In vivo clinical raman spectroscopy for non-invasive quantification of calcinosis cutis in rheumatic disease

Summary: Abstract Body: Calcinosis cutis (CC) is a challenging sequela of rheumatic skin diseases. The nature of CC is poorly understood and there are no validated outcomes, creating a barrier to therapeutic development. Raman spectroscopy (RS) is a non-invasive method that can quantify compounds based on the scattering of incident light, allowing rapid chemical characterization. This makes RS a promising tool to better characterize the composition of CC lesions and assist with diagnosis. Thus, we performed a pilot study using RS to compare the relative composition of hydroxyapatite, collagen, and lipid in a single center, convenience sample of 15 calcinosis compared to 15 control sites in nine participants with systemic sclerosis (N=4), dermatomyositis (N=3), and morphea (N=2). The in vivo spectra were fitted with a non-negative least squares algorithm to determine the relative concentration of these pure compounds. For univariate analysis, Wilcoxon signed-rank test was utilized for paired data. We found, consistent across all sites, that lesional CC sites contained a higher relative concentration of hydroxyapatite (median: 0.28 (interquartile range, IQR: 0.17-0.46) vs. median: 0.04 (IQR: 0.003-0.12); p<0.001) and lower relative concentration of collagen compared to their control sites (median: 0.68 (IQR: 0.53-0.78) vs. median: 0.91 (IQR: 0.81-0.96); p=0.002). We did not find any significant difference in relative lipid concentration (median: 0 vs. median: 0; p=0.38). This non-invasive feasibility study was limited by the lack of histological confirmation, as biopsy was not indicated. As additional studies are being conducted to confirm findings, these results suggest that Raman spectroscopy is a novel method for the in vivo differentiation of CC from unaffected skin in patients with rheumatic skin diseases. Jay Garza¹, Jessica Baas², Justin Singer², Jenny Foster¹, Triniti Vanoven^{2, 3}, Heidi Jacobe¹, Isaac Pence², Benjamin Chong¹ 1. Dermatology, The University of Texas Southwestern Medical Center, Dallas, TX, United States. 2. Biomedical Engineering, The University of Texas Southwestern Medical Center, Dallas, TX, United States. 3. Bioengineering, The University of Texas at Dallas, Richardson, TX, United States. Bioinformatics, Computational Biology, and Imaging