Abstract
Spinal cord injury (SCI) is a debilitating neurological and pathological condition that results in significant impairments in motor, sensory, and autonomic functions. By integrating multispectral imaging (MSI) with Raman spectroscopy, a label-free optical methodology was developed for achieving a non-invasive in vivo understanding on the pathological features of SCI evolution. Under the guidance of captured the spectral imaging data cube with a rigid endoscope based MSI system, a special designed fiber probe passed through the instrumental channel for acquiring the finger-print spectral information from compression rat SCI models. After identifying the main visual features of injured spinal cord tissue in all Sham, 0-, 3- and 7-days post injury (0 DPI, 3 DPI, and 7 DPI) groups, the blood volume and oxygen content were visualized to describe hemorrhage, hypoxia and inflammatory state after acute injury. The averaged reflectance spectra, which were deduced from MSI data cubes, were utilized for describing oxygen saturation and hemoglobin concentration in living tissue. The results of Raman spectroscopy addressed complex compositional and conformational phenomena during SCI progression, correlated with the well-known event like neuronal apoptosis, hemorrhage, demyelination, and even the upregulation of chondroitin sulfate proteoglycans (CSPGs). A principal component analysis and linear discriminate algorithm (PCA-LDA) based discriminate model was introduced for categorizing spectral features in different injury stages, which was applicable for intraoperative interpretations on the complex pathological courses of SCI and therapeutic outcomes.
Published Version
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