Ricerc@Sapienza

Age-related macular degeneration (AMD) represents the main cause of vision loss in the elderly leading to a profound impact on daily life and the healthcare system. Eyes with AMD progress from early stages characterized by drusen to intermediate and late stages characterized by macular neovascularization or macular atrophy that determine the significant impact on visual function leading to legal blindness. Recent advances enable a correlation between histopathological and multimodal imaging features that helped identify in vivo ultrastructural alterations.
The research will investigate the predictive value of different clinical and multimodal imaging biomarkers detected through color fundus photographs, optical coherence tomography (OCT), and optical coherence tomography angiography (OCTA). The study aims to assess the most robust predictors of AMD progression using different technologies and identify potential novel predictors of disease progression. A stepwise approach will be adopted to define a predictive model, which will categorize the imaging features according to the technology used, and then combine all the different parameters considered into a single model.
New and known biomarkers will be all included in the stepwise model, which will be essential in understanding the potentiality of every single biomarker or combining features that may design a risk phenotype.
Tailored monitoring of AMD progression at an early stage represents a key point to control the disease burden, preventing costly follow-up, onerous treatment, and blindness in healthy people with a relatively long-life expectance.
Possible alternative potentialities of this research project will include using these findings to build up more accurate deep learning models and the use of the biomarkers in future and ongoing clinical trials testing therapeutic targets able to arrest the disease progression or prevent further disease evolution.