OP0175 RELEVANT FEATURES IN FLUORESCENCE OPTICAL IMAGING FOR DIFFERENTIAL DIAGNOSIS OF RHEUMATIC DISEASES AFFECTING THE HANDS

Abstract

BackgroundAccurate and fast diagnosis of rheumatic diseases affecting the hands is essential for further treatment decision. Different rheumatic diseases affecting the hands present characteristic patterns and features in fluorescence optical imaging (FOI) as outlined in previous studies [1, 2].ObjectivesWe tested an atlas of image features in FOI for their ability to differentiate various rheumatic joint diseases such as rheumatoid arthritis (RA), osteoarthritis (OA), psoriatic arthritis (PsA) and connective tissue diseases (CTD) like systemic sclerosis (SSc) and systemic lupus erythematodes (SLE) with the aim to identify specific features for differential diagnosis.MethodsFOI images from patients with RA, OA, PsA and CTD were analysed by two readers blinded for diagnosis and calibrated against each other, using the prima vista mode (PVM) and the 5-phase model. For the latter, the overall time course of FOI in each hand was divided into 5 phases with a computational algorithm. Phases 1 and 2 describe the inflow (start to 15% and 15%-90% on rising edge), phase 3 is the peak phase and phases 4 and 5 comprise the outflow (90%-36.8% and 36.8% to end on falling edge). Twenty-six different features were defined, for example, the signal enhanced forearm (Y), broad signal enhancement along the finger (B), cloudy signal in the hand (W), secondary Raynaud syndrome (R), and underperfused nail bed region (U) (illustrated in theFigure 1). The feature frequency in each patient and phase (PVM, 5-phase) was counted and statistically analysed.ResultsIn total, 374 patients (115 RA patients; mean age 54.4; SD 12.6; median 54.5), OA (89; 62.1; 7.4; 63.2), PsA (59; 50.0; 11.4; 49.2) and CTD (111; 52.2; 14.9; 54.5) were included in the feature reading. Statistical results (χ2, diagnostic odds ratio DOR, sensitivity TPR, specificity TNR, positive predictive value PPV, negative predictive value NPV) are given in theTable 1. CTD can best be differentiated from RA, OA and PsA on the basis of the feature Y, in which sensitivity is high in all phases. CTD compared to RA in feature Y gives a similar result as in PsA. The other features B, W, R and U show Phase-dependent high specificity for CTD.Other significant image features from the atlas yield high specificity (70%-98%) while having low sensitivity (12%-52%) (data not presented).ConclusionThis work supports that FOI feature analysis has the potential for differential diagnosis in rheumatic diseases affecting the hands. Feature Y has the ability to differentiate CTD (here mainly SLE/SSc) from RA, OA, and PsA while the features B, W, R and U can exclude CTD from RA, OA and PsA. In the future, FOI could therefore play an important role in the early arthritis clinic.