FRI0226 OPTICAL COHERENCE TOMOGRAPHY OF THE SKIN DETECTS SCLERODERMA CHANGES IN CLINICALLY UNAFFECTED SKIN: AN OPPORTUNITY FOR EARLY DETECTION OF SYSTEMIC SCLEROSIS
Authors: G. Abignano, D. Temiz Karadağ, O. Gundogdu, G. Lettieri, M. C. Padula, A. Padula, P. Emery, S. D’angelo, F. Del Galdo
Journal: Annals of the Rheumatic Diseases (2020)

Background: The Very Early Diagnosis Of Systemic Sclerosis (VEDOSS) study has shown that 82% of patients with Raynaud’s Phenomenon, specific ANA positivity and scleroderma pattern at nail fold videocapillaroscopy will fulfil classification criteria within 5 years. This is suggesting that there is a subclinical window of opportunity to diagnose systemic sclerosis (SSc) before clinical manifestations occur. In this scenario, a non-invasive tool to diagnose SSc in clinically unaffected skin might improve the early detection of disease in at risk-patients. Optical coherence tomography (OCT) of the skin has been shown to be a sensitive and accurate biomarker of skin fibrosis in SSc. Objectives: Here we aimed to assess the ability of skin OCT to “detect” SSc in clinically unaffected skin from a multicentre cohort. Methods: Dorsal forearm skin of SSc patients and matched-healthy controls (HC) was evaluated using VivoSight scanner (Michelson Diagnostics). Mean A-scans (mean OCT signal plotted against depth-in-tissue) were derived as previously described. Minimum Optical Density (MinOD), Maximum OD (MaxOD) and OD at 300 micron-depth (OD300) were calculated. Clinical involvement was assessed by an operator blinded to OCT findings using the mRSS. Receiver-operating characteristic (ROC) curve analysis was carried out for MinOD, MaxOD, and OD300 to evaluate their ability to discriminate between SSc and HC. Statistical analysis was performed using GraphPad Prism software V.7.0. Results: One hundred seventy four OCT images were collected from 87 subjects [43 SSc (39 Female, mean age 49.7±9.1 years) and 44 gender/age-matched healthy controls (HC) (36 Female, mean age 50.2±8.3 years)] in two different SSc centres. All patients fulfilled classification criteria for SSc. OCT measures demonstrated discriminative ability in SSc skin detection with any clinical skin involvement (0-3 at site of analysis) with an AUC of 0.73 (MinOD, 95%CI 0.64-0.81), 0.77 (MaxOD, 95%CI 0.7-0.85) and 0.82 (OD300, 95%CI 0.76-0.89); p&lt;0.0001 for all as previously indicated. Most importantly, all three measures showed comparable performance in detecting scleroderma also in clinically unaffected skin (mRss=0 at site of analysis), with an AUC of 0.7 (95%CI 0.6-0.81, p=0.001), 0.72 (95%CI 0.61-0.83, p=0.0003) and 0.72 (95%CI 0.61-0.83, p=0.0003) for MinOD, MaxOD and OD300 respectively. Conclusion: Virtual biopsy by OCT recognises clinically unaffected skin of SSc patients from the HC skin. This is consistent with gene array data showing that scleroderma specific signatures are consistent in affected and clinically unaffected skin. These results inform future studies on at risk patients with clinically unaffected skin which may define a role for OCT in detecting subclinical SSc. Disclosure of Interests: Giuseppina Abignano: None declared, Duygu Temiz Karadağ: None declared, Ozcan Gundogdu: None declared, Giovanni Lettieri: None declared, Maria Carmela Padula: None declared, Angela Padula: None declared, Paul Emery Grant/research support from: AbbVie, Bristol-Myers Squibb, Merck Sharp &amp; Dohme, Pfizer, Roche (all paid to employer), Consultant of: AbbVie (consultant, clinical trials, advisor), Bristol-Myers Squibb (consultant, clinical trials, advisor), Lilly (clinical trials, advisor), Merck Sharp &amp; Dohme (consultant, clinical trials, advisor), Novartis (consultant, clinical trials, advisor), Pfizer (consultant, clinical trials, advisor), Roche (consultant, clinical trials, advisor), Samsung (clinical trials, advisor), Sandoz (clinical trials, advisor), UCB (consultant, clinical trials, advisor), Salvatore D’Angelo: None declared, Francesco Del Galdo: None declared