Neural networks to identify multiple sclerosis with optical coherence tomography

. Purpose:  To compare axonal loss in ganglion cells detected with spectral‐domain optical coherence tomography (OCT) in eyes of patients with multiple sclerosis (MS) versus healthy control subjects using an artificial neural network (ANN). To analyse the capability of the ANN technique to improve t...

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Bibliographic Details
Published in:Acta ophthalmologica (Oxford, England) England), 2013-12, Vol.91 (8), p.e628-e634
Main Authors: Garcia‐Martin, Elena, Pablo, Luis E., Herrero, Raquel, Ara, Jose R., Martin, Jesus, Larrosa, Jose M., Polo, Vicente, Garcia‐Feijoo, Julian, Fernandez, Javier
Format: Article
Language:English
Subjects:
Adult
Aged
Axons - pathology
Female
Humans
Intraocular Pressure
Male
Middle Aged
multiple sclerosis
Multiple Sclerosis - diagnosis
neural networks
Neural Networks (Computer)
Ophthalmology
Optic Disk - pathology
optical coherence tomography
Retinal Ganglion Cells - pathology
retinal nerve fibre layer
ROC Curve
Sensitivity and Specificity
Tomography, Optical Coherence - methods
Tonometry, Ocular
Young Adult
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Summary:. Purpose:  To compare axonal loss in ganglion cells detected with spectral‐domain optical coherence tomography (OCT) in eyes of patients with multiple sclerosis (MS) versus healthy control subjects using an artificial neural network (ANN). To analyse the capability of the ANN technique to improve the detection of retinal nerve fibre layer (RNFL) damage in patients with multiple sclerosis. Methods:  Patients with multiple sclerosis (n = 106) and age‐matched healthy subjects (n = 115) were enrolled. The Spectralis OCT system was used to obtain the circumpapillary RNFL thickness in both eyes. The 768 RNFL thickness measurements provided by the Spectralis OCT were performed to obtain thickness measurements from 24 uniformly divided locations around the peripapillary RNFL. The performance of the ANN technique for identifying RNFL loss in patients with multiple sclerosis was evaluated. Receiver‐operating characteristic (ROC) curves were used to display the ability of the test to discriminate between MS and healthy eyes in our population. ROC curves obtained using ANN and parameters provided by OCT (mean and 6 sector thicknesses) were compared. Results:  The capability of the ANN technique to detect RNFL loss in patients with multiple sclerosis compared with healthy subjects was good. The area under the ROC curve was 0.945. Compared with the OCT‐provided parameters, the ANN had the largest area under the ROC curve. Conclusions:  Measurements of RNFL thickness obtained with Spectralis OCT have a good ability to differentiate between healthy and individuals with multiple sclerosis. Based on the area under the ROC curve, the ANN performed better than any single OCT parameter.
ISSN:1755-375X
1755-3768
DOI:10.1111/aos.12156