Automatic diagnosis of bipolar disorder using optical coherence tomography data and artificial intelligence

Sánchez-Morla E.M. ; Fuentes J.L. ; Miguel-Jiménez J.M. ; Boquete L. ; Ortiz M. ; Orduna E. (Universidad de Zaragoza) ; Satue M. (Universidad de Zaragoza) ; Garcia-Martin E. (Universidad de Zaragoza)

Resumen: Background: The aim of this study is to explore an objective approach that aids the diagnosis of bipolar disorder (BD), based on optical coherence tomography (OCT) data which are analyzed using artificial intelligence. Methods: Structural analyses of nine layers of the retina were analyzed in 17 type I BD patients and 42 controls, according to the areas defined by the Early Treatment Diabetic Retinopathy Study (ETDRS) chart. The most discriminating variables made up the feature vector of several automatic classifiers: Gaussian Naive Bayes, K-nearest neighbors and support vector machines. Results: BD patients presented retinal thinning affecting most layers, compared to controls. The retinal thickness of the parafoveolar area showed a high capacity to discriminate BD subjects from healthy individuals, specifically for the ganglion cell (area under the curve (AUC) = 0.82) and internal plexiform (AUC = 0.83) layers. The best classifier showed an accuracy of 0.95 for classifying BD versus controls, using as variables of the feature vector the IPL (inner nasal region) and the INL (outer nasal and inner inferior regions) thickness. Conclusions: Our patients with BD present structural alterations in the retina, and artificial intelligence seem to be a useful tool in BD diagnosis, but larger studies are needed to confirm our findings.

Idioma: Inglés

DOI: 10.3390/jpm11080803

Año: 2021

Publicado en: Journal of Personalized Medicine 11, 8 (2021), 803 [15 pp.]
ISSN: 2075-4426

Factor impacto JCR: 3.508 (2021)

Categ. JCR: MEDICINE, GENERAL & INTERNAL rank: 69 / 172 = 0.401 (2021) - Q2 - T2
Categ. JCR: HEALTH CARE SCIENCES & SERVICES rank: 42 / 110 = 0.382 (2021) - Q2 - T2

Factor impacto CITESCORE: 1.8 - Medicine (Q3)

Factor impacto SCIMAGO: 0.757 - Medicine (miscellaneous) (Q2)

Financiación: info:eu-repo/grantAgreement/ES/ISCIII-FEDER/PI17-01726
Financiación: info:eu-repo/grantAgreement/ES/ISCIII-FEDER/PI20-00437
Financiación: info:eu-repo/grantAgreement/ES/MINECO FEDER/RD16-0008-029

Tipo y forma: Artículo (Versión definitiva)

Área (Departamento): Área Oftalmología (Dpto. Cirugía)
Área (Departamento): Área Óptica (Dpto. Física Aplicada)