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Microvascular Metrics on Diabetic Retinopathy Severity: Analysis of Diabetic Eye Images from Real-World Data

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Title: Microvascular Metrics on Diabetic Retinopathy Severity: Analysis of Diabetic Eye Images from Real-World Data
Authors: Cristina Cuscó, Pau Esteve-Bricullé, Ana Almazán-Moga, Jimena Fernández-Carneado, Berta Ponsati
Source: Biomedicines, Vol 12, Iss 12, p 2753 (2024)
Publisher Information: MDPI AG, 2024.
Publication Year: 2024
Collection: LCC:Biology (General)
Subject Terms: diabetic retinopathy, retinal fundus imaging, real-world data, microvascular lesions, retinal biomarkers, diabetic retinopathy severity grading, Biology (General), QH301-705.5
More Details: Objective: To quantify microvascular lesions in a large real-world data (RWD) set, based on single central retinal fundus images of diabetic eyes from different origins, with the aim of validating its use as a precision tool for classifying diabetic retinopathy (DR) severity. Design: Retrospective meta-analysis across multiple fundus image datasets. Sample size: The study analyzed 2445 retinal fundus images from diabetic patients across four diverse RWD international datasets, including populations from Spain, India, China and the US. Intervention: The quantification of specific microvascular lesions: microaneurysms (MAs), hemorrhages (Hmas) and hard exudates (HEs) using advanced automated image analysis techniques on central retinal images to validate reliable metrics for DR severity assessment. The images were pre-classified in the DR severity levels as defined by the International Clinical Diabetic Retinopathy (ICDR) scale. Main Outcome Measures: The primary variables measured were the number of MAs, Hmas, red lesions (RLs) and HEs. These counts were related with DR severity levels using statistical methods to validate the relationship between lesion counts and disease severity. Results: The analysis revealed a robust and statistically significant increase (p < 0.001) in the number of microvascular lesions and the DR severity across all datasets. Tight data distributions were reported for MAs, Hmas and RLs, supporting the reliability of lesion quantification for accurately assessing DR severity. HEs also followed a similar pattern, but with a broader dispersion of data. Data used in this study are consistent with the definition of the DR severity levels established by the ICDR guidelines. Conclusions: The statistically significant increase in the number of microvascular lesions across DR severity validate the use of lesion quantification in a single central retinal field as a key biomarker for disease classification and assessment. This quantification method demonstrates an improvement over traditional assessment scales, providing a quantitative microvascular metric that enhances the precision of disease classification and patient monitoring. The inclusion of a numerical component allows for the detection of subtle variations within the same severity level, offering a deeper understanding of disease progression. The consistency of results across diverse datasets not only confirms the method’s reliability but also its applicability in a global healthcare setting.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 2227-9059
Relation: https://www.mdpi.com/2227-9059/12/12/2753; https://doaj.org/toc/2227-9059
DOI: 10.3390/biomedicines12122753
Access URL: https://doaj.org/article/3be0aaa6d2634ceeb829006367dddc19
Accession Number: edsdoj.3be0aaa6d2634ceeb829006367dddc19
Database: Directory of Open Access Journals
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  Data: Objective: To quantify microvascular lesions in a large real-world data (RWD) set, based on single central retinal fundus images of diabetic eyes from different origins, with the aim of validating its use as a precision tool for classifying diabetic retinopathy (DR) severity. Design: Retrospective meta-analysis across multiple fundus image datasets. Sample size: The study analyzed 2445 retinal fundus images from diabetic patients across four diverse RWD international datasets, including populations from Spain, India, China and the US. Intervention: The quantification of specific microvascular lesions: microaneurysms (MAs), hemorrhages (Hmas) and hard exudates (HEs) using advanced automated image analysis techniques on central retinal images to validate reliable metrics for DR severity assessment. The images were pre-classified in the DR severity levels as defined by the International Clinical Diabetic Retinopathy (ICDR) scale. Main Outcome Measures: The primary variables measured were the number of MAs, Hmas, red lesions (RLs) and HEs. These counts were related with DR severity levels using statistical methods to validate the relationship between lesion counts and disease severity. Results: The analysis revealed a robust and statistically significant increase (p &lt; 0.001) in the number of microvascular lesions and the DR severity across all datasets. Tight data distributions were reported for MAs, Hmas and RLs, supporting the reliability of lesion quantification for accurately assessing DR severity. HEs also followed a similar pattern, but with a broader dispersion of data. Data used in this study are consistent with the definition of the DR severity levels established by the ICDR guidelines. Conclusions: The statistically significant increase in the number of microvascular lesions across DR severity validate the use of lesion quantification in a single central retinal field as a key biomarker for disease classification and assessment. This quantification method demonstrates an improvement over traditional assessment scales, providing a quantitative microvascular metric that enhances the precision of disease classification and patient monitoring. The inclusion of a numerical component allows for the detection of subtle variations within the same severity level, offering a deeper understanding of disease progression. The consistency of results across diverse datasets not only confirms the method’s reliability but also its applicability in a global healthcare setting.
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