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- Normative mice retinal thickness: 16-month longitudinal characterization of wild-type mice and changes in a model of Alzheimer's diseasePublication . Batista, Ana; Guimarães, Pedro; Martins, João; Moreira, Paula I.; Ambrósio, António F.; Castelo-Branco, Miguel; Serranho, Pedro; Bernardes, RuiAnimal models of disease are paramount to understand retinal development, the pathophysiology of eye diseases, and to study neurodegeneration using optical coherence tomography (OCT) data. In this study, we present a comprehensive normative database of retinal thickness in C57BL6/129S mice using spectral-domain OCT data. The database covers a longitudinal period of 16 months, from 1 to 16 months of age, and provides valuable insights into retinal development and changes over time. Our findings reveal that total retinal thickness decreases with age, while the thickness of individual retinal layers and layer aggregates changes in different ways. For example, the outer plexiform layer (OPL), photoreceptor inner segments (ILS), and retinal pigment epithelium (RPE) thickened over time, whereas other retinal layers and layer aggregates became thinner. Additionally, we compare the retinal thickness of wild-type (WT) mice with an animal model of Alzheimer's disease (3×Tg-AD) and show that the transgenic mice exhibit a decrease in total retinal thickness compared to age-matched WT mice, with statistically significant differences observed at all evaluated ages. This normative database of retinal thickness in mice will serve as a reference for future studies on retinal changes in neurodegenerative and eye diseases and will further our understanding of the pathophysiology of these conditions.
- Shedding light on early central nervous system changes for Alzheimer’s disease through the retina: an animal studyPublication . Bernardes, Rui; Ferreira, Hugo; Guimarães, Pedro; Serranho, PedroThe World Health Organization (WHO) 2015 projections estimated 75.6 million people living with dementia in 2030, an update from the 66 million estimated in 2013. These figures account for all types of dementia, but Alzheimer’s disease stands out as the most common estimated type, representing 60% to 80% of the cases. An increasing number of research groups adopted the approach of using the retina as a window to the brain. Besides being the visible part of the central nervous system, the retina is readily available through non-invasive imaging techniques such as optical coherence tomography (OCT). Moreover, cumulative evidence indicates that neurodegenerative diseases can also affect the retina. In the work reported herein, we imaged the retina of wild-type and the triple-transgenic mouse model of Alzheimer’s disease, at the ages of one-, two-, three-, four-, eight-, twelve- and sixteen-months-old, by OCT and segmented gathered data using a developed convolutional neural network into distinct layers. Group differences through texture analysis of computed fundus images for five layers of the retina, normative retinal thickness data throughout the observation period of the ageing mice, and findings related to the estimation of the ageing effect of the human genes present in the transgenic group, as well as the classification of individual fundus images through convolutional neural networks, will be presented and thoroughly discussed in the Special Session on ”New Developments in Imaging for Ocular and Neurodegenerative Disorders”.
- Retinal imaging in animal models: searching for biomarkers of neurodegenerationPublication . Batista, Ana; Guimarães, Pedro; Serranho, Pedro; Nunes, Ana; Martins, João; Moreira, Paula I.; Ambrósio, António F.; Morgado, Miguel; Castelo-Branco, Miguel; Bernardes, RuiThere is a pressing need for novel diagnostic and progression biomarkers of neurodegeneration. However, the inability to determine disease duration and stage in patients with Alzheimer’s disease (AD) hinders their discovery. Because animal models of disease allow us to circumvent some of these limitations, they have proven to be of paramount importance in clinical research. Due to the clear optics of the eye, the retina combined with optical coherence tomography (OCT) offers the perfect opportunity to image neurodegeneration in the retina in vivo, non-invasively, directly, quickly, and inexpensively. Based on these premises, our group has worked towards uncovering neurodegeneration-associated changes in the retina of the triple-transgenic mouse model of familial AD (3×Tg-AD). In this work, we present an overview of our work on this topic. We report on thickness variations of the retina and retinal layers/layer aggregates caused by healthy aging and AD-like conditions and discuss the implications of focusing research efforts solely on retinal thickness. We explore what other information is embedded in the OCT data, extracted based on texture analysis and deep-learning approaches, to further identify biomarkers that could be used for early detection and diagnosis. We were able to detect changes in the retina of the animal model of AD as early as 1 month of age. We also discuss our work to develop an optical coherence elastography system to measure retinal elasticity, which can be used in conjunction with conventional OCT. Finally, we discuss the potential application of these technologies in human patients and the steps needed to make OCT a helpful screening tool for the detection of neurodegeneration.
