SD-OCT peripapillary nerve fibre layer and ganglion cell complex parameters in glaucoma: principal component analysis

• Published in: British journal of ophthalmology Vol. 105; no. 4; pp. 496 - 501
• Main Authors: Pazos, Marta, Biarnés, Marc, Blasco-Alberto, Andrés, Dyrda, Agnieszka, Luque-Fernández, Miguel Ángel, Gómez, Alicia, Mora, Clara, Milla, Elena, Muniesa, MªJesús, Antón, Alfonso, Díaz-Alemán, Valentín Tinguaro
• Format: Journal Article
• Language: English
• Published: England BMJ Publishing Group LTD 01.04.2021
• Subjects: Age; Diabetic retinopathy; Glaucoma; Medical diagnosis; Optics; Principal components analysis; Software; Variables; Spain; Tenerife; diagnostic tests/investigation; imaging; optic nerve; glaucoma
• ISSN: 0007-1161; 1468-2079
• DOI: 10.1136/bjophthalmol-2020-316296

Background/aimsTo identify objective glaucoma-related structural features based on peripapillary (p) and macular (m) spectral domain optical coherence tomography (SD-OCT) parameters and assess their discriminative ability between healthy and glaucoma patients.MethodsTwo hundred and sixty eyes (91 controls and 169 glaucoma) were included in this prospective study. After a complete examination, all participants underwent the posterior pole and the peripapillary retinal nerve fibre layer (pRNFL) protocols of the Spectralis SD-OCT. Principal component analysis (PCA), a data reduction method, was applied to identify and characterise the main information provided by the ganglion cell complex (GCC). The discriminative ability between healthy and glaucomatous eyes of the first principal components (PCs) was compared with that of conventional SD-OCT parameters (pRNFL, macular RNFL (mRNFL), macular ganglion cell layer (mGCL)and macular inner plexiform layer (mIPL)) using 10-fold cross-validated areas under the curve (AUC).ResultsThe first PC explained 58% of the total information contained in the GCC and the pRNFL parameters and was the result of a general combination of almost all variables studied (diffuse distribution). Other PCs were driven mainly by pRNFL and mRNFL measurements. PCs and pRNFL had similar AUC (0.95 vs 0.96, p=0.88), and outperformed the other structural measurements: mRNFL (0.91, p=0.002), mGCL (0.92, p=0.02) and mIPL (0.92, p=0.0001).ConclusionsPCA identified a diffuse representation of the papillary and macular SD-OCT parameters as the most important PC to summarise structural data in healthy and glaucomatous eyes. PCs and pRNFL parameters showed the greatest discriminative ability between healthy and glaucoma cases.