P161 Optical coherence tomography of the skin detects scleroderma changes in clinically unaffected skin: an opportunity for early detection of systemic sclerosis
Authors: Abignano Giuseppina , Karadag Duygu Temiz , Gundogdu Ozcan , Lettieri Giovanni , Padula Maria Carmela , Padula Angela A , Emery Paul , D'Angelo Salvatore , Galdo Francesco Del 
Published: April 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 nailfold video capillaroscopy will fulfill classification criteria within 5 years. This is suggesting that there is a sub-clinical 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. 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.

Disclosures

G. Abignano None. D. Temiz Karadag None. O. Gundogdu None. G. Lettieri None. M. Padula None. A.A. Padula None. P. Emery None. S. D'Angelo None. F. Del Galdo None.