- The hemodynamic response function as a type 2 diabetes biomarker: a data-driven approachPublication . Guimarães, Pedro; Serranho, Pedro; Duarte, João V.; Crisóstomo, Joana; Moreno, Carolina; Gomes, Leonor; Bernardes, Rui; Castelo-Branco, MiguelIntroduction: There is a need to better understand the neurophysiological changes associated with early brain dysfunction in Type 2 diabetes mellitus (T2DM) before vascular or structural lesions. Our aim was to use a novel unbiased data-driven approach to detect and characterize hemodynamic response function (HRF) alterations in T2DM patients, focusing on their potential as biomarkers. Methods: We meshed task-based event-related (visual speed discrimination) functional magnetic resonance imaging with DL to show, from an unbiased perspective, that T2DM patients’ blood-oxygen-level dependent response is altered. Relevance analysis determined which brain regions were more important for discrimination. We combined explainability with deconvolution generalized linear model to provide a more accurate picture of the nature of the neural changes. Results: The proposed approach to discriminate T2DM patients achieved up to 95% accuracy. Higher performance was achieved at higher stimulus (speed) contrast, showing a direct relationship with stimulus properties, and in the hemispherically dominant left visual hemifield, demonstrating biological interpretability. Differences are explained by physiological asymmetries in cortical spatial processing (right hemisphere dominance) and larger neural signal-to-noise ratios related to stimulus contrast. Relevance analysis revealed the most important regions for discrimination, such as extrastriate visual cortex, parietal cortex, and insula. These are disease/task related, providing additional evidence for pathophysiological significance. Our data-driven design allowed us to compute the unbiased HRF without assumptions. Conclusion: We can accurately differentiate T2DM patients using a datadriven classification of the HRF. HRF differences hold promise as biomarkers and could contribute to a deeper understanding of neurophysiological changes associated with T2DM.
- When sex matters: differences in the central nervous system as imaged by OCT through the retinaPublication . Nunes, Ana; Serranho, Pedro; Guimarães, Pedro; Ferreira, João; Castelo-Branco, Miguel; Bernardes, RuiBackground: Retinal texture has gained momentum as a source of biomarkers of neurodegeneration, as it is sensitive to subtle differences in the central nervous system from texture analysis of the neuroretina. Sex differences in the retina structure, as detected by layer thickness measurements from optical coherence tomography (OCT) data, have been discussed in the literature. However, the effect of sex on retinal interocular differences in healthy adults has been overlooked and remains largely unreported. Methods: We computed mean value fundus images for the neuroretina layers as imaged by OCT of healthy individuals. Texture metrics were obtained from these images to assess whether women and men have the same retina texture characteristics in both eyes. Texture features were tested for group mean differences between the right and left eye. Results: Corrected texture differences exist only in the female group. Conclusions: This work illustrates that the differences between the right and left eyes manifest differently in females and males. This further supports the need for tight control and minute analysis in studies where interocular asymmetry may be used as a disease biomarker, and the potential of texture analysis applied to OCT imaging to spot differences in the retina.
- Retinal OCT-derived texture features as potential biomarkers for early diagnosis and progression of Diabetic RetinopathyPublication . Oliveira, Sara; Guimarães, Pedro; Campos, Elisa Julião; Fernandes, Rosa; Martins, João; Castelo-Branco, Miguel; Serranho, Pedro; Matafome, Paulo; Bernardes, Rui; Ambrósio, António FranciscoPURPOSE. Diabetic retinopathy (DR) is usually diagnosed many years after diabetes onset. Indeed, an early diagnosis of DR remains a notable challenge, and, thus, developing novel approaches for earlier disease detection is of utmost importance. We aim to explore the potential of texture analysis of optical coherence tomography (OCT) retinal images in detecting retinal changes in streptozotocin (STZ)-induced diabetic animals at “silent” disease stages when early retinal molecular and cellular changes that cannot be clinically detectable are already occurring. METHODS. Volume OCT scans and electroretinograms were acquired before and 1, 2, and 4 weeks after diabetes induction. Automated OCT image segmentation was performed, followed by retinal thickness and texture analysis. Blood-retinal barrier breakdown, glial reactivity, and neuroinflammation were also assessed. RESULTS. Type 1 diabetes induced significant early changes in several texture metrics. At week 4 of diabetes, autocorrelation, correlation, homogeneity, information measure of correlation II (IMCII), inverse difference moment normalized (IDN), inverse difference normalized (INN), and sum average texture metrics decreased in all retinal layers. Similar effects were observed for correlation, homogeneity, IMCII, IDN, and INN at week 2. Moreover, the values of those seven-texture metrics described above decreased throughout the disease progression. In diabetic animals, subtle retinal thinning and impaired retinal function were detected, as well as an increase in the number of Iba1-positive cells (microglia/macrophages) and a subtle decrease in the tight junction protein immunoreactivity, which did not induce any physiologically relevant effect on the blood-retinal barrier. CONCLUSIONS. The effects of diabetes on the retina can be spotted through retinal texture analysis in the early stages of the disease. Changes in retinal texture are concomitant with biological retinal changes, thus unlocking the potential of texture analysis for the early diagnosis of DR. However, this requires to be proven in clinical studies.