AB0733 Treatment monitoring of fluorescence optical imaging (foi) using automated, computer-based quantitative assessment. (23rd January 2014)

• Record Type: Journal Article
• Authors: Bahner, M.; Werner, S. G.; Cziumplik, M.; Berger, J.; Langer, H.-E.; Schirner, M.
• Is Part Of: Annals of the rheumatic diseases. Volume 72:Supplement 3(2013)
• Page Start: A1012
• Page End: A1013
• Publication Date: 2014-01-23
• Subjects: Rheumatism -- Periodicals; 616.723005
• DOI: 10.1136/annrheumdis-2013-eular.3055
• Languages: English
• ISSNs: 0003-4967

Abstract

Abstract : Background: Fluorescence optical imaging (FOI) with the Xiralite® system is clinically available for diagnostic imaging of inflammation and has been shown to be a suitable tool to assess treatment response in subjects with RA and PsA. Changes in FOI are measured using the semi-quantitative fluorescence optical imaging activity score (FOIAS) which allows for a low inter-reader variability 1 . Most recently, an automatic, computer-based image analysis of FOI (DACT) has been described and validated in healthy subjects 2 . Objectives: To evaluate an automatic computer-based analysis of FOI in patients with RA or PsA under treatment. Methods: 30 patients with rheumatoid (RA) or psoriatic (PsA) arthritis were examined before starting treatment (visit 1) and at follow-up (visit 2). Treatment response was assessed using DAS28, cFOIAS and the automated calculated DACT. First, 3 readers analyzed all 60 image data sets individually. For articular location of increased signal intensities (ISI) the FOIAS was used. For extraarticular location the signals were graded semiquantitatively on a scale of 0 to 2. These values were added to a single number representing the overall fluorescence signal intensity of the hands (cFOIAS). For DACT composite images were generated automatically. Using dedicated parameters of the histograms, automatic extraction of the hands from the image background was performed by the computer. The algorithm separated the hands from the forearm in a standardized manner by using a multiple of the length of the middle finger. A threshold in the fluorescence intensity curve was set to discriminate high and low intensity areas. The area of high intensity was calculated and the values of each patient were divided by the 95th percentile of normal individuals which was defined as reference value. DACT was expressed as high signal intensity area patient / healthy reference. DACT in healthy individuals equals 1. Then cFOIAS and DACT values were compared. Results: 60 left and 60 right hands were correctly extracted from the auto-scaled composite image of the first 240 seconds. The intra-individual variation of the extraction procedure measured as intensity area of the hand in the consecutive procedures was 1.1 % + 1.0 (range: 0.04 – 4.9). cFOIAS scores strongly correlate with automated calculated DACT (0.86 / reader 1, 0.84 / reader 2 and 0.85 / reader 3). Agreement of declining DAS28 with declining cFOIAS was found in 16/30 (reader 1), 17/30 (reader 2) and 15/30 (reader 3) treatment courses. Agreement of declining DAS28 with declining DACT was found in 16/30 treatment course. Conclusions: This first clinical trial in patients with RA or PsA under treatment with follow-up FOI exams demonstrates that automatic, computer-based image analysis of FOI to calculate DACT values is technically feasible, offers high reproducibility and high agreement with cFOIAS score reading, while agreement of DACT value with DAS28 was only moderate. Even very low changes of the DACT value can be measured and considered as statistically significant. References: Werner SG et al. Indocyanine Green Enhanced Optical Imaging Using for Monitoring of Treatment Response. Arthritis & Rheumatism 2011: 63 (10); S73 Schirner M. et al. Methods for automated, computer-based quantitative assessment of fluorescence optical imaging. Ann Rheum Dis 2012;71(Suppl3):711 Disclosure of Interest: M. Bahner Shareholder of: mivenion GmbH, Employee of: mivenion GmbH, S. Werner: None Declared, M. Cziumplik Employee of: mivenion GmbH, J. Berger Employee of: mivenion GmbH, H.-E. Langer: None Declared, M. Schirner Shareholder of: mivenion GmbH, Employee of: mivenion GmbH