would be beneficial for cancer screening/diagnosis. In this respect, the suitability of potentially exploiting mucus in colorectal cancer was tested using infrared spectroscopy in combination with statistical modeling. Twenty-six paraffinized colon tissue biopsy sections containing mucus regions from 20 individuals (10 normal and 16 cancerous) were measured using mid-infrared spectroscopic imaging. A digital de-paraffinization, followed by cluster analysis driven digital color-coded multi-staining segmented the infrared images into various histopathological features such as epithelium, connective tissue, stroma, and mucus regions within the tissue sections. Principal component analysis followed by supervised linear discriminant analysis was carried out on pure mucus and epithelial spectra from normal and cancerous regions of the tissue. For the mucus-based classification, a sensitivity of 96%, a specificity of 83%, and an area under the curve performance of 95% was obtained. For the epithelial tissue-based classification, a sensitivity of 72%, a specificity of 88%, and an area under the curve performance of 89% was obtained. The mucus spectral profiles further showed contributions indicative of glycans including that of sialic acid changes between these pathology groups. The study demonstrates that infrared spectroscopic analysis of mucus discriminates colorectal cancers with high sensitivity. This concept could be exploited to develop screening/diagnostic approaches complementary to histopathology.

Brillouin microspectroscopy data of tissue-mimicking gelatin hydrogels.

Brillouin spectroscopy, based on the inelastic scattering of light from thermally driven acoustic waves or phonons [1], holds great promise in the field of life sciences as it provides functionally relevant micromechanical information in a contactless all-optical manner [2]. Due to the complexity of biological systems such as cells and tissues, which present spatio-temporal heterogeneities, interpretation of Brillouin spectra can be difficult. The data presented here were collected from gelatin hydrogels, used as tissue-mimicking model systems for Brillouin microspectroscopy measurements conducted using a lab-built Brillouin microscope with a dual-stage VIPA spectrometer. By varying the solute concentration in the range 4-18% (w/w), the macroscopic mechanical properties of the hydrogels can be tuned and the corresponding evolution in the Brillouin-derived longitudinal elastic modulus measured. An increase in Brillouin frequency shift with increasing solute concentration was observed, which was found to correlate with an increase in acoustic wave velocity and longitudinal modulus. The gels used here provide a viable model system for benchmarking and standardisation, and the data will be useful for spectrometer development and validation.

Diagnostic prospects and preclinical development of optical technologies using gold nanostructure contrast agents to boost endogenous tissue contrast.

Numerous developments in optical biomedical imaging research utilizing gold nanostructures as contrast agents have advanced beyond basic research towards demonstrating potential as diagnostic tools; some of which are translating into clinical applications. Recent advances in optics, lasers and detection instrumentation along with the extensive, yet developing, knowledge-base in tailoring the optical properties of gold nanostructures has significantly improved the prospect of near-infrared (NIR) optical detection technologies. Of particular interest are optical coherence tomography (OCT), photoacoustic imaging (PAI), multispectral optoacoustic tomography (MSOT), Raman spectroscopy (RS) and surface enhanced spatially offset Raman spectroscopy (SESORS), due to their respective advancements. Here we discuss recent technological developments, as well as provide a prediction of their potential to impact on clinical diagnostics. A brief summary of each techniques' capability to distinguish abnormal (disease sites) from normal tissues, using endogenous signals alone is presented. We then elaborate on the use of exogenous gold nanostructures as contrast agents providing enhanced performance in the above-mentioned techniques. Finally, we consider the potential of these approaches to further catalyse advances in pre-clinical and clinical optical diagnostic technologies.

Direct monitoring of light mediated hyperthermia induced within mammalian tissues using surface enhanced spatially offset Raman spectroscopy (T-SESORS).

