Spectroscopie Raman de tissus biologiques dans le domaine temporel

La spectroscopie Raman est un outil d’imagerie optique à la popularité grandissante pour le diagnostic du cancer. Il exploite la diffusion inélastique pour identifier la composition moléculaire d’un échantillon. Or, la probabilité d’occurrence de cette diffusion étant très faible, dans des environnements à la composition moléculaire complexe elle est très souvent masquée par un autre phénomène résultant de l’interaction lumière - matière : la fluorescence. C’est particulièrement le cas dans les tissus biologiques qui contiennent naturellement une quantité importante de molécules émettrices de fluorescence. Pour isoler le spectre Raman, on a le plus souvent recours à des algorithmes mathématiques, dont la portée reste limitée. Une méthode prometteuse pour supprimer l’effet de la fluorescence est l’utilisation du domaine temporel. Elle se base sur la différence de profil temporel entre les deux phénomènes pour rejeter la fluorescence et isoler le Raman. Le comptage de photon unique corrélée dans le temps est une technique communément utilisée pour la mesure du temps de vie de fluorescence. Grâce à l’arrivée récente de détecteurs à photon unique ultra rapide, plusieurs systèmes de spectroscopie Raman en temporel ont été développés à partir de cette technologie. Cependant, elle n’a encore jamais été testée sur des tissus biologiques. Ce projet consiste donc à évaluer la pertinence de la spectroscopie Raman en temporel dans le contexte biomédical de la reconnaissance moléculaire de tissus. Un premier système, utilisant un laser à lumière visible, a été conçu. À l’aide d’un détecteur à la commande ultra-rapide, il a été capable de réduire l’importante fluorescence émise à ces mêmes longueurs d’onde sur un morceau de viande de bœuf par l’application d’une fenêtre temporelle, laissant ainsi apparaître des pics Raman caractéristiques de l’échantillon. De plus, il a été démontré que la réduction progressive du signal de fond, majoritairement composé de fluorescence, permet d’augmenter la qualité des spectres Raman comparativement au seul traitement mathématique. Un second système a alors été développé avec, cette fois, une source dans le proche infrarouge, dans le but de comparer les résultats avec un système de spectroscopie Raman conventionnel, qui utilise cette même plage spectrale. Combinant de manière inédite la mesure dans le domaine de Fourier et le comptage de photon unique corrélé dans le temps, ce nouveau système a démontré une importante réduction du signal de fond ainsi qu’une bonne correspondance avec les résultats du système conventionnel sur des échantillons biologiques.----------ABSTRACT Raman spectroscopy is an increasingly popular optical imaging tool for cancer diagnostic. It exploits inelastic scattering to identify the molecular composition of a sample. However, since the probability of occurrence of this scattering is very low, in environments with a complex molecular composition it is very often masked by another light - matter interaction: the fluorescence. This is particularly the case in biological tissues which naturally contain a significant number of fluorescence-emitting molecules. To isolate the Raman spectrum, we most often use mathematical algorithms, which remains limited. One promising method to suppress the effect of fluorescence is the use of the time domain. It is based on the difference in temporal profile between the two phenomena to reject fluorescence and isolate Raman. Time correlated single photon counting is a commonly used technique for measuring fluorescence lifetimes. With the recent arrival of ultra-fast single-photon sensors, several time-based Raman spectroscopy systems have been developed based on this technology. However, it has never been tested in biological tissue before. This project therefore consists in evaluating the relevance of time-domain Raman spectroscopy in the biomedical context of tissue recognition. A first system, using a visible light laser, has been designed. Using an ultra-fast controlled detector, it was able to reduce the large fluorescence emitted at these same wavelengths on a piece of beef by applying a time window, thus revealing Raman peaks characteristic of the sample. In addition, it has been shown that the gradual reduction of the background signal, mainly composed of fluorescence, makes it possible to increase the quality of Raman spectra when compared with a solely algorithmic approach. A second system was then developed with, this time, a source in the near infrared, in order to compare the results with a conventional Raman spectroscopy system, which uses this same spectral range. Combining in an unprecedented way the measurement in the Fourier domain and the time-correlated single photon counting, this new system demonstrated a significant reduction of the background signal as well as a good correspondence with the results of the conventional system on biological samples

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

ABSTRACT: Objectives Raman spectroscopy as a diagnostic tool for biofluid applications is limited by low inelastic scattering contributions compared to the fluorescence background from biomolecules. Surface-enhanced Raman spectroscopy (SERS) can increase Raman scattering signals, thereby offering the potential to reduce imaging times. We aimed to evaluate the enhancement related to the plasmonic effect and quantify the improvements in terms of spectral quality associated with SERS measurements in human saliva. Methods Dried human saliva was characterized using spontaneous Raman spectroscopy and SERS. A fabrication protocol was implemented leading to the production of silver (Ag) nanopillar substrates by glancing angle deposition. Two different imaging systems were used to interrogate saliva from 161 healthy donors: a custom single-point macroscopic system and a Raman micro-spectroscopy instrument. Quantitative metrics were established to compare spontaneous RS and SERS measurements: the Raman spectroscopy quality factor (QF), the photonic count rate (PR), the signal-to-background ratio (SBR). Results SERS measurements acquired with an excitation energy four times smaller than with spontaneous RS resulted in improved QF, PR values an order of magnitude larger and a SBR twice as large. The SERS enhancement reached 100×, depending on which Raman bands were considered. Conclusions Single-point measurement of dried saliva with silver nanopillars substrates led to reproducible SERS measurements, paving the way to real-time tools of diagnosis in human biofluids

Saliva-based detection of COVID-19 infection in a real-world setting using reagent-free Raman spectroscopy and machine learning

ABSTRACT: SIGNIFICANCE: The primary method of COVID-19 detection is reverse transcription polymerase chain reaction (RT-PCR) testing. PCR test sensitivity may decrease as more variants of concern arise and reagents may become less specific to the virus. AIM: We aimed to develop a reagent-free way to detect COVID-19 in a real-world setting with minimal constraints on sample acquisition. The machine learning (ML) models involved could be frequently updated to include spectral information about variants without needing to develop new reagents. APPROACH: We present a workflow for collecting, preparing, and imaging dried saliva supernatant droplets using a non-invasive, label-free technique-Raman spectroscopy-to detect changes in the molecular profile of saliva associated with COVID-19 infection. RESULTS: We used an innovative multiple instance learning-based ML approach and droplet segmentation to analyze droplets. Amongst all confounding factors, we discriminated between COVID-positive and COVID-negative individuals yielding receiver operating coefficient curves with an area under curve (AUC) of 0.8 in both males (79% sensitivity and 75% specificity) and females (84% sensitivity and 64% specificity). Taking the sex of the saliva donor into account increased the AUC by 5%. CONCLUSION: These findings may pave the way for new rapid Raman spectroscopic screening tools for COVID-19 and other infectious diseases