The Effect of Three-Dimensional Ocular Shape on Longitudinal Biometric Changes: A Six-Year Follow-Up Study.

IF 2.7 3区医学 Q2 OPHTHALMOLOGY

Translational Vision Science & Technology Pub Date : 2026-08-03 DOI:10.1167/tvst.15.8.18

Feng Jiang, Huawang Wu, Ou Xiao, Xinxing Guo, Mingguang He, Zhixi Li

{"title":"The Effect of Three-Dimensional Ocular Shape on Longitudinal Biometric Changes: A Six-Year Follow-Up Study.","authors":"Feng Jiang, Huawang Wu, Ou Xiao, Xinxing Guo, Mingguang He, Zhixi Li","doi":"10.1167/tvst.15.8.18","DOIUrl":null,"url":null,"abstract":"Purpose: To investigate progression rates of ocular biometry in various ocular shapes using three-dimensional magnetic resonance imaging (3D MRI).Methods: Highly myopic participants (spherical power ≤ -6 diopters [D]) of the prospective cohort study underwent ocular biometry, cycloplegic refraction and MRI examinations. Ocular shapes were classified using 3D MRI as spheroidal, ellipsoidal, conical, nasally distorted, temporally distorted, or barrel shaped. Spheroidal and ellipsoidal shapes were further categorized into non-deformed forms and other shapes were deformed. Mixed-effects model was used to assess the association between the change rate of spherical equivalent (SE) and ocular biometry and ocular shape. Machine learning models were developed to predict annual AL and SE progression rates.Results: A total of 150 eyes including 89 non-deformed eyes and 61 deformed eyes from 75 Participants (36 females [48.00%]) were followed up for 6.70 ± 2.66 years, with a mean age of 34.30 ± 13.43 years. Mean SE and axial length (AL) were -11.49 ± 3.76 D and 28.23 ± 1.72 mm. Eyes showed progressive myopic shift (-0.36 D/y; 95% confidence interval [CI], -0.45 to -0.26) and axial elongation (0.07 mm/y; 95% CI, 0.06-0.08). Deformed ocular (61 eyes) exhibited faster SE progression (β = -0.20, P < 0.001) and AL elongation (β = 0.05, P < 0.001) compared with non-deformed shapes (89 eyes). For annual AL progression, the random forest model achieved the lowest root mean square error (RMSE) (0.067; 95% CI, 0.048-0.087). For annual SE progression, the XGBoost model outperformed other algorithms with the lowest RMSE (0.644; 95% CI, 0.192-1.248).Conclusions: Ocular shapes continue to progress in SE and AL, with deformed ocular demonstrating higher rates of SE and AL than non-deformed shapes.Translational relevance: A 3D MRI-based ocular shape identifies highly myopic eyes at increased risk of rapid biometric progression.","PeriodicalId":23322,"journal":{"name":"Translational Vision Science & Technology","volume":"15 8","pages":"18"},"PeriodicalIF":2.7000,"publicationDate":"2026-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13505797/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Translational Vision Science & Technology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1167/tvst.15.8.18","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"OPHTHALMOLOGY","Score":null,"Total":0}

引用次数: 0

Abstract

Purpose: To investigate progression rates of ocular biometry in various ocular shapes using three-dimensional magnetic resonance imaging (3D MRI).

Methods: Highly myopic participants (spherical power ≤ -6 diopters [D]) of the prospective cohort study underwent ocular biometry, cycloplegic refraction and MRI examinations. Ocular shapes were classified using 3D MRI as spheroidal, ellipsoidal, conical, nasally distorted, temporally distorted, or barrel shaped. Spheroidal and ellipsoidal shapes were further categorized into non-deformed forms and other shapes were deformed. Mixed-effects model was used to assess the association between the change rate of spherical equivalent (SE) and ocular biometry and ocular shape. Machine learning models were developed to predict annual AL and SE progression rates.

