The goal of this prospective, multinational, multicenter observational study is to to predict conversion of early and intermediate AMD with functional vision to advanced AMD with irreversible loss of vision on an individual-based level over 2 years. The main objectives of this study are: * Identify and quantify focal and global alterations in the retina in regard to disease progression. * Assess the individual risk of disease progression in intermediate AMD patients converting to advanced AMD based on imaging. * Specify the course of disease in regard to the sequence of events that lead to the conversion to advanced AMD * Enhance the ability to classify AMD using artificial intelligence in addition to traditional models. All patients will be followed for 24 months with 6 month intervals to assess clinical changes. Monitoring of disease progression will be performed using the following routine in-vivo imaging procedures: * Scanning Laser Fundus Photography * Color Fundus Photography (CFP) * Optical Coherence Tomography (OCT) * Optical Coherence Tomography Angiography (OCTA) Patients will be asked for their medical history. Standard ophthalmic examination, as well as a questionnaire on visual function will be carried out. No intervention will be performed during the study since no treatment is yet available within Europe. As soon as treatment is approved in the EU, patients in this cohort might receive treatment according to availability in their respective country and standard of care. If treatment will be performed, it will be as standard of care outside the study according to each country's standard of care and by EMA label.
Study Type
OBSERVATIONAL
Enrollment
500
Medical University of Vienna
Vienna, Austria
NOT_YET_RECRUITINGCHU Dijon
Dijon, France
RECRUITINGUniversity Medical Center Ljubljana
Ljubljana, Slovenia
RECRUITINGFundacio de Recerca Clinic Barcelona-Institut D Investigacions Biomed
Barcelona, Spain
RECRUITINGVista Klinik Binningen
Binningen, Switzerland
RECRUITINGUniversity of Zürich
Zurich, Switzerland
RECRUITINGQueen's Unviversity Belfast
Belfast, United Kingdom
RECRUITINGTo characterise and quantify focal and global changes of the retina by retinal imaging to identify patients at risk for conversion to advanced AMD.
The correlation between biomarkers (independent variables) and progression will be assessed by linear mixed models or prospectively by Cox-regression models. Artificial intelligence models will be applied to assess progression speed and predict local and global progression. Mixed Effects models will be calculated to estimate the association between independent variables, including the timepoint as an independent variable, on individual markers of progression (PR thinning and PR loss expansion).
Time frame: 2 years
To identify and quantify disease progression-related biomarkers
Longitudinal assessments of imaging biomarkers are performed in a descriptive manner. The following biomarkers will be evaluated in detail as independent variables: * Drusen volume/Refractile drusen (scale, nl) * Subretinal Drusenoid Deposits (SDD) (scale, mm2) * Hyperreflective Foci (HRF) (scale, nl) * Thinning of outer retinal layers (PR thinning) (scale, µm) * Loss of outer retinal layers (RPE and PR) (scale, mm2) * PR loss/RPE loss ratio (scale, ratio) * Other retinal biomarkers if relevant to the progression of intermediate AMD to advanced AMD The correlation between biomarkers (independent variables) and disease progression will be assessed by linear mixed models or prospectively by Cox-regression models. Mixed Effects models will be calculated to estimate the association between independent variables, including the timepoint as an independent variable, on individual markers of progression (PR thinning and PR loss expansion).
Time frame: 2 years
To evaluate monitoring of AMD progression assisted by AI algorithms
The following will be provided by AI-based image analysis of the GA Monitor (independent variables used to detect an event for the Cox-regression model): * RPE integrity loss (mm2) in the 1mm central area, 6mm area, and the respective relative change to previous visit * PR integrity loss (mm2) in the 1mm central area, 6mm area, and the respective relative change to previous visit The following will be provided by AI-based image analysis of the Fluid Monitor (independent variables used to detect an event for the Cox-regression model): * Intraretinal fluid volume (nl) in the 1mm central area, 6 mm area, and the respective relative change to previous visit * Subretinal fluid volume (nl) in the 1mm central area, 6 mm area, and the respective relative change to previous visit * Pigment epithelium detachment volume (nl) in the 1mm central area, 6mm area, and the respective relative change to previous visit
Time frame: 2 years
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