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He HL, Liu YX, Liu H, Zhang X, Song H, Xu TZ, Fang Y, Ma Y, Ren HY, Ling SG, Dong Z, Xu J, Qin L, Wong TY, Ang M, Jin ZB. Deep Learning-Enabled Vasculometry Depicts Phased Lesion Patterns in High Myopia Progression. Asia Pac J Ophthalmol (Phila) 2024:100086. [PMID: 39053733 DOI: 10.1016/j.apjo.2024.100086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Revised: 07/10/2024] [Accepted: 07/21/2024] [Indexed: 07/27/2024] Open
Abstract
PURPOSE To investigate the potential phases in myopic retinal vascular alterations for further elucidating the mechanisms underlying the progression of high myopia (HM). METHODS For this retrospective study, participants diagnosed with high myopia at Beijing Tongren Hospital were recruited. Based on bionic mechanisms of human vision, an intelligent image processing model was developed and utilized to extract and quantify the morphological characteristics of retinal vasculatures in different regions measured by papilla-diameter (PD), including vascular caliber, arteriole-to-venule ratio (AVR), tortuosity, the angle of the vascular arch (AVA), the distance of the vascular arch (DVA), density, fractal dimension, and venular length. In addition, the optic disc and the area of peripapillary atrophy (PPA) were also quantified. The characteristics of the overall population, as well as patients aged less than 25 years old, were compared by different genders. Univariate and multiple linear regression analyses were conducted to investigate the correlation of retinal vasculature parameters with PPA width, and detailed trends of the vascular indicators were analyzed to explore the potential existence of staged morphological changes. FINDINGS The study included 14,066 fundus photographs of 5775 patients (aged 41.2 ± 18.6 years), of whom 7379 (61.2 %) were female. The study included 12,067 fundus photographs of 5320 patients (aged 41.2 ± 18.6 years). Significant variations in the morphological parameters of retinal vessels were observed between males and females. After adjusting for age and sex, multiple linear regression analysis showed that an increased PPA width ratio was associated with lower AVA (1PD), DVA (1PD), vascular caliber (0.5-1.0 PD), tortuosity (0.5-1.0 PD), density and fractal dimension (all P < 0.001, Spearman's ρ < 0). Overall, the changes in retinal vascular morphology showed two phases: tortuosity (0.5-1.0PD) and AVA (1PD) decreased rapidly in the first stage but significantly more slowly in the second stage, while vascular density and fractal dimension showed a completely opposite trend with an initial slow decline followed by a rapid decrease. CONCLUSIONS This study identified two distinct phases of retinal vascular morphological changes during the progression of HM. Traction lesions were predominant in the initial stage, while atrophic lesions were predominant in the later stage. These findings provide further insight into the development mechanism of HM from the perspective of retinal vasculature.
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Affiliation(s)
- Hai-Long He
- Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China
| | - Yi-Xin Liu
- Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China
| | - Hanruo Liu
- Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China
| | - Xiaomei Zhang
- School of Statistics, University of International Business and Economics, Beijing, China
| | - Hao Song
- Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China
| | - Tian-Ze Xu
- Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China
| | - Yuxin Fang
- Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China
| | - Ya Ma
- Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China
| | - Hao-Ying Ren
- School of Statistics, University of International Business and Economics, Beijing, China
| | - Sai-Guang Ling
- EVision technology (Beijing) co. LTD, Beijing 100085, China
| | - Zhou Dong
- EVision technology (Beijing) co. LTD, Beijing 100085, China
| | - Jie Xu
- Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China
| | - Lei Qin
- School of Statistics, University of International Business and Economics, Beijing, China; Dong Fureng Institute of Economic and Social Development, Wuhan University, Wuhan, China
| | - Tien Yin Wong
- Tsinghua Medicine, Tsinghua University, Beijing, China; Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
| | - Marcus Ang
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
| | - Zi-Bing Jin
- Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China.
