Anatomical Determinants of Postoperative In-the-Bag IOL Position: Introducing a Novel Biometric Index

生物识别 索引(排版) 职位(财务) 生物特征数据 计算机科学 医学 人工智能 计算机视觉 眼科 验光服务 业务 万维网 财务
作者
Jianxia Fang,Xinyu Ma,Zhe Xu,Ce Shi,Yaqi Wang,Weijia Yan,Zhichao Hu,Chujun Liu,Huiling Zhao,Gangyong Jia,Wen Xu
出处
期刊:American Journal of Ophthalmology [Elsevier BV]
标识
DOI:10.1016/j.ajo.2025.08.011
摘要

To investigate whether a novel preoperative biometric index that integrates lens geometry and the relative position of the capsular bag can predict the postoperative in-the-bag intraocular lens (IOL) position proportion coefficient and, subsequently, the final IOL position. Retrospective study. This study included 322 eyes of 322 patients undergoing uneventful cataract surgery with in-the-bag implantation of an aspheric Tecnis IOL (Johnson & Johnson Vision, Santa Ana, CA). Preoperative biometric assessments were performed in cataract surgery patients using swept-source anterior segment optical coherence tomography, encompassing conventional parameters (e.g., anterior chamber depth, lens thickness [LT], crystalline lens rise [CLR]) and composite indices such as the CLR to LT ratio (CLR/LT). Axial length (AL) was measured using the IOLMaster 700. All parameters were analyzed for correlation with the in-the-bag IOL position proportion coefficient. The most predictive variables were incorporated into multiple linear and machine learning regression models to estimate IOL position proportion coefficient. The predicted IOL position proportion coefficient was then used to calculate IOL position, and the accuracy was compared with conventional vergence formulas. Correlation between preoperative biometric parameters and the postoperative in-the-bag IOL position proportion coefficient; accuracy of IOL position estimation based on the predicted IOL position proportion coefficient compared with actual postoperative IOL positions and conventional vergence-based IOL power formulas across AL subgroups. CLR/LT demonstrated a strong association with postoperative IOL position proportion coefficient. A support vector machine model incorporating CLR/LT significantly improved the accuracy of IOL position proportion coefficient prediction. Compared with standard formulas, calculating IOL position via predicted IOL position proportion coefficient markedly enhanced prediction precision, particularly in eyes with atypical AL. CLR/LT is a clinically meaningful preoperative index for predicting in-the-bag IOL position. Its use enables more individualized IOL power selection and improved refractive accuracy, especially in eyes with unusual biometric profiles.

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