Article ; Online: Systemic retinal biomarkers.
Current opinion in ophthalmology
2021 Volume 32, Issue 5, Page(s) 439–444
Abstract: Purpose of review: Systemic retinal biomarkers are biomarkers identified in the retina and related to evaluation and management of systemic disease. This review summarizes the background, categories and key findings from this body of research as well as ...
Abstract | Purpose of review: Systemic retinal biomarkers are biomarkers identified in the retina and related to evaluation and management of systemic disease. This review summarizes the background, categories and key findings from this body of research as well as potential applications to clinical care. Recent findings: Potential systemic retinal biomarkers for cardiovascular disease, kidney disease and neurodegenerative disease were identified using regression analysis as well as more sophisticated image processing techniques. Deep learning techniques were used in a number of studies predicting diseases including anaemia and chronic kidney disease. A virtual coronary artery calcium score performed well against other competing traditional models of event prediction. Summary: Systemic retinal biomarker research has progressed rapidly using regression studies with clearly identified biomarkers such as retinal microvascular patterns, as well as using deep learning models. Future systemic retinal biomarker research may be able to boost performance using larger data sets, the addition of meta-data and higher resolution image inputs. |
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MeSH term(s) | Anemia/diagnosis ; Anemia/diagnostic imaging ; Biomarkers ; Cardiovascular Diseases/diagnosis ; Cardiovascular Diseases/diagnostic imaging ; Humans ; Image Processing, Computer-Assisted ; Kidney Diseases/diagnosis ; Kidney Diseases/diagnostic imaging ; Neurodegenerative Diseases/diagnosis ; Neurodegenerative Diseases/diagnostic imaging ; Retina/diagnostic imaging |
Chemical Substances | Biomarkers |
Language | English |
Publishing date | 2021-07-09 |
Publishing country | United States |
Document type | Journal Article ; Review |
ZDB-ID | 1049383-9 |
ISSN | 1531-7021 ; 1040-8738 |
ISSN (online) | 1531-7021 |
ISSN | 1040-8738 |
DOI | 10.1097/ICU.0000000000000784 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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