Center for Innovative Biomedicine and Biotechnology

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Stage-independent biomarkers for Alzheimer’s disease from the living retina: an animal study

Publication . Ferreira, Hugo; Serranho, Pedro; Guimarães, Pedro; Trindade, Rita; Martins, João; Moreira, Paula I.; Ambrósio, António Francisco; Castelo-Branco, Miguel; Bernardes, Rui

The early diagnosis of neurodegenerative disorders is still an open issue despite the many efforts to address this problem. In particular, Alzheimer’s disease (AD) remains undiagnosed for over a decade before the first symptoms. Optical coherence tomography (OCT) is now common and widely available and has been used to image the retina of AD patients and healthy controls to search for biomarkers of neurodegeneration. However, early diagnosis tools would need to rely on images of patients in early AD stages, which are not available due to late diagnosis. To shed light on how to overcome this obstacle, we resort to 57 wild-type mice and 57 triple-transgenic mouse model of AD to train a network with mice aged 3, 4, and 8 months and classify mice at the ages of 1, 2, and 12 months. To this end, we computed fundus images from OCT data and trained a convolution neural network (CNN) to classify those into the wild-type or transgenic group. CNN performance accuracy ranged from 80 to 88% for mice out of the training group’s age, raising the possibility of diagnosing AD before the first symptoms through the non-invasive imaging of the retina.

2022Journal article

Open access

Retinal OCT-derived texture features as potential biomarkers for early diagnosis and progression of Diabetic Retinopathy

Publication . Oliveira, Sara; Guimarães, Pedro; Campos, Elisa Julião; Fernandes, Rosa; Martins, João; Castelo-Branco, Miguel; Serranho, Pedro; Matafome, Paulo; Bernardes, Rui; Ambrósio, António Francisco

PURPOSE. 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.

2025Journal article

Open access