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Freiberg J, Welikala R, Rovelt J, Barman SA, Owen CG, Rudnicka AR, Kolko M. Longitudinal associations of retinal vessel morphology with intraocular pressure and blood pressure at follow-up visit-Findings from a Danish eye and vision cohort, Project FOREVER. Acta Ophthalmol 2024. [PMID: 38953839 DOI: 10.1111/aos.16737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2024] [Accepted: 06/22/2024] [Indexed: 07/04/2024]
Abstract
PURPOSE To characterise the retinal vasculometry of a Danish eye and vision cohort and examine associations with systolic blood pressure (BP), diastolic BP, mean arterial BP, and intraocular pressure (IOP). DESIGN Longitudinal study. METHODS The retinal vasculature of fundus images from the FOREVER (Finding Ophthalmic Risks and Evaluating the Value of Eye exams and their predictive Reliability) cohort was analysed using a fully automated image analysis program. Longitudinal associations of retinal vessel morphology at follow-up visit with IOP (baseline and follow-up) and BP (follow-up) were examined using multilevel linear regression models adjusting for age, sex and retinal vasculometry at baseline as fixed effects and person as random effect. Width measurements were additionally adjusted for the spherical equivalent. RESULTS A total of 2089 subjects (62% female) with a mean age of 61 (standard deviation 8) years and a mean follow-up period of 4.1 years (SD 0.6 years) were included. The mean arteriolar diameter was approximately 20% thinner than the mean venular diameter, and venules were about 21%-23% less tortuous than arterioles. BP at follow-up was associated with decreased arteriolar diameter from baseline to follow-up. After adjusting for baseline IOP, IOP at follow-up was associated with increased arteriolar tortuosity above baseline (0.59%, 95% CI 0.08-1.10, p-value 0.024). CONCLUSION In a Danish eye and vision cohort, variations in BP and alterations in IOP over time were associated with changes in the width and tortuosity of retinal vessels. Our findings contribute novel insights into retinal vascular alterations over time.
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Affiliation(s)
- Josefine Freiberg
- Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark
| | - Roshan Welikala
- School of Computer Science and Mathematics, Kingston University, Surrey, UK
| | - Jens Rovelt
- Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark
| | - Sarah A Barman
- School of Computer Science and Mathematics, Kingston University, Surrey, UK
| | - Christopher G Owen
- Population Health Research Institute, St. George's, University of London, London, UK
| | - Alicja R Rudnicka
- Population Health Research Institute, St. George's, University of London, London, UK
| | - Miriam Kolko
- Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark
- Department of Ophthalmology, Copenhagen University Hospital, Rigshospitalet, Glostrup, Copenhagen, Denmark
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Freiberg J, Welikala RA, Rovelt J, Owen CG, Rudnicka AR, Kolko M, Barman SA. Automated analysis of vessel morphometry in retinal images from a Danish high street optician setting. PLoS One 2023; 18:e0290278. [PMID: 37616264 PMCID: PMC10449151 DOI: 10.1371/journal.pone.0290278] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 06/29/2023] [Indexed: 08/26/2023] Open
Abstract
PURPOSE To evaluate the test performance of the QUARTZ (QUantitative Analysis of Retinal vessel Topology and siZe) software in detecting retinal features from retinal images captured by health care professionals in a Danish high street optician chain, compared with test performance from other large population studies (i.e., UK Biobank) where retinal images were captured by non-experts. METHOD The dataset FOREVERP (Finding Ophthalmic Risk and Evaluating the Value of Eye exams and their predictive Reliability, Pilot) contains retinal images obtained from a Danish high street optician chain. The QUARTZ algorithm utilizes both image processing and machine learning methods to determine retinal image quality, vessel segmentation, vessel width, vessel classification (arterioles or venules), and optic disc localization. Outcomes were evaluated by metrics including sensitivity, specificity, and accuracy and compared to human expert ground truths. RESULTS QUARTZ's performance was evaluated on a subset of 3,682 images from the FOREVERP database. 80.55% of the FOREVERP images were labelled as being of adequate quality compared to 71.53% of UK Biobank images, with a vessel segmentation sensitivity of 74.64% and specificity of 98.41% (FOREVERP) compared with a sensitivity of 69.12% and specificity of 98.88% (UK Biobank). The mean (± standard deviation) vessel width of the ground truth was 16.21 (4.73) pixels compared to that predicted by QUARTZ of 17.01 (4.49) pixels, resulting in a difference of -0.8 (1.96) pixels. The differences were stable across a range of vessels. The detection rate for optic disc localisation was similar for the two datasets. CONCLUSION QUARTZ showed high performance when evaluated on the FOREVERP dataset, and demonstrated robustness across datasets, providing validity to direct comparisons and pooling of retinal feature measures across data sources.
