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Distribution and determinants of choroidal vascularity index in healthy eyes from deep-learning choroidal analysis: a population-based SS-OCT study
  1. Meng Xuan1,
  2. Cong Li1,
  3. Xiangbin Kong2,
  4. Jian Zhang1,
  5. Wei Wang1,
  6. Mingguang He1,3,4,5,6
  1. 1 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
  2. 2 Department of Ophthalmology, Affiliated Foshan Hospital, Southern Medical University, Foshan, Guangdong, China
  3. 3 Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Victoria, Australia
  4. 4 School of Optometry, The Hong Kong Polytechnic University, Hong Kong, China
  5. 5 Research Centre for SHARP Vision, The Hong Kong Polytechnic University, Hong Kong, China
  6. 6 Centre for Eye and Vision Research (CEVR), 17W Hong Kong Science Park, Hong Kong, China
  1. Correspondence to Dr Wei Wang, Department of preventive ophthalmology, Sun Yat-Sen University Zhongshan Ophthalmic Center State Key Laboratory of Ophthalmology, Guangzhou, Guangdong, China; wangwei{at}gzzoc.com; Professor Mingguang He; mingguang.he{at}unimelb.edu.au

Abstract

Aims To quantify the profiles of choroidal vascularity index (CVI) using fully artificial intelligence (AI)-based algorithm applied to swept-source optical coherence tomography (SS-OCT) images and evaluate the determinants of CVI in a population-based study.

Methods This cross-sectional study included adults aged ≥35 years residing in the Yuexiu District of Guangzhou, China, a follow-up population-based study. All participants (n=646) underwent comprehensive ophthalmic examinations, including SS-OCT for quantifying choroidal parameters. The CVI and subfoveal choroidal thickness (SFCT) were measured by a novel AI-based system.

Results A total of 556 participants were included, with a mean age of 56.4±9.9 years and 44.96% women. The average CVI and SFCT of the overall population were 69.7% (95% CI 69.2 to 70.3) and 263.0 µm (95% CI 257.2 to 268.8), respectively. After adjusting for other factors, older age and longer AL were significantly associated with a lower CVI. The CVI decreased by –0.13% (–0.19 to –0.06, p<0.001) with each 1-year increase in age, –2.10% (–3.29 to –0.92, p=0.001) with each 1 mm increase in AL. Furthermore, significantly positive correlation between CVI and SFCT has been observed, with coefficient of 0.059 (0.052 to 0.065, p<0.001).

Conclusion Using new AI-based choroidal segmentation software, we provided a fast, reliable and objective CVI profile for large-scale samples. Older age and longer AL were independent correlates of choroidal thinning and CVI decline. These factors should be considered when interpreting SS-OCT-based choroidal measurements.

  • Choroid
  • Imaging
  • Epidemiology
  • Public health
  • Anatomy

Data availability statement

All data relevant to the study are included in the article or uploaded as supplementary information.

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Data availability statement

All data relevant to the study are included in the article or uploaded as supplementary information.

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Footnotes

  • WW and MH contributed equally.

  • MX and CL contributed equally.

  • Contributors MX, WW and MH had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: MH. Acquisition, analysis, or interpretation of data: All authors. Drafting of the manuscript: MX, WW, MH. Critical revision of the manuscript for important intellectual content: All authors. Statistical analysis: WW. Obtained funding: MH. Administrative, technical or material support: MH, JZ. Study supervision: JZ, MH. MH is guarantor.

  • Funding This research was supported in part by a grant from the Guangdong Basic and Applied Basic Research Foundation (2019B1515120011), Fundamental Research Funds of the State Key Laboratory of 0phthalmology (3030901010058) and Natural Science Foundation of Guangdong Province (2023A1515011475).

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.