Analysis of the asymmetry between both eyes in early diagnosis of glaucoma combining features extracted from retinal images and OCTs into classification models

This study aims to analyze the asymmetry between both eyes of the same patient for the early diagnosis of glaucoma. Two imaging modalities, retinal fundus images and optical coherence tomographies (OCTs), have been considered in order to compare their different capabilities for glaucoma detection. From retinal fundus images, the difference between cup/disc ratio and the width of the optic rim has been extracted. Analogously, the thickness of the retinal nerve fiber layer has been measured in spectral-domain optical coherence tomographies. These measurements have been considered as asymmetry characteristics between eyes in the modeling of decision trees and support vector machines for the classification of healthy and glaucoma patients. The main contribution of this work is indeed the use of different classification models with both imaging modalities to jointly exploit the strengths of each of these modalities for the same diagnostic purpose based on the asymmetry characteristics between the eyes of the patient. The results show that the optimized classification models provide better performance with OCT asymmetry features between both eyes (sensitivity 80.9%, specificity 88.2%, precision 66.7%, accuracy 86.5%) than with those extracted from retinographies, although a linear relationship has been found between certain asymmetry features extracted from both imaging modalities. Therefore, the resulting performance of the models based on asymmetry features proves their ability to differentiate healthy from glaucoma patients using those metrics. Models trained from fundus characteristics are a useful option as a glaucoma screening method in the healthy population, although with lower performance than those trained from the thickness of the peripapillary retinal nerve fiber layer. In both imaging modalities, the asymmetry of morphological characteristics can be used as a glaucoma indicator, as detailed in this work.This work has been partially supported by Spanish National projects AES2017–PI17/00771, AES2017–PI17/00821 (Instituto de Salud Carlos III), and Regional project 20901/PI/18 (Fundación Séneca)

PAPILA: Dataset with fundus images and clinical data of both eyes of the same patient for glaucoma assessment

Glaucoma is one of the ophthalmological diseases that frequently causes loss of vision in today’s society. Previous studies assess which anatomical parameters of the optic nerve can be predictive of glaucomatous damage, but to date there is no test that by itself has sufficient sensitivity and specificity to diagnose this disease. This work provides a public dataset with medical data and fundus images of both eyes of the same patient. Segmentations of the cup and optic disc, as well as the labeling of the patients based on the evaluation of clinical data are also provided. The dataset has been tested with a neural network to classify healthy and glaucoma patients. Specifically, the ResNet-50 has been used as the basis to classify patients using information from each eye independently as well as using the joint information from both eyes of each patient. Results provide the baseline metrics, with the aim of promoting research in the early detection of glaucoma based on the joint analysis of both eyes of the same patient.This work has been partially funded by Spanish National projects AES2017-PI17/00771 and AES2017-PI17/00821 (Instituto de Salud Carlos III) and regional project 20901/PI/18 (Fundación Séneca)

Automatic Segmentation of the Retinal Nerve Fiber Layer by Means of Mathematical Morphology and Deformable Models in 2D Optical Coherence Tomography Imaging

