The Zhu-Lu formula: a machine learning-based intraocular lens power calculation formula for highly myopic eyes

Eye and Vision

Research

Jinhai Huang¹  Yunqian Yao²  Yi Lu²  Xiangjia Zhu²  Dongling Guo²  Ling Wei²  Wenwen He²  Jiao Qi²  Xu Chen³  Yunxiao Song⁴ 

[1] Eye Institute and Department of Ophthalmology, Eye & ENT Hospital, Fudan University, 200031, Shanghai, China;Eye Hospital of Wenzhou Medical University, Wenzhou, China;Eye Institute and Department of Ophthalmology, Eye & ENT Hospital, Fudan University, 200031, Shanghai, China;NHC Key Laboratory of Myopia, Fudan University, Shanghai, China;Key Laboratory of Myopia, Chinese Academy of Medical Science, Shanghai, China;Shanghai Key Laboratory of Visual Impairment and Restoration, Shanghai, China;Shanghai Aier Eye Hospital, Shanghai, China;University of Illinois at Urbana-Champaign, Illinois, USA;

关键词: Machine learning;    IOL power calculation;    High myopia;    Prediction error;   

DOI  :  10.1186/s40662-023-00342-5

 received in 2022-11-14, accepted in 2023-04-12,  发布年份 2023

来源: Springer

【 摘 要 】

BackgroundTo develop a novel machine learning-based intraocular lens (IOL) power calculation formula for highly myopic eyes.MethodsA total of 1828 eyes (from 1828 highly myopic patients) undergoing cataract surgery in our hospital were used as the internal dataset, and 151 eyes from 151 highly myopic patients from two other hospitals were used as external test dataset. The Zhu-Lu formula was developed based on the eXtreme Gradient Boosting and the support vector regression algorithms. Its accuracy was compared in the internal and external test datasets with the Barrett Universal II (BUII), Emmetropia Verifying Optical (EVO) 2.0, Kane, Pearl-DGS and Radial Basis Function (RBF) 3.0 formulas.ResultsIn the internal test dataset, the Zhu-Lu, RBF 3.0 and BUII ranked top three from low to high taking into account standard deviations (SDs) of prediction errors (PEs). The Zhu-Lu and RBF 3.0 showed significantly lower median absolute errors (MedAEs) than the other formulas (all P < 0.05). In the external test dataset, the Zhu-Lu, Kane and EVO 2.0 ranked top three from low to high considering SDs of PEs. The Zhu-Lu formula showed a comparable MedAE with BUII and EVO 2.0 but significantly lower than Kane, Pearl-DGS and RBF 3.0 (all P < 0.05). The Zhu-Lu formula ranked first regarding the percentages of eyes within ± 0.50 D of the PE in both test datasets (internal: 80.61%; external: 72.85%). In the axial length subgroup analysis, the PE of the Zhu-Lu stayed stably close to zero in all subgroups.ConclusionsThe novel IOL power calculation formula for highly myopic eyes demonstrated improved and stable predictive accuracy compared with other artificial intelligence-based formulas.

【 授权许可】

CC BY   
© The Author(s) 2023

【 图 表 】

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