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Affiliation(s)
- Josefine Freiberg
- Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark
| | - Roshan A. Welikala
- School of Computer Science and Mathematics, Kingston University, Surrey, United Kingdom
| | - Jens Rovelt
- Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark
| | - Christopher G. Owen
- Population Health Research Institute, St. George’s, University of London, London, United Kingdom
| | - Alicja R. Rudnicka
- Population Health Research Institute, St. George’s, University of London, London, United Kingdom
| | - Miriam Kolko
- Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark
- Department of Ophthalmology, Copenhagen University Hospital, Rigshospitalet, Glostrup, Copenhagen, Denmark
| | - Sarah A. Barman
- School of Computer Science and Mathematics, Kingston University, Surrey, United Kingdom
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Abstract
The eye is the window through which light is transmitted and visual sensory signalling originates. It is also a window through which elements of the cardiovascular and nervous systems can be directly inspected, using ophthalmoscopy or retinal imaging. Measurements of ocular parameters may therefore offer important information on the physiology and homeostasis of these two important systems. Here we report the results of a genetic characterisation of retinal vasculature. Four genome-wide association studies performed on different aspects of retinal vasculometry phenotypes, such as arteriolar and venular tortuosity and width, found significant similarities between retinal vascular characteristics and cardiometabolic health. Our analyses identified 119 different regions of association with traits of retinal vasculature, including 89 loci associated arteriolar tortuosity, the strongest of which was rs35131825 (p = 2.00×10-108), 2 loci with arteriolar width (rs12969347, p = 3.30×10-09 and rs5442, p = 1.9E-15), 17 other loci associated with venular tortuosity and 11 novel associations with venular width. Our causal inference analyses also found that factors linked to arteriolar tortuosity cause elevated diastolic blood pressure and not vice versa.
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An empirical study of preprocessing techniques with convolutional neural networks for accurate detection of chronic ocular diseases using fundus images. APPL INTELL 2023; 53:1548-1566. [PMID: 35528131 PMCID: PMC9059700 DOI: 10.1007/s10489-022-03490-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/08/2022] [Indexed: 01/07/2023]
Abstract
Chronic Ocular Diseases (COD) such as myopia, diabetic retinopathy, age-related macular degeneration, glaucoma, and cataract can affect the eye and may even lead to severe vision impairment or blindness. According to a recent World Health Organization (WHO) report on vision, at least 2.2 billion individuals worldwide suffer from vision impairment. Often, overt signs indicative of COD do not manifest until the disease has progressed to an advanced stage. However, if COD is detected early, vision impairment can be avoided by early intervention and cost-effective treatment. Ophthalmologists are trained to detect COD by examining certain minute changes in the retina, such as microaneurysms, macular edema, hemorrhages, and alterations in the blood vessels. The range of eye conditions is diverse, and each of these conditions requires a unique patient-specific treatment. Convolutional neural networks (CNNs) have demonstrated significant potential in multi-disciplinary fields, including the detection of a variety of eye diseases. In this study, we combined several preprocessing approaches with convolutional neural networks to accurately detect COD in eye fundus images. To the best of our knowledge, this is the first work that provides a qualitative analysis of preprocessing approaches for COD classification using CNN models. Experimental results demonstrate that CNNs trained on the region of interest segmented images outperform the models trained on the original input images by a substantial margin. Additionally, an ensemble of three preprocessing techniques outperformed other state-of-the-art approaches by 30% and 3%, in terms of Kappa and F 1 scores, respectively. The developed prototype has been extensively tested and can be evaluated on more comprehensive COD datasets for deployment in the clinical setup.