[EN] Glaucoma is a neurodegenerative disease process that leads to progressive damage of the optic nerve to produce visual impairment and blindness. Spectral-domain OCT technology enables peripapillary circular scans of the retina and the measurement of the thickness of the retinal nerve fiber layer (RNFL) for the assessment of the disease status or progression in glaucoma patients. This paper describes a new approach to segment and measure the retinal nerve fiber layer in peripapillary OCT images. The proposed method consists of two stages. In the first one, morphological operators robustly detect the coarse location of the layer boundaries, despite the speckle noise and diverse artifacts in the OCT image. In the second stage, deformable models are initialized with the results of the previous stage to perform a fine segmentation of the boundaries, providing an accurate measurement of the entire RNFL. The results of the RNFL segmentation were qualitatively assessed by ophthalmologists, and the measurements of the thickness of the RNFL were quantitatively compared with those provided by the OCT inbuilt software as well as the state-of-the-art methods.This work was partially funded by Spanish National projects AES2017-PI17/00771 and AES2017-PI17/00821 (Instituto de Salud Carlos III), PID2019-105142RB-C21 (AI4SKIN) (Spanish Ministry of Economy and Competitiveness), PTA2017-14610-I (State Research Spanish Agency), regional project 20901/PI/18 (Fundacion Seneca) and Polytechnic University of Valencia (PAID-01-20).Berenguer-Vidal, R.; Verdú-Monedero, R.; Morales-Sánchez, J.; Sellés-Navarro, I.; Del Amor, R.; García-Pardo, JG.; Naranjo Ornedo, V. (2021). Automatic Segmentation of the Retinal Nerve Fiber Layer by Means of Mathematical Morphology and Deformable Models in 2D Optical Coherence Tomography Imaging. Sensors. 21(23):1-30. https://doi.org/10.3390/s21238027S130212

Oxidative stress mediates epigenetic modifications and the expression of miRNAs and genes related to apoptosis in diabetic retinopathy patients

Producción CientíficaKnowledge on the underlying mechanisms and molecular targets for managing the ocular complications of type 2 diabetes mellitus (T2DM) remains incomplete. Diabetic retinopathy (DR) is a major cause of irreversible visual disability worldwide. By using ophthalmological and molecular-genetic approaches, we gathered specific information to build a data network for deciphering the crosslink of oxidative stress (OS) and apoptosis (AP) processes, as well as to identify potential epigenetic modifications related to noncoding RNAs in the eyes of patients with T2DM. A total of 120 participants were recruited, being classified into two groups: individuals with T2MD (T2MDG, n = 67), divided into a group of individuals with (+DR, n = 49) and without (−DR, n = 18) DR, and a control group (CG, n = 53). Analyses of compiled data reflected significantly higher plasma levels of malondialdehyde (MDA), superoxide dismutase (SOD), and glutathione peroxidase (GPx) and significantly lower total antioxidant capacity (TAC) in the +DR patients compared with the −DR and the CG groups. Furthermore, the plasma caspase-3 (CAS3), highly involved in apoptosis (AP), showed significantly higher values in the +DR group than in the −DR patients. The microRNAs (miR) hsa-miR 10a-5p and hsa-miR 15b-5p, as well as the genes BCL2L2 and TP53 involved in these pathways, were identified in relation to DR clinical changes. Our data suggest an interaction between OS and the above players in DR pathogenesis. Furthermore, potential miRNA-regulated target genes were identified in relation to DR. In this concern, we may raise new diagnostic and therapeutic challenges that hold the potential to significantly improve managing the diabetic eye.Instituto de Salud Carlos III, Red de Enfermedades Inflamatorias (REI), Fondo Europeo de Desarrollo Regional (FEDER), NextGenerationEU - (grant RD21/0002/0032)Comunidad Valenciana, Fundación para el Fomento de la Salud y la Investigación Biomédica (FISABIO) - (Project MACBIO/2022-2023: UGP-21-216

Efecto a corto y largo plazo de diferentes períodos de isquemia transitoria en la supervivencia de las células ganglionares de la retina de rata adulta: estudio cuantitativo

La retina es un tejido nervioso que parece tener una mayor tolerancia ante situaciones de hipoxia que el resto del sistema nervioso central (SNC). Sin embargo, las consecuencias funcionales derivadas de la privación de flujo sanguíneo son graves y en la mayoría de los casos irreversibles. Se han realizado numerosas investigaciones con el fin de conocer las alteraciones morfológicas y funcionales de la retina ante situaciones de isquemia de diferente intensidad, sin embargo se carecen de … [+]estudios que caractericen específicamente el comportamiento de las células ganglionares de la retina (GCR) ante la isquemia utilizando métodos que nos permiten cuantificar la muerte de las (GCR). Queremos determinar su grado de tolerancia ante la isquemia, y estudiar el patrón de muerte de estas células tras someterlas a diferentes periodos de isquemia transitoria basándonos en técnicas neuroanatómicas. Hemos marcado las CGR con un trazador neuronal fluorescente, el fluoro-Gold, que aplicado en los principales núcleos de proyección de la vía óptica de la rata adulta nos ha permitido distinguir y diferenciar las CG

