Here, we explore the potential benefits of extracting hemoglobin oxygenation metrics using multispectral imaging (MSI) in nailfold capillaroscopy for systemic sclerosis (SSc) patients. We used a nine-band multispectral camera to capture images of the nail bed from SSc patients (n=10) and healthy controls (n=12). Spectral analysis and machine learning classification were employed to examine systematic changes between healthy controls and SSc patients. The results demonstrate differences in spectra and promising accuracy in classification, with further work needed to extract oxygenation values and improve signal-to-noise ratio. MSI shows potential for improving sensitivity of nailfold capillaroscopy and detection of changes in early disease.
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