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1.
Comput Biol Med ; 170: 107979, 2024 Mar.
Article in English | MEDLINE | ID: mdl-38219645

ABSTRACT

Diabetic Macular Edema (DME) is the most common sight-threatening complication of type 2 diabetes. Optical Coherence Tomography (OCT) is the most useful imaging technique to diagnose, follow up, and evaluate treatments for DME. However, OCT exam and devices are expensive and unavailable in all clinics in low- and middle-income countries. Our primary goal was therefore to develop an alternative method to OCT for DME diagnosis by introducing spectral information derived from spontaneous electroretinogram (ERG) signals as a single input or combined with fundus that is much more widespread. Baseline ERGs were recorded in 233 patients and transformed into scalograms and spectrograms via Wavelet and Fourier transforms, respectively. Using transfer learning, distinct Convolutional Neural Networks (CNN) were trained as classifiers for DME using OCT, scalogram, spectrogram, and eye fundus images. Input data were randomly split into training and test sets with a proportion of 80 %-20 %, respectively. The top performers for each input type were selected, OpticNet-71 for OCT, DenseNet-201 for eye fundus, and non-evoked ERG-derived scalograms, to generate a combined model by assigning different weights for each of the selected models. Model validation was performed using a dataset alien to the training phase of the models. None of the models powered by mock ERG-derived input performed well. In contrast, hybrid models showed better results, in particular, the model powered by eye fundus combined with mock ERG-derived information with a 91 % AUC and 86 % F1-score, and the model powered by OCT and mock ERG-derived scalogram images with a 93 % AUC and 89 % F1-score. These data show that the spontaneous ERG-derived input adds predictive value to the fundus- and OCT-based models to diagnose DME, except for the sensitivity of the OCT model which remains the same. The inclusion of mock ERG signals, which have recently been shown to take only 5 min to record in daylight conditions, therefore represents a potential improvement over existing OCT-based models, as well as a reliable and cost-effective alternative when combined with the fundus, especially in underserved areas, to predict DME.


Subject(s)
Diabetes Mellitus, Type 2 , Diabetic Retinopathy , Macular Edema , Humans , Macular Edema/diagnostic imaging , Diabetic Retinopathy/diagnostic imaging , Diabetes Mellitus, Type 2/complications , Fundus Oculi , Tomography, Optical Coherence/methods
2.
Eye (Lond) ; 35(2): 632-638, 2021 02.
Article in English | MEDLINE | ID: mdl-32382145

ABSTRACT

OBJECTIVES: To evaluate the performance of an artificial intelligence (AI) system (Pegasus, Visulytix Ltd., UK*) at the detection of diabetic retinopathy (DR) from images captured by a handheld portable fundus camera. METHODS: A cohort of 6404 patients (~80% with diabetes mellitus) was screened for retinal diseases using a handheld portable fundus camera (Pictor Plus, Volk Optical Inc., USA) at the Mexican Advanced Imaging Laboratory for Ocular Research. The images were graded for DR by specialists according to the Scottish DR grading scheme. The performance of the AI system was evaluated, retrospectively, in assessing referable DR (RDR) and proliferative DR (PDR) and compared with the performance on a publicly available desktop camera benchmark dataset. RESULTS: For RDR detection, Pegasus performed with an 89.4% (95% CI: 88.0-90.7) area under the receiver operating characteristic (AUROC) curve for the MAILOR cohort, compared with an AUROC of 98.5% (95% CI: 97.8-99.2) on the benchmark dataset. This difference was statistically significant. Moreover, no statistically significant difference was found in performance for PDR detection with Pegasus achieving an AUROC of 94.3% (95% CI: 91.0-96.9) on the MAILOR cohort and 92.2% (95% CI: 89.4-94.8) on the benchmark dataset. CONCLUSIONS: Pegasus showed good transferability for the detection of PDR from a curated desktop fundus camera dataset to real-world clinical practice with a handheld portable fundus camera. However, there was a substantial, and statistically significant, decrease in the diagnostic performance for RDR when using the handheld device.


Subject(s)
Diabetes Mellitus , Diabetic Retinopathy , Artificial Intelligence , Diabetic Retinopathy/diagnostic imaging , Humans , Photography , ROC Curve , Retina , Retrospective Studies
3.
Arch Soc Esp Oftalmol ; 86(4): 103-6, 2011 Apr.
Article in Spanish | MEDLINE | ID: mdl-21569918

ABSTRACT

OBJECTIVE: To determine whether there are changes in the peripapillary nerve fibre layer, in colour vision, contrast sensitivity, dark adaptation and electroretinography changes in these patients who do not have infectious retinitis. METHODS: We studied 52 patients without ocular pathology; the mean age was 35.88 years old. RESULTS: We observed less thickness in all quadrants, except the nasal. The colour vision was altered in 27.77% of the patients. The contrast sensitivity test showed high frequency alterations. There was no statistically significant difference in the electroretinography test or in dark adaptation. CONCLUSIONS: There are changes in the peripapillary nerve fibre layer thickness; also we found changes in colour vision, contrast sensitivity and a decreasing trend of the B wave in the electroreninogram.


Subject(s)
HIV Infections/physiopathology , HIV-1 , Vision Disorders/etiology , Vision Tests , Adult , Color Vision , Contrast Sensitivity , Cross-Sectional Studies , Electroretinography , Female , HIV Infections/complications , HIV Infections/pathology , Humans , Male , Optic Disk/pathology , Prospective Studies , Retina/pathology , Tomography, Optical Coherence
4.
Arch. Soc. Esp. Oftalmol ; 86(4): 103-106, abr. 2011. tab
Article in Spanish | IBECS | ID: ibc-92517

ABSTRACT

Objetivo: Encontrar si existen alteraciones en el grosor de la capa de fibras nerviosas peripapilares,en la visión al color, sensibilidad al contraste, adaptación a la oscuridad y cambioselectrorretinográficos en estos pacientes, que no presentan retinitis infecciosa.Métodos: Se les realizaron las pruebas a 52 pacientes sin evidencia de enfermedad ocular. Elpromedio de edad fue de 35,88 años.Resultados: Se observó una disminución en el grosor de las fibras nerviosas en todos los cuadrantes,menos en el nasal. La visión al color se mostró alterada en el 27,77% de los pacientes.El estudio de sensibilidad al contraste demostró alteraciones en las frecuencias altas. No seencontró diferencia estadísticamente significativa en las pruebas de electrorretinograma nien adaptación a la oscuridad.Conclusiones: Existe alteración en el grosor de fibras nerviosas peripapilares; además seencontraron alteraciones en la visión al color, sensibilidad al contraste y una tendenciaa la disminución de la onda B del electrorretinograma(AU)


Objective: To determine whether there are changes in the peripapillary nerve fibre layer, incolour vision, contrast sensitivity, dark adaptation and electroretinography changes in thesepatients who do not have infectious retinitis.Methods: We studied 52 patients without ocular pathology; the mean age was 35.88 yearsold.Results: We observed less thickness in all quadrants, except the nasal. The colour vision was altered in 27.77% of the patients. The contrast sensitivity test showed high frequency alterations. There was no statistically significant difference in the electroretinography test or in dark adaptation. Conclusions: There are changes in the peripapillary nerve fibre layer thickness; also we foundchanges in colour vision, contrast sensitivity and a decreasing trend of the B wave in theelectroreninogram(AU)


Subject(s)
Humans , Male , Female , HIV Infections/complications , Retinal Neurons/pathology , Optic Nerve/pathology , Tomography, Optical Coherence/methods , HIV , Atrophy , Color Vision , Contrast Sensitivity , Prospective Studies
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