Systemic sclerosis (SSc) is a chronic multisystem disease associated with collagen accumulation and fibrosis, most prominent in the skin and lungs. There is considerable patient-to-patient, as well as within-patient temporal, heterogeneity in the extent and course of fibrosis. The widely used modified Rodnan skin score (mRSS) employs skin thickening as a surrogate for SSc severity; however, the value of this tool for risk stratification and for prediction of disease progression is limited. Infrared (IR) spectroscopic imaging permits rapid label-free tissue imaging to extract spectral biomarkers for prediction of disease outcome, and shows sensitivity to biochemical changes that can identify sub-clinical complications and pre-histological changes in multiple diseases. In this study, we performed IR spectroscopic imaging of skin biopsies from 15 healthy controls and 20 SSc patients. The results demonstrate unambiguous spectral changes discriminating between healthy and SSc biopsies using multivariate data analysis. Spectral differences in skin biopsies were not correlated with the potential confounding factors age, race or gender or disease duration. In longitudinal analysis, baseline skin biopsies were unable to predict changes in mRSS at 12 months. Together, these results demonstrated the utility of IR spectroscopic imaging for classifying skin biopsies. Further studies are required to determine whether spectral IR imaging can provide clinical-level information for augmenting current approaches to disease classification in SSc.
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