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.
The present project combines clinical and multimodal imaging biomarkers to expand the current understanding of the pathogenic, clinical course, and phenotypic manifestations of age-related macular degeneration. Beyond identifying potential novel biomarkers predictive of the disease course and the development of macular complications, this study will also provide a model of predictivity applied in daily clinical practice.
The proponent of this project has already been involved in research projects on the topic, accounting for relevant experience cultivated during Ph.D., fellowship, and training periods abroad. Moreover, these experiences created valuable and solid collaborations with international groups leaders in the field.
Based on the background and expertise on this relevant topic, the goal of the project is to characterize potential biomarkers easily recognizable during a routine clinical exam, identifying potential novel predictors. New and known biomarkers will be all included in a stepwise model, which will be essential in understanding the potentiality of every single biomarker or combining clinical features that may design a risk phenotype depending on the technology used and according to the complication subtypes that can be characterized by neovascular tissue or retinal atrophy. Since the exact mechanisms and lifecycle of AMD are not completely understood, the identification of a more robust model that considers different approaches customizable in the clinical setting may be beneficial with broad clinical applicability. Moreover, it will contribute to driving a tailored approach for disease progression and monitoring.
The need to control the progression of AMD at an early stage represents the key to reduce 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.