Results: A total of 150 eyes including 89 non-deformed eyes and 61 deformed eyes from 75 Participants (36 females [48.00%]) were followed up for 6.70 ± 2.66 years, with a mean age of 34.30 ± 13.43 years. Mean SE and axial length (AL) were -11.49 ± 3.76 D and 28.23 ± 1.72 mm. Eyes showed progressive myopic shift (-0.36 D/y; 95% confidence interval [CI], -0.45 to -0.26) and axial elongation (0.07 mm/y; 95% CI, 0.06-0.08). Deformed ocular (61 eyes) exhibited faster SE progression (β = -0.20, P < 0.001) and AL elongation (β = 0.05, P < 0.001) compared with non-deformed shapes (89 eyes). For annual AL progression, the random forest model achieved the lowest root mean square error (RMSE) (0.067; 95% CI, 0.048-0.087). For annual SE progression, the XGBoost model outperformed other algorithms with the lowest RMSE (0.644; 95% CI, 0.192-1.248).

Conclusions: Ocular shapes continue to progress in SE and AL, with deformed ocular demonstrating higher rates of SE and AL than non-deformed shapes.

Translational relevance: A 3D MRI-based ocular shape identifies highly myopic eyes at increased risk of rapid biometric progression.

查看原文本刊更多论文

三维眼形对纵向生物特征变化的影响：一项为期六年的随访研究。

目的：利用三维磁共振成像（3D MRI）研究不同眼形的眼生物特征进展率。方法：前瞻性队列研究的高度近视受试者（球面屈光度≤-6屈光度[D]）行眼部生物测量、睫状体麻痹屈光和MRI检查。三维MRI将眼形分为球型、椭球型、圆锥形、鼻型、颞型和桶形。球体和椭球形进一步被分类为非变形形状，其他形状被变形。采用混合效应模型评价球当量（SE）变化率与眼生物特征和眼形态的关系。开发了机器学习模型来预测年度AL和SE进展率。结果：75例患者共150只眼，其中女性36例（48.00%），无畸形眼89只，畸形眼61只，随访6.70±2.66年，平均年龄34.30±13.43岁。平均SE和AL分别为-11.49±3.76 D和28.23±1.72 mm。眼睛表现为进行性近视偏移（-0.36 D/y； 95%可信区间[CI]， -0.45至-0.26）和轴向伸长（0.07 mm/y; 95% CI, 0.06-0.08）。变形眼（61眼）与未变形眼（89眼）相比，SE进展（β = -0.20, P < 0.001）和AL延长（β = 0.05, P < 0.001）更快。对于年度人工智能进展，随机森林模型实现了最低的均方根误差（RMSE）（0.067; 95% CI, 0.048-0.087）。对于年度SE进展，XGBoost模型以最低的RMSE优于其他算法（0.644;95% CI, 0.192-1.248）。结论：眼形态在SE和AL中持续发展，变形的眼比未变形的眼表现出更高的SE和AL发生率。翻译相关性：基于3D mri的眼形状识别高度近视的眼睛在快速生物特征进展的风险增加。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Translational Vision Science & Technology Engineering-Biomedical Engineering

CiteScore

5.70

自引率

3.30%

发文量

346

审稿时长

25 weeks

期刊介绍： Translational Vision Science & Technology (TVST), an official journal of the Association for Research in Vision and Ophthalmology (ARVO), an international organization whose purpose is to advance research worldwide into understanding the visual system and preventing, treating and curing its disorders, is an online, open access, peer-reviewed journal emphasizing multidisciplinary research that bridges the gap between basic research and clinical care. A highly qualified and diverse group of Associate Editors and Editorial Board Members is led by Editor-in-Chief Marco Zarbin, MD, PhD, FARVO. The journal covers a broad spectrum of work, including but not limited to: Applications of stem cell technology for regenerative medicine, Development of new animal models of human diseases, Tissue bioengineering, Chemical engineering to improve virus-based gene delivery, Nanotechnology for drug delivery, Design and synthesis of artificial extracellular matrices, Development of a true microsurgical operating environment, Refining data analysis algorithms to improve in vivo imaging technology, Results of Phase 1 clinical trials, Reverse translational ("bedside to bench") research. TVST seeks manuscripts from scientists and clinicians with diverse backgrounds ranging from basic chemistry to ophthalmic surgery that will advance or change the way we understand and/or treat vision-threatening diseases. TVST encourages the use of color, multimedia, hyperlinks, program code and other digital enhancements.