Tissue engineering (TE) constructs are an attractive alternative therapy for patients with e.g., degenerated cartilage. The positive patient outcome relies on the quality of the TE constructs as they should mimic the native tissue in its molecular, chemical, and physical properties. Most quality assessment techniques of TE constructs are destructive to the sample. Therefore, there is an urgent need for a novel non-destructive method to control the in vitro cultivating process. Here, we present Raman Projection Tomography (RPT) which enables live label-free 3D molecular imaging. RPT was employed for the non-destructive quality control of cartilage TE constructs.
We have developed a forward-scattered high-resolution Raman-Computed Tomography (R-CT) technique that relies on true CT principles rather than diffuse tomography. The in-house built optical system rotates around the sample while Raman spectra are measured from different angles by multiplexing on the 2D CCD. Forward scattered photons are largely in the far-field to reject diffuse photons. We show that R-CT provides both, spatial and molecular information in diffusely scattering phantoms. Data reconstruction is performed using backprojection and multivariate regression analysis to provide a 3D chemical contrast. We finally present preliminary results on rodent limbs.
The R-CT technique developed offers a potential technique to improve the characterisation of tissues and drug efficiency in rodent limbs at the molecular level as it offers morphological information that is not available in conventional transmission Raman spectroscopy.
Osteoarthritis (OA) is a painful, debilitating disease characterized by the degeneration of articular cartilage. We have developed a novel multiplexed polarized, hypodermic-needle-compatible Raman arthroscope probe that can achieve intra-articular assessments of the compositional and structural changes to cartilage associated with early-stage OA, including depletion of glycosaminoglycans from the cartilage superficial regions and changes to superficial zone collagen alignment. Through ex vivo models on human and bovine cartilage, we demonstrate that using multivariate linear regression, this platform can accurately measure superficial zone cartilage GAG depletion. This work shows that Raman needle arthroscopy can provide a practical, minimally invasive, point-of-care clinical tool capable of diagnosing OA before irreparable cartilage degeneration is radiographically evident.
Spontaneous Raman spectroscopy enables non-ionising, non-destructive, and label-free acquisition of a biochemical fingerprint for a given sample. However, the long integration times required largely prohibit high-throughput applications. Here, we present a comprehensive deep learning framework for extreme speed-up of spontaneous Raman imaging. Our deep learning framework enhances Raman imaging two-fold, effectively reconstructing both spectral and spatial information from low spatial resolution, low signal-to-noise ratio images to achieve extreme Raman imaging time speed-ups of 40-90x while mainting high reconstruction fidelity. As such, our framework could enable a host of higher-throughput spontaneous Raman spectroscopy applications across a diverse range of fields.
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