Here we demonstrate light mediated heating of nanoparticles confined deep inside mammalian tissue, whilst directly monitoring their temperature non-invasively using a form of deep Raman spectroscopy, T-SESORS. One of the main barriers to the introduction of photo-thermal therapies (PTT) has been recognised as the inability to directly monitor the local temperature deep within the tissue at the point of therapy. Here Au nanoparticles with a Raman reporter molecule (temperature reporters) are used in combination with Au nanoshells (heat mediators) to provide simultaneously heating under NIR illumination and direct spectroscopic monitoring of local temperature deep within mammalian tissues. The surface enhanced Raman signal was read out at the tissue surface using a transmission geometry in this example and the temperature of the tissue was ascertained from the anti-Stokes to Stokes Raman reporter. This approach opens the prospect of non-invasive hyperthermia treatments with direct temperature feedback from deep inside within tissue, where nanoparticles can be used to both provide localised heating and accurately monitor the local temperature.

Liquid Biopsies in Lung Cancer: Four Emerging Technologies and Potential Clinical Applications.

Background: Liquid biopsies offer a promising alternative to tissue samples, providing non-invasive diagnostic approaches or serial monitoring of disease evolution. However, certain challenges remain, and the full potential of liquid biopsies has yet to be reached. Here we report several methodological approaches to interrogate liquid biopsies using circulating tumour cell (CTC) enumeration and characterisation, transcriptomics, Raman spectroscopy, and copy number instability (CNI) scores using blood samples of lung cancer (LC) patients. Methods: We choose LC; since it still is the most common cause of cancer-related mortality worldwide, and therefore there is a need for development of new non-invasive diagnostic/prognostic technologies. Changes in gene expression were assessed using RNA-seq, and in CTCs using ImageStream, an imaging flow-cytometer. CNI scores, from paired tissue/ctDNA were also explored. Raman spectroscopy was used to provide chemical fingerprints of plasma samples. Results: CTCs were detected in all LC patients (n = 10). We observed a significant increase in CTC levels in LC patients (n = 10) compared to controls (n = 21). A similar CNI was noted in the tissue and plasma of 2 patients, where higher CNI scores corresponded with poorer outcome. Significant changes in Raman spectra (carotenoid concentrations) were noted in LC patients (n = 20) compared to controls (n = 10). RNA-seq revealed differential expression of 21 genes between LC cases and controls in both LC tissue and blood samples. Conclusions: Liquid biopsies can potentially provide a more comprehensive picture of the disease compared to a single tissue biopsy. CTC enumeration is feasible and sensitive for LC patients. Molecular profiling of CTCs is also possible from total blood. CNI scores and Raman spectra require further investigation. Further work is being undertaken to explore these methods of detection in a larger LC cohort.

Age-Related Changes in Femoral Head Trabecular Microarchitecture.

Osteoporosis is a prevalent bone condition, characterised by low bone mineral density and increased fracture risk. Currently, the gold standard for identifying osteoporosis and increased fracture risk is through quantification of bone mineral density using dual energy X-ray absorption. However, many studies have shown that bone strength, and consequently the probability of fracture, is a combination of both bone mass and bone 'quality' (architecture and material chemistry). Although the microarchitecture of both non-fracture and osteoporotic bone has been previously investigated, many of the osteoporotic studies are constrained by factors such as limited sample number, use of ovariectomised animal models, and lack of male and female discrimination. This study reports significant differences in bone quality with respect to the microarchitecture between fractured and non-fractured human femur specimens. Micro-computed tomography was utilised to investigate the microarchitecture of femoral head trabecular bone from a relatively large cohort of non-fracture and fracture human donors. Various microarchitectural parameters have been determined for both groups, providing an understanding of the differences between fracture and non -fracture material. The microarchitecture of non-fracture and fracture bone tissue is shown to be significantly different for many parameters. Differences between sexes also exist, suggesting differences in remodelling between males and females in the fracture group. The results from this study will, in the future, be applied to develop a fracture model which encompasses bone density, architecture and material chemical properties for both female and male tissues.

Upconversion raster scanning microscope for long-wavelength infrared imaging of breast cancer microcalcifications.

Long-wavelength identification of microcalcifications in breast cancer tissue is demonstrated using a novel upconversion raster scanning microscope. The system consists of quantum cascade lasers (QCL) for illumination and an upconversion system for efficient, high-speed detection using a silicon detector. Absorbance spectra and images of regions of ductal carcinoma in situ (DCIS) from the breast have been acquired using both upconversion and Fourier-transform infrared (FTIR) systems. The spectral images are compared and good agreement is found between the upconversion and the FTIR systems.