Wide-field spontaneous Raman spectroscopy imaging system for biological tissue interrogation
Raman spectroscopy has shown great promise as a method to discriminate between cancerous and normal tissue/cells for a range of oncology applications using microscopy and tissue interrogation instruments such as handheld probes and needles. Here we are presenting preliminary steps toward the development of a practical handheld macroscopic Raman spectroscopy instrument, demonstrating its capabilities to discriminate between different biological tissue types during ex vivo porcine experiments. The novel probe design can image a field of view of 25 mm2 with a spatial resolution <100 μm and an average spectral resolution of 95 cm−1, covering the fingerprint region between 450 to 1750 cm−1. The ability of the system to produce tissue maps based on molecular characteristics is demonstrated using a neural network machine learning technique.
For interventional procedures requiring the resection of cancer tissue, patient outcome (survival, quality of life) can be improved by maximizing the volume of cancer resected. Thus, there is a critical need in surgical oncology for portable and accurate tissue characterization tools that can see cancer beyond what can currently be detected with standard-of-care medical imaging techniques (e.g., magnetic resonance imaging, computed tomography, nuclear medicine) and minimize the unnecessary removal of healthy tissue to reduce debilitating effects. Optical techniques exploiting the contrast associated with lighttissue interactions are ideal for intraoperative use because of the non-ionizing nature of the interactions, and they can potentially provide high-resolution spectroscopic information to detect the signature of a multitude of molecular species. Several approaches have been developed to guide surgeries following.
the injection of contrast agents targeting molecular processes associated with specific biomarkers. In vivo methods include fluorescence induced by the injection of aminolevulenic acid (ALA), indocynanine green (ICG), and fluorescein [1], but there is a wide range of ongoing research developing targeted fluorescent markers. Another option for surgical guidance is exploiting intrinsic optical contrast of tissue for in vivo intraoperative characterization, avoiding the need to administer an exogenous compound and, thus, significantly facilitating clinical translation. Such techniques have been developed for interventional use, including optical coherence tomography to image the attenuation contrast associated with elastic scattering, label-free tissue fluorescence to image intrinsic tissue fluorophores, diffuse reflectance to image the optical contrast associated with tissue chromophores (e.g., haemoglobin, melanin, lipids, water) and elastic scattering, as well as vibrational techniques interrogating tissue based on its fine molecular constituents based on inelastic light scattering.
Human tissue is composed of a multitude of molecular species with vibrational properties that can be probed using spontaneous Raman spectroscopy (RS). This technique is thus used for label-free tissue characterization based on molecular fingerprinting in terms of tissue constituents, including lipids, proteins and amino acids, cholesterol, and DNA. Because the concentrations of these biomolecules, as well as their interactions with the cellular/extra-cellular environment, are known to vary between tissue types and pathological status, RS is a promising approach for eventual routine use as an adjunct guidance tool during surgical oncology interventions. Over the past two decades, Raman micro-spectroscopy has been used to detect cancer tissue with high accuracy with ex vivo tissue samples and cell cultures for several pathologies [3]. However, only a limited number of studies have been conducted evaluating RS in vivo for surgical guidance applications. One of the impediments to the clinical translation of RS for interventional medicine applications includes the difficulty to acquire sufficiently high signal-to-noise ratio (SNR) inelastic scattering within timeframes compatible with the workflow of surgeons.
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