人工智能驱动的眼内透镜功率计算在极端轴近视的情况下
Yudai Suzuki1,2, Koju Kamoi3, Kengo Uramoto1
1Department of Ophthalmology & Visual Science Graduate school of Medical and Dental Sciences , Institute of Science Tokyo , Tokyo, Japan.
Scientific reports
|October 22, 2025
概括
精确的眼内透镜 (IOL) 功率计算对于极端近视的AI公式如凯恩和希尔-RBF得到了改进. 这些先进的方法比传统配方提供了更好的折射精度,增强了白内障手术后的视觉结果.
科学领域:
- 眼科医生 眼科 眼科
- 生物医学工程 生物医学工程
- 人工智能在医学中的应用
背景情况:
- 准确的眼内镜 (IOL) 功率计算对于成功的白内障手术至关重要.
- 传统配方在极端轴近视 (轴长≥30.0毫米) 的患者中经常显示不准确.
- 这就需要探索先进的计算方法,以便在这个具有挑战性的患者群体中改善折射结果.
研究的目的:
- 追溯评估和比较两个AI驱动的IOL公式 (Hill-RBF,Kane) 与巴雷特通用II和传统SRK/T公式的准确性.
- 为了评估这些公式在极端轴近视的眼睛中的折射预测性.
- 为了确定人工智能驱动的配方是否在这个特定的患者队列中提供更高的准确性.
主要方法:
- 追溯分析了51名患者80只眼睛的数据,这些患者的轴长≥30.0毫米.
- 使用Hill-RBF,Kane,Barrett Universal II和SRK/T公式计算的手术后折射误差的比较.
- 使用平均误差 (ME),平均绝对误差 (MAE) 和中位数绝对误差 (MedAE) 进行准确性评估,并进行统计分析,包括Wilcoxon签名等级和奇平方测试.
主要成果:
- 与SRK/T (P <0.05) 相比,凯恩和希尔-RBF公式显示了明显较低的MAE (0.51 D和0.52 D).
- 巴雷特环球II显示MAE为0.66 D,与SRK/T没有显著差异.
- 在轴长≥32.0毫米的眼睛中,凯恩获得了最低的MAE (0.44 D) 和MedAE (0.40 D).
- 与SRK/T (42.5%) 相比,Kane和Hill-RBF导致的折射误差>±1.0 D (7.5%) 的眼睛较少.
结论:
- 人工智能驱动的IOL配方,特别是Kane和Hill-RBF,在极端轴近视患者中显著提高折射精度.
- 这些先进的配方显示出改善术后视觉结果的潜力.
- 临床采用人工智能驱动的配方可能会减少对此种人群后续折射干预的需要.
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