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.
Doppler optical coherence tomography (DOCT) combines the imaging capabilities of OCT with functional velocity
imaging and is used routinely to study skin in-vivo. The skin provides a window to monitor diseases; it has been shown
that changes in skin blood flow and structure are indicative of systemic disease change and representative of disease
status. This study aims to aid understanding and interpretation of DOCT images of skin with respect to vessel diameter,
depth and blood flow. We have constructed a tissue model using glass capillary tubes suspended at an angle of 20° to the
horizontal in an Intralipid-filled tank. The Intralipid was diluted to levels which represented optimal tissue and blood
flow scattering parameters. Intralipid was then pumped through the tubes to represent blood flow. The angled nature of
the tubes allowed flow imaging at various depths. DOCT images were recorded using a swept-source OCT system with
1300 nm central wavelength and 6 μm axial resolution (OCMP1300SS, Thorlabs, Inc.). Data parameters extracted from
images include velocity, penetration depth and their dependence on tube diameter, depth and flow. We have successfully
demonstrated a tissue model that allows DOCT imaging of vessel diameter, depth and blood flow to be investigated.
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