Shi, Danli;
Zhou, Yukun;
He, Shuang;
Wagner, Siegfried K;
Huang, Yu;
Keane, Pearse A;
Ting, Daniel SW;
... He, Mingguang; + view all
(2024)
Cross-modality Labeling Enables Noninvasive Capillary Quantification as a Sensitive Biomarker for Assessing Cardiovascular Risk.
Ophthalmology Science
, 4
(3)
, Article 100441. 10.1016/j.xops.2023.100441.
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Abstract
PURPOSE: We aim to use fundus fluorescein angiography (FFA) to label the capillaries on color fundus (CF) photographs and train a deep learning model to quantify retinal capillaries noninvasively from CF and apply it to cardiovascular disease (CVD) risk assessment. DESIGN: Cross-sectional and longitudinal study. PARTICIPANTS: A total of 90732 pairs of CF-FFA images from 3893 participants for segmentation model development, and 49229 participants in the UK Biobank for association analysis. METHODS: We matched the vessels extracted from FFA and CF, and used vessels from FFA as labels to train a deep learning model (RMHAS-FA) to segment retinal capillaries using CF. We tested the model's accuracy on a manually labeled internal test set (FundusCapi). For external validation, we tested the segmentation model on 7 vessel segmentation datasets, and investigated the clinical value of the segmented vessels in predicting CVD events in the UK Biobank. MAIN OUTCOME MEASURES: Area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity for segmentation. Hazard ratio (HR; 95% confidence interval [CI]) for Cox regression analysis. RESULTS: On the FundusCapi dataset, the segmentation performance was AUC = 0.95, accuracy = 0.94, sensitivity = 0.90, and specificity = 0.93. Smaller vessel skeleton density had a stronger correlation with CVD risk factors and incidence (P < 0.01). Reduced density of small vessel skeletons was strongly associated with an increased risk of CVD incidence and mortality for women (HR [95% CI] = 0.91 [0.84-0.98] and 0.68 [0.54-0.86], respectively). CONCLUSIONS: Using paired CF-FFA images, we automated the laborious manual labeling process and enabled noninvasive capillary quantification from CF, supporting its potential as a sensitive screening method for identifying individuals at high risk of future CVD events. FINANCIAL DISCLOSURES: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
| Type: | Article |
|---|---|
| Title: | Cross-modality Labeling Enables Noninvasive Capillary Quantification as a Sensitive Biomarker for Assessing Cardiovascular Risk |
| Location: | Netherlands |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.xops.2023.100441 |
| Publisher version: | http://dx.doi.org/10.1016/j.xops.2023.100441 |
| Language: | English |
| Additional information: | © 2024 Published by Elsevier Inc. on behalf of the American Academy of 1 Ophthalmology. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
| Keywords: | Cardiovascular disease, Cross-modality labeling, RMHAS-FA, Retinal capillary quantification |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Institute of Ophthalmology |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10188490 |
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