Loading...
2 results
Search Results
Now showing 1 - 2 of 2
- 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.