Multimodal imaging of retinal manifestations of Alzheimer’s disease for early diagnosis and clinical research

Although Alzheimer’s disease (AD) is the number one dementia cause, the currently available diagnostic techniques (brain imaging and cerebrospinal fluid sampling) do not allow preclinical diagnosis or screening due to their high cost, limited resolution and invasiveness. These limitations result in delayed treatment onset and unsuccessful drug development. The retina offers a unique opportunity to overcome these limitations since the neuroretinal tissue can be visualized non-invasively using high-resolution imaging tools. Recent research has shown that aggregated amyloid beta deposits can be detected in the retina using hyperspectral retinal imaging (HSRI). In addition, neurodegeneration of the inner retina and optic nerve, and retinal vascular changes have been also described in the disease. This project aims to develop a diagnostic biomarker for (early) detection of AD based on multimodal retinal imaging (MMRI). The project will use conventional retinal imaging modalities and an HSRI set-up to perform clinical in vivo studies with the aim to deliver evidence of the diagnostic value of the investigated biomarker by addressing the following key question: Can MMRI serve as a biomarker for AD (early) diagnosis? The objective of this study is to collect an MMRI dataset and analyse these data with advanced artificial intelligence (AI) techniques to assess the discriminative and diagnostic power of this biomarker.