Clinical-Evolutionary Staging System of Primary Open-Angle Glaucoma Using Optical Coherence Tomography

Primary open-angle glaucoma (POAG) is considered one of the main causes of blindness. Detection of POAG at early stages and classification into evolutionary stages is crucial to blindness prevention. 1001 patients were enrolled, of whom 766 were healthy subjects and 235 were ocular hypertensive or g...

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Published inJournal of clinical medicine Vol. 9; no. 5; p. 1530
Main Authors Parra-Blesa, Alfonso, Sanchez-Alberca, Alfredo, Garcia-Medina, Jose Javier
Format Journal Article
LanguageEnglish
Published Switzerland MDPI AG 19.05.2020
MDPI
Subjects
Algorithms
Antihypertensives
Classification
Clinical medicine
Discriminant analysis
Engineering
evolutionary stages
Glaucoma
Hypertension
Optic nerve
Optics
primary open-angle glaucoma
retinal disease
retinal imaging
Software
spectral domain-optical coherence tomography
Standard deviation
Statistical methods
Tomography
Values
Variables
United States > US
Spain
evolutionary stages
retinal disease
primary open-angle glaucoma
retinal imaging
spectral domain-optical coherence tomography
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Summary:Primary open-angle glaucoma (POAG) is considered one of the main causes of blindness. Detection of POAG at early stages and classification into evolutionary stages is crucial to blindness prevention. 1001 patients were enrolled, of whom 766 were healthy subjects and 235 were ocular hypertensive or glaucomatous patients in different stages of the disease. Spectral domain optical coherence tomography (SD-OCT) was used to determine Bruch's membrane opening-minimum rim width (BMO-MRW) and the thicknesses of peripapillary retinal nerve fibre layer (RNFL) rings with diameters of 3.0, 4.1 and 4.7 mm centred on the optic nerve. The BMO-MRW rim and RNFL rings were divided into seven sectors (G-T-TS-TI-N-NS-NI). The k-means algorithm and linear discriminant analysis were used to classify patients into disease stages. We defined four glaucoma stages and provided a new model for classifying eyes into these stages, with an overall accuracy greater than 92% (88% when including healthy eyes). An online application was also implemented to predict the probability of glaucoma stage for any given eye. We propose a new objective algorithm for classifying POAG into clinical-evolutionary stages using SD-OCT.
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ISSN:2077-0383
2077-0383
DOI:10.3390/jcm9051530