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基于OCT的近视指数:对高近视的进展的生物学预测指标
Zheming Zhang1, Zheng Gong2, Wangting Li3,4
1Zhongshan Ophthalmic Center, Sun Yat-sen University, WHO Collaborating Centre for Eye Care and Vision, State Key Laboratory of Ophthalmology, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Sun Yat-Sen University, Guangzhou, China.
The British journal of ophthalmology
|March 11, 2026
概括
一个新的近视指数,来自光学连贯性断层扫描 (OCT) 扫描,更好地通过评估 fundus 变形来预测高近视的进展. 这个索引提供了比单独的轴长更深入的见解.
科学领域:
- 眼科医生 眼科 眼科
- 医疗成像医学成像
- 人工智能的人工智能
背景情况:
- 轴长度 (AL) 的增长导致高近视和眼睛变形,导致无法量化的 fundus 微观结构变化.
- 目前仅依赖AL的方法缺乏对这些变化的全面评估.
研究的目的:
- 提出基于光学连贯性断层扫描 (OCT) 的修改AL,称为近视指数,以量化 fundus 变形.
- 评估近视指数在预测近视进展方面的临床意义.
主要方法:
- 在27539张OCT图像和眼部生物识别数据上训练了一个深度学习模型.
- 将近视指数与测量AL进行比较,以计算差异 (DAL).
- 未来评估了模型的预测能力,使用不同的AL类别的2866张OCT图像.
主要成果:
- 近视指数与测量AL有很强的相关性 (R2=0.804).
- 深度学习模型在短/正常AL (视网膜) 与长AL (胆膜,RPE) 中确定了不同的注意区域.
- DAL与AL增加有显著的相关性 (p=0.038).
结论:
- 近视指数准确地反映了 fundus 微观结构状态,强调胆.
- 近视指数显示了对高近视进展的强有力的预测能力.
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