Automated thresholding algorithms outperform manual thresholding in macular optical coherence tomography angiography image analysis.

INTRODUCTION:For quantification of Optical Coherence Tomography Angiography (OCTA) images, Vessel Density (VD) and Vessel Skeleton Density (VSD) are well established parameters and different algorithms are in use for their calculation. However, comparability, reliability and ability to discriminate healthy and impaired macular perfusion of different algorithms are unclear, yet, of potential high clinical relevance. Hence, we assessed comparability and test-retest reliability of the most common approaches. MATERIALS AND METHODS:Two consecutive 3×3mm OCTA en face images of the superficial and deep retinal layer were acquired with swept-source OCTA. VD and VSD were calculated with manual thresholding and six automated thresholding algorithms (Huang, Li, Otsu, Moments, Mean, Percentile) using ImageJ and compared in terms of intra-class correlation coefficients, measurement differences and repeatability coefficients. Receiver operating characteristic analyses (healthy vs. macular pathology) were performed and Area Under the Curve (AUC) values were calculated. RESULTS:Twenty-six eyes (8 female, mean age: 47 years) of 15 patients were included (thereof 15 eyes with macular pathology). Binarization thresholds, VD and VSD differed significantly between the algorithms and compared to manual thresholding (p < 0.0001). Inter-measurement differences did not differ significantly between patients with healthy versus pathologic maculae (p ≥ 0.685). Reproducibility was higher for the automated algorithms compared to manual thresholding on all measures of reproducibility assessed. AUC was significantly higher for the Mean algorithm compared to the manual approach with respect to the superficial retinal layer. CONCLUSIONS:Automated thresholding algorithms yield a higher reproducibility of OCTA parameters and allow for a more sensitive diagnosis of macular pathology. However, different algorithms are not interchangeable nor results readily comparable. Especially the Mean algorithm should be investigated in further detail. Automated thresholding algorithms are preferable but more standardization is needed for clinical use