Líf - og heilbrigðisvísindaráðstefna Háskóla Íslands 2021

Automation improves the repeatability and reproducibility of retinal oximetry measurements

Main author: Róbert Arnar Karlsson
Institution or Company: University of Iceland Faculty of Medicine, University of Iceland Faculty of Electrical and Computer Engineering

Co-Authors, Institution or Company:
Ólöf Birna Ólafsdóttir, University of Iceland Faculty of Medicine. Soumaya Belhadj, University of Tübingen. Védís Helgadóttir, University of Iceland Faculty of Medicine. Sveinn Hákon Harðarsson, University of Iceland Faculty of Medicine.

Introduction: Retinal oximetry is a technique based on spectrophotometry where images are analyzed with software capable of calculating oxygen saturation. Until now, operators have had to choose each vessel segment being explicitly measured. A new, automatic version of the software automatically selects the vessels once the operator defines the measurement area. This study evaluates the repeatability and reproducibility of these two measurement methods.

Methods: Five operators analyzed image pairs from the right eye of 23 healthy subjects with an existing version of retinal oximetry analysis software, Oxymap analyzer (v.2.5.1), and an automated version (v.3.0). Inter- and intra-operator variability was investigated using two-way analysis of variance and the intraclass correlation coefficient (ICC) between oxygen saturation measurements of vessel segments in the same area of the retina.

Results: For manual measurements the inter-rater ICC was 0.78 95%CI[0.69, 0.86] for arterioles and 0.87 95%CI [0.78, 0.92] for venules. For automated measurements the inter-rater ICC  was 0.989 95%CI [0.983, 0.994] for arterioles and 0.991 95%CI [0.987, 0.995]. For manual measurements the repeatability was 1.6 for arterioles and 3.39 for venules. For automated measurements, the repeatability was 0.46 for arterioles and 2.2 for venules. For manual measurements there was a statistically significant difference between operators when evaluating both arterioles (p = 0.0001) and venules (p < 10-6), for automated measurements this difference disappeared for both arterioles (p = 0.23) and venules (p = 0.75).

Conclusion: Automated measurements of retinal oximetry values are more repeatable and reproducible compared to measurements where vessels are selected manually.

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