Refractive Predictability Using the IOLMaster 700 and Artificial Intelligence-Based IOL Power Formulas Compared to Standard Formulas
Refractive Predictability Using the IOLMaster 700 and Artificial Intelligence-Based IOL Power Formulas Compared to Standard Formulas
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DOI：
10.3928/1081597x-20200514-02
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发表时间：
2020-07-01
影响因子：
2.4
通讯作者：
Wu, Mingxing
中科院分区：
文献类型：
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作者：
Cheng, Huanhuan;Kane, Jack X.;Wu, Mingxing
目得：目的：探讨扫频光源光学相干断层扫描（SS-OCT）计算IOL屈光度公式的准确性。无并发症的白内障超声乳化术和IOL植入术入组本回顾性研究。将新发布的基于人工智能的公式（包括Hill-Radial Basis Function（RBF）2.0、Kane和PEARL-DGS）与基于高斯光学的标准公式进行比较。结果：410例（410眼）患者的屈光状态均符合标准，且屈光度的预测值与实际屈光状态的等效球镜值之间存在显著性差异。与使用用户组激光干涉生物测定常数相比，使用优化的SS-OCT生物测定常数可显著降低Barrett、Haigis和Hoffer Q公式的中位绝对误差（MedAE）（P <.05）。总体而言，在恒定优化下，Olsen（0.283屈光度[D]）和Kane（0.286 D）公式的MedAE显著低于RBF 2.0（0.314 D）、Haigis（0.322 D）、SRK/T（0.371 D）、Holladay 1（0.376 D）和Hoffer 0（0.379 D）公式（P <0.05）。预测误差标准差最低的前四个公式是Kane（0.451 DI）、Olsen（0.456 D）、EVO 2.0（0.460 D）和Barrett（0.470 D）。奥尔森（47.1%），巴雷特（45.9%1、Kane 145.4%1和EVO 2.0（45.1%）公式中预测屈光度+/-0.25 D范围内的眼睛比例高于Hoffer Q（35.9%）、SRK/T（35.9%）和Holladay 1（33.4%）公式（P <0.05）。结论：SS-OCT生物测量的持续优化进一步提高了公式的性能。Barrett、EVO 2.0、Kane和Olsen公式可实现最准确的术后屈光预测。
PURPOSE: To investigate the accuracy of intraocutar tens (IOL) power calculation formulas using swept-source optical coherence tomography (SS-OCT).METHODS: Eyes with biometry measurement by IOLMaster 700 (Cart Zeiss Meditec AG). uncomplicated phacoemulsification, and IOL implantation were enrolled in this retrospective study. Newly released artificial intelligence-based formulas including Hill-Radial Basis Function (RBF) 2.0, Kane, and PEARL-DGS were compared with Gaussian optics-based standard formulas. The refraction predicted by each formula was compared with the actual refractive outcome in spherical equivalent.RESULTS: A total of 410 eyes of 410 patients were included in this study. Using optimized constants for SS-OCT biometry led to a significant decrease in median absolute error (MedAE) for Barrett, Haigis, and Hoffer Q formulas compared with using User Group for Laser Interference Biometry constants (P < .05). Overall, Olsen (0.283 diopters [D]) and Kane (0.286 D) formulas had significantly tower MedAEs than RBF 2.0 (0.314 D), Haigis (0.322 D), SRK/T (0.371 D), Holladay 1 (0.376 D), and Hoffer 0 (0.379 D) formulas under constant optimization (P < .05). The first four formulas with the lowest standard deviations of prediction error were Kane (0.451 DI, Olsen (0.456 D), EVO 2.0 (0.460 D), and Barrett (0.470 D). Olsen (47.1%), Barrett (45.9%1, Kane 145.4%1, and EVO 2.0 (45.1%) formulas had greater proportions of eyes within +/- 0.25 D of the predicted refraction than Hoffer Q (35.9%), SRK/T (35.9%), and Holladay 1 (33.4%) formulas (P < .05).CONCLUSIONS: Constant optimization for SS-OCT biometry further improves the performance of formulas. The most accurate prediction of postoperative refraction can be achieved with Barrett, EVO 2.0, Kane, and Olsen formulas.