Endotying neurodegeneration through the eye using multimodal retinal imaging
Endotying neurodegeneration through the eye using multimodal retinal imaging
批准号:
2893169
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2023
资助国家:
英国
项目状态:
未结题
起止时间:
2023 至 --
中文摘要
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英文摘要
Neurodegenerative diseases affect millions of people worldwide and are a global public health challenge. They occur when nerve cells in the brain or peripheral nervous system lose function over time and ultimately die. While no cures currently exist, early detection provides a chance for earlier treatment that may help to prevent or slow disease progression with symptomatic relief to enhance patients' quality of life. However, accurate diagnosis can be challenging. A clinician examining a person to elucidate signs and symptoms over time is usually supported by biomarker data from complex and invasive tests such as MRI and PET imaging and biochemical analysis of cerebrospinal fluid. There is a clinical need for new tests and biomarkers that are quick, less invasive, better tolerated by patients, less expensive, and more accurate [1]. In addition, biomarkers that can predict progression or act as outcome measures in trials of new therapeutics are highly sought.The retina as an accessible part of the human nervous system where we can study nerve cells and small blood vessels [2]. With similarities between the retina and the brain in the composition and structure of cells and vessels and their inflammatory and immunologic reactions to insults combined with the capability to image at a micron level means the eye provides a unique "window" to neurodegeneration and neurovascular dysfunction. Applied to cross-linked datasets collected from patients in Edinburgh has already uncovered evidence of signatures or phenotypes in the eye of diseases affecting the brain such as multiple sclerosis, motor neuron disease, and dementias [3, 4].The SPECTRALIS platform manufactured by our industry partner, Heidelberg Engineering, features 3 types or modes of retinal imaging in one device: Scanning Laser Ophthalmoscopy (SLO) to capture views of the interior surface of the retina featuring the optic nerve head, macula and small blood vessels; Optical coherence tomography (OCT) for cross-sectional imaging of the retina and choroid; OCT-Angiography (OCTA) to image the smallest capillary-level vessel networks. Combining these outputs will enable a detailed characterisation of the vascular systems of the retina and surrounding nerve tissues and further the study of neurodegeneration and neurovascular dysfunction. Generating new insights through the eye will help develop a better understanding, differentiating and monitoring of brain disease, and eventually the development of new therapeutic targets.AimsInvestigate multimodal retinal imaging and analysis as a means of endotyping neurodegeneration.Identify candidate biomarkers derived from imaging for prospective clinical use.Demonstrate the utility of imaging the retina for neurology in diagnosis, prognosis, and monitoring.The specific hypotheses to be examined are:People with different conditions or subtypes of neurodegenerative disease will show significant differences in retinal measures.Retinal measures will correlate with abnormalities found on other clinical tests and brain imaging.Differences in the retina will be evidenced on both cross-sectional and longitudinal measures.Retinal measures will predict patient outcome and/or deterioration.References1. Hansson O. Biomarkers for neurodegenerative diseases. Nat Med. 2021 Jun;27(6):954-963.2. London A, Benhar I, Schwartz M. The retina as a window to the brain-from eye research to CNS disorders. Nat Rev Neurol. 2013 Jan;9(1):44-53.3. Cameron JR (2018). The Eye as a Window to the Brain: investigating the clinical utility of retinal imaging derived biomarkers in the phenotyping of neurodegenerative disease. PhD Thesis, University of Edinburgh, Edinburgh, UK4. Pearson TMC (2019). Multi-modal retinal scanning for diagnostic and therapeutic biomarker discovery in neurodegenerative disease. PhD Thesis, University of Edinburgh, Edinburgh, UK
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