Abstract
Optical coherence tomography angiography (OCTA) is clinically useful for the qualitative assessment of the macular microvasculature. However, there is a need for comprehensive quantitative tools to help objectively analyze the OCT angiograms. Few studies have reported the use of a single quantitative index to describe vessel density in OCT angiograms. In this study, we introduce a five-index quantitative analysis of OCT angiograms in an attempt to detect and assess vascular abnormalities from multiple perspectives. The indices include vessel area density, vessel skeleton density, vessel diameter index, vessel perimeter index, and vessel complexity index. We show the usefulness of the proposed indices with five illustrative cases. Repeatability is tested on both a healthy case and a stable diseased case, giving interclass coefficients smaller than 0.031. The results demonstrate that our proposed quantitative analysis may be useful as a complement to conventional OCTA for the diagnosis of disease and monitoring of treatment.
Highlights
Optical coherence tomography angiography (OCTA) was recently introduced for the imaging of microvascular networks in the human eye.[1]
To demonstrate the usefulness of these parameters, we used Optical microangiography (OMAG) en face images generated by using both spectral domain OCT (SD-OCT) and swept-source OCT (SS-OCT) angiography prototype instruments
We proposed five metrics, vessel area density (VAD), vessel skeleton density (VSD), vessel diameter index (VDI), VPI, and vessel complexity index (VCI), for the quantitative assessment of OCT angiograms
Summary
Optical coherence tomography angiography (OCTA) was recently introduced for the imaging of microvascular networks in the human eye.[1]. The combination of OCT and OCTA can present integrated structural and flow information of the human eye in vivo, opening new opportunities for both qualitative and quantitative analysis of ocular diseases. Optical microangiography (OMAG)[1] is one of the many OCTA approaches that utilizes the intrinsic properties of particles’ (e.g., red blood cells) motion, to highlight the contrast between signals due to red blood cells (RBCs) and signals due to static tissues. Unlike other OCTA approaches such as speckle variance,[9] split-spectrum amplitude decorrelation angiography,[10] and phase variance,[11] OMAG is able to harness motion information to the fullest extent by exploiting both amplitude and phase information contained within the OCT signals.
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