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Song Y, Cheng W, Li F, Lin F, Wang P, Gao X, Peng Y, Liu Y, Zhang H, Chen S, Fan Y, Zhang R, Wang W, Zhang X. Ocular Factors of Fractal Dimension and Blood Vessel Tortuosity Derived From OCTA in a Healthy Chinese Population. Transl Vis Sci Technol 2022; 11:1. [PMID: 35499823 PMCID: PMC9078077 DOI: 10.1167/tvst.11.5.1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
Purpose To identify the ocular factors of microvascular fractal dimension (FD) and blood vessel tortuosity (BVT) of macula measured with optical coherence tomography angiography (OCTA) in a healthy Chinese population. Methods Healthy subjects without ocular disorders were recruited at Zhongshan Ophthalmic Center. The FD and BVT in the superficial capillary plexus (SCP) and deep capillary plexus (DCP) at the macula were obtained from OCTA images. The FD was calculated using the box-counting method, and the BVT was defined as the ratio of the actual distance between two points to the straight distance on the skeletonized image. Univariate and stepwise multivariate linear regression analyses were performed to identify the ocular factors of FD and BVT, and the results are presented as coefficients and 95% confidence intervals (CIs). Only the right eye of each subject was included. Results A total of 2189 healthy individuals (2189 eyes) were included with a mean age of 49.9 ± 13.2 years; 54.4% were female. In the multivariate model, the FD in the SCP was significantly associated with higher intraocular pressure (IOP) (β = 0.204; 95% CI, 0.073-0.335; P < 0.001), axial length (AL) (β = -0.875; 95% CI, -1.197 to -0.552; P < 0.001; R2 = 0.26; root mean square error [RMSE] = 7.78). The FD in the DCP was significantly associated with best-corrected visual acuity (β = -6.170; 95% CI, -10.175 to -2.166; P = 0.003) and anterior chamber depth (β = -0.348; 95% CI, -0.673 to -0.023; P = 0.036; R2 = 0.10; RMSE = 2.58). Superficial BVT was independently associated with IOP (β = -0.044; 95% CI, -0.079 to -0.009; P = 0.012) and AL (β = 0.097; 95% CI, 0.014-0.181; P = 0.022; R2 = 0.15; RMSE = 2.02). Deep BVT was independently associated with IOP (β = -0.004; 95% CI, -0.009 to -0.0005; P = 0.028) and lens thickness (β = 0.036, 95% CI, 0.003-0.060; P = 0.028; R2 = 0.07, RMSE = 0.25). Conclusions The IOP and AL were dependent ocular parameters variables of FD and BVT in the SCP in this healthy population. The FD in the DCP was also influenced by visual acuity and anterior chamber depth. These factors should be considered when microvascular geometrics are used in the future studies. Translational Relevance This work discovered the influence factors of OCTA geometrics parameters for further establishment of diagnostic model or method for glaucoma and other microvasculature-related ocular diseases.
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Affiliation(s)
- Yunhe Song
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, China
| | - Weijing Cheng
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, China
| | - Fei Li
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, China
| | - Fengbin Lin
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, China
| | - Peiyuan Wang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, China
| | - Xinbo Gao
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, China
| | - Yuying Peng
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, China
| | - Yuhong Liu
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, China
| | - Hengli Zhang
- Department of Ophthalmology, Shijiazhuang People's Hospital, Shijiazhuang, China
| | - Shiyan Chen
- Department of Ophthalmology, Sichuan Academy of Medical Sciences & Sichuan Provincial People's Hospital, Chengdu, China
| | - Yazhi Fan
- The Second Affiliated Hospital of Xi'an Jiaotong University, Shaanxi, China
| | - Ran Zhang
- Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, China
| | - Wei Wang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, China
| | - Xiulan Zhang
- State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, China
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