- 1. Department of Ophthalmology, Jiangmen Central Hospital, Affiliated to Guangdong Medical University, Jiangmen 529000, China;
- 2. Department of Ophthalmology, People’s Hospital of Jiangmen, Jiangmen 529000, China;
Peng Chao,
Email: ppy1125@126.com
Choroidal vascularity index （CVI）, as a new biological parameter to quantitatively evaluate the state of choroidal vessels, has shown great potential in the diagnosis and treatment of ophthalmic diseases in recent years. CVI primarily calculated from images obtained via optical coherence tomography (OCT) and OCT angiography, demonstrates enhanced accuracy, stability, and clinical value with the advancement of three-dimensional imaging and artificial intelligence technologies. Compared with two-dimensional CVI, three-dimensional CVI comprehensively reflects the spatial distribution and structural changes of choroidal blood vessels by constructing three-dimensional choroidal models through ultra-widefield scanning. In various ophthalmic diseases, including age-related macular degeneration, central serous chorioretinopathy, diabetic retinopathy, and pathological myopia, CVI exhibits characteristic changes that not only contribute to understanding disease pathogenesis but also serve as indicators for early screening, individualized treatment, and efficacy monitoring. The application of artificial intelligence and deep learning technology improves the efficiency of automated CVI analysis, while integration with multimodal imaging further optimizes disease evaluation. Future efforts should focus on establishing standardized measurement protocols and quality control systems to promote its broader application and development in ophthalmology.
Copyright ? the editorial department of Chinese Journal of Ocular Fundus Diseases of West China Medical Publisher. All rights reserved
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- 1. Betzler BK, Ding J, Wei X, et al. Choroidal vascularity index: a step towards software as a medical device[J]. Br J Ophthalmol, 2022, 106(2): 149-155. DOI: 10.1136/bjophthalmol-2021-318782.
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- 3. Tan KA, Gupta P, Agarwal A, et al. State of science: choroidal thickness and systemic health[J]. Surv Ophthalmol, 2016, 61(5): 566-581. DOI: 10.1016/j.survophthal.2016.02.007.
- 4. Di Pippo M, Santia C, Rullo D, et al. The choroidal vascularity index versus optical coherence tomography angiography in the evaluation of the choroid with a focus on age-related macular degeneration[J]. Tomography, 2023, 9(4): 1456-1470. DOI: 10.3390/tomography9040116.
- 5. 劉然, 晏穎, 陳曉. 脈絡膜血管指數的臨床運用研究進展[J]. 眼科新進展, 2020, 40(07): 696-700. DOI: 10.13389/i.cnki.rao.2020.0159.Liu R, Yan Y, Chen X. Clinical application and research progress of choroidal vascular index[J]. Rec Adv Ophthalmol, 2020, 40(07): 696-700. DOI: 10.13389/i.cnki.rao.2020.0159.
- 6. Agrawal R, Gupta P, Tan KA, et al. Choroidal vascularity index as a measure of vascular status of the choroid: measurements in healthy eyes from a population-based study[J/OL]. Sci Rep, 2016, 6: 21090[2016-02-12]. https://pubmed.ncbi.nlm.nih.gov/26868048/. DOI: 10.1038/srep21090.
- 7. Agrawal R, Ding J, Sen P, et al. Exploring choroidal angioarchitecture in health and disease using choroidal vascularity index[J/OL]. Prog Retin Eye Res, 2020, 77: 100829[2020-01-10]. https://pubmed.ncbi.nlm.nih.gov/31927136/. DOI: 10.1016/j.preteyeres.2020.100829.
- 8. Iovino C, Pellegrini M, Bernabei F, et al. Choroidal vasculature index: an in-depth analysis of this novel optical coherence tomography parameter[J/OL]. J Clin Med, 2020, 9(2): 595[2020-01-21]. https://pubmed.ncbi.nlm.nih.gov/32098215/. DOI: 10.3390/jcm9020595.
- 9. Sadeghi E, Valsecchi N, Ibrahim MN, et al. Three-dimensional choroidal vessels assessment in age-related macular degeneration[J]. Invest Ophthalmol Vis Sci, 2024, 65(13): 39-39. DOI: 10.1167/iovs.65.13.39.
- 10. Masood S, Fang R, Li P, et al. Automatic choroid layer segmentation from optical coherence tomography images using deep learning[J/OL]. Sci Rep, 2019, 9 (1): 3058[2019-12-13]. https://pubmed.ncbi.nlm.nih.gov/30816296/. DOI: 10.1038/s41598-019-39795-x.
- 11. Xuan M, Wang W, Shi D, et al. A deep learning–based fully automated program for choroidal structure analysis within the region of interest in myopic children[J]. Transl Vis Sci Technol, 2023, 12(3): 22-22. DOI: 10.1167/tvst.12.3.22.
- 12. 董雪雯, 劉春夢, 趙丹丹, 等. 糖尿病患者脈絡膜厚度及血管指數變化的研究進展[J]. 中國中醫眼科雜志, 2022, 32(7): 585-588. DOI: 10.13444/j.cnki.zgzyykzz.2022.07.018.Dong XW, Liu CM, Zhao DD, et al. Advances in the study of choroidal thickness and choroidal vascularity index in diabetic patients[J]. Chinese Journal of Chinese Ophthalmology, 2022, 32(7): 585-588. DOI: 10.13444/j.cnki.zgzyykzz.2022.07.018.
- 13. Valsecchi N, Sadeghi E, Davis E, et al. Assessment of choroidal vessels in healthy eyes using 3-dimensional vascular maps and a semi-automated deep learning approach[J/OL]. Sci Rep, 2025, 15(1): 714[2025-01-03]. https://pubmed.ncbi.nlm.nih.gov/39753934/. DOI: 10.1038/s41598-025-85189-7.
- 14. Tan KA, Laude A, Yip V, et al. Choroidal vascularity index - a novel optical coherence tomography parameter for disease monitoring in diabetes mellitus?[J/OL]. Acta Ophthalmol, 2016, 94(7): e612-e616[2016-05-06]. https://pubmed.ncbi.nlm.nih.gov/27151819/. DOI: 10.1111/aos.13044.
- 15. Gupta P, Saw SM, Cheung CY, et al. Choroidal thickness and high myopia: a case–control study of young Chinese men in Singapore[J/OL]. Acta Ophthalmol, 2015, 93(7): e585-e592[2014-12-21]. https://pubmed.ncbi.nlm.nih.gov/25529388/. DOI: 10.1111/aos.12631.
- 16. Rasheed MA, Sahoo NK, Goud A, et al. Qualitative comparison of choroidal vascularity measurement algorithms[J]. Indian J Ophthalmol, 2018, 66(12): 1785-1789. DOI: 10.4103/ijo.IJO_663_18.
- 17. Wang L, Wang W, Zhou Z, et al. Quantitative assessment of choroidal thickness and choroidal vascular features in healthy eyes based on image binarization of EDI-OCT: a single-center cross-sectional analysis in Chinese population[J/OL]. J Clin Med, 2023, 12(5): 1911[2023-02-28]. https://pubmed.ncbi.nlm.nih.gov/36902698/. DOI: 10.3390/jcm12051911.
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