Decision Trees for Glaucoma Screening Based on the Asymmetry of the Retinal Nerve Fiber Layer in Optical Coherence Tomography

Purpose: The aim of this study was to analyze the relevance of asymmetry features between both eyes of the same patient for glaucoma screening using optical coherence tomography. Methods: Spectral-domain optical coherence tomography was used to estimate the thickness of the peripapillary retinal nerve fiber layer in both eyes of the patients in the study. These measurements were collected in a dataset from healthy and glaucoma patients. Several metrics for asymmetry in the retinal nerve fiber layer thickness between the two eyes were then proposed. These metrics were evaluated using the dataset by performing a statistical analysis to assess their significance as relevant features in the diagnosis of glaucoma. Finally, the usefulness of these asymmetry features was demonstrated by designing supervised machine learning models that can be used for the early diagnosis of glaucoma. Results: Machine learning models were designed and optimized, specifically decision trees, based on the values of proposed asymmetry metrics. The use of these models on the dataset provided good classification of the patients (accuracy 88%, sensitivity 70%, specificity 93% and precision 75%). Conclusions: The obtained machine learning models based on retinal nerve fiber layer asymmetry are simple but effective methods which offer a good trade-off in classification of patients and simplicity. The fast binary classification relies on a few asymmetry values of the retinal nerve fiber layer thickness, allowing their use in the daily clinical practice for glaucoma screening

Analysis of SNP Array Abnormalities in Patients with DE NOVO Acute Myeloid Leukemia with Normal Karyotype

Nearly 50% of patients with de novo acute myeloid leukemia (AML) harbor an apparently normal karyotype (NK) by conventional cytogenetic techniques showing a very heterogeneous prognosis. This could be related to the presence of cryptic cytogenetic abnormalities (CCA) not detectable by conventional methods. The study of copy number alterations (CNA) and loss of heterozygozity (LOH) in hematological malignancies is possible using a high resolution SNP-array. Recently, in clinical practice the karyotype study has been complemented with the identifcation of point mutations in an increasing number of genes. We analyzed 252 de novo NK-AML patients from Hospital La Fe (n=44) and from previously reported cohorts (n=208) to identify CCA by SNP-array, and to integrate the analysis of CCA with molecular alterations detected by Next-Generation-sequencing. CCA were detected in 58% of patients. In addition, 49% of them harbored CNA or LOH and point mutations, simultaneously. Patients were grouped in 3 sets by their abnormalities: patients carrying several CCA simultaneously, patients with mutations in FLT3, NPM1 and/or DNMT3A and patients with an amalgam of mutations. We found a negative correlation between the number of CCA and the outcome of the patients. This study outlines that CCA are present in up to 50% of NK-AML patients and have a negative impact on the outcome. CCA may contribute to the heterogeneous prognosis.This study was supported by research funding from FEDER funds (CIBERONC (CB16/12/00284)), “Fundación Española de Hematología (FEHH)”; “Red Temática de Investigación Cooperativa en Cancer” grant (RD12/0036/0014), and the “Red Cooperativa de Biobancos Hospitalarios” (RD09/0076/00021); “Instituto de Salud Carlos III” grants PI12/01047, PI13/01640, PT13/0010/0026, PIE13/00046, PI16/011113 and PI16/00665; the research grant 2013/0327 from the “Instituto Investigación Sanitaria Hospital La Fe”; and from the “Consellería de Educación, Cultura y Deporte” PROMETEO/2011/025 and PROMETEOII/2015/008.Biotecnologí