OCTAVA: An open-source toolbox for quantitative analysis of optical coherence tomography angiography images

• Published in: PloS one Vol. 16; no. 12; p. e0261052
• Main Authors: Untracht, Gavrielle R, Matos, Rolando S, Dikaios, Nikolaos, Bapir, Mariam, Durrani, Abdullah K, Butsabong, Teemapron, Campagnolo, Paola, Sampson, David D, Heiss, Christian, Sampson, Danuta M
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 09.12.2021; Public Library of Science (PLoS)
• Subjects: Adult; Algorithms; Analysis; Angiography; Biomarkers; Blood vessels; Coherence (Optics); Computer and Information Sciences; Data analysis; Data processing; Dermatology; Engineering and Technology; Forearm - blood supply; Forearm - diagnostic imaging; Hand - blood supply; Hand - diagnostic imaging; Healthy Volunteers; Humans; Image Processing, Computer-Assisted - methods; Image segmentation; Information management; Laboratories; Medical imaging; Medicine; Medicine and Health Sciences; Microvasculature; Microvessels - diagnostic imaging; Middle Aged; Open source software; Ophthalmology; Optical Coherence Tomography; Optimization; Pathophysiology; Physical Sciences; Physics; Quantitative analysis; Research and Analysis Methods; Science Policy; Signal-To-Noise Ratio; Standardization; Tomography; Tomography, Optical Coherence - methods; Visualization; Workflow; United States; United Kingdom > UK
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0261052

Optical coherence tomography angiography (OCTA) performs non-invasive visualization and characterization of microvasculature in research and clinical applications mainly in ophthalmology and dermatology. A wide variety of instruments, imaging protocols, processing methods and metrics have been used to describe the microvasculature, such that comparing different study outcomes is currently not feasible. With the goal of contributing to standardization of OCTA data analysis, we report a user-friendly, open-source toolbox, OCTAVA (OCTA Vascular Analyzer), to automate the pre-processing, segmentation, and quantitative analysis of en face OCTA maximum intensity projection images in a standardized workflow. We present each analysis step, including optimization of filtering and choice of segmentation algorithm, and definition of metrics. We perform quantitative analysis of OCTA images from different commercial and non-commercial instruments and samples and show OCTAVA can accurately and reproducibly determine metrics for characterization of microvasculature. Wide adoption could enable studies and aggregation of data on a scale sufficient to develop reliable microvascular biomarkers for early detection, and to guide treatment, of microvascular disease.