Moshirfar Majid, Sperry Ronald A, Altaf Amal W, Stoakes Isabella M, Hoopes Phillip C
Hoopes Vision Research Center, Hoopes Vision, 11820 S. State St. #200, Draper, UT, 84020, USA.
John A. Moran Eye Center, University of Utah School of Medicine, Salt Lake City, UT, USA.
Ophthalmol Ther. 2024 Jun;13(6):1703-1722. doi: 10.1007/s40123-024-00946-7. Epub 2024 Apr 25.
This study aims to evaluate the accuracy of 12 different intraocular lens (IOL) power calculation formulas for post-radial keratotomy (RK) eyes. The investigation utilizes recent advances in topography/tomography devices and artificial intelligence (AI)-based calculators, comparing the results to those reported in current literature to assess the efficacy and predictability of IOL calculations for this patient group.
In this retrospective study, 37 eyes from 24 individuals with a history of RK who underwent cataract surgery at Hoopes Vision Center were analyzed. Biometry and corneal topography measurements were taken preoperatively. Subjective refraction was obtained 6 months postoperatively. Twelve different IOL power calculations were used, including the American Society of Cataract and Refractive Surgery (ASCRS) post-RK online formula, and the Barrett True K, Double K modified-Holladay 1, Haigis-L, Panacea, Camellin-Calossi, Emmetropia Verifying Optical (EVO) 2.0, Kane, and Prediction Enhanced by Artificial Intelligence and output Linearization-Debellemanière, Gatinel, and Saad (PEARL-DGS) formulas. Outcome measures included median absolute error (MedAE), mean absolute error (MAE), arithmetic mean error (AME), and percentage of eyes achieving refractive prediction errors (RPE) within ± 0.50 D, ± 0.75 D, and ± 1 D for each formula. A search of the literature was also performed by two independent reviewers based on relevant formulas.
Overall, the best performing IOL power calculations were the Camellin-Calossi (MedAE = 0.515 D), the ASCRS average (MedAE = 0.535 D), and the EVO (MedAE = 0.545 D) and Kane (MedAE = 0.555 D) AI-based formulas. The EVO and Kane formulas along with the ASCRS calculation performed similarly, with 48.65% of eyes scoring within ± 0.50 D of the target range, while the Equivalent Keratometry Reading (EKR) 65 Holladay formula achieved the greatest percentage of eyes scoring within ± 0.25 D of the target range (35.14%). Additionally, the EVO 2.0 formula achieved 64.86% of eyes scoring within the ± 0.75 D RPE category, while the Kane formula achieved 75.68% of eyes scoring within the ± 1 D RPE category. There was no significant difference in MAE between the established and newer generation formulas (P > 0.05). The Panacea formula consistently underperformed when compared to the ASCRS average and other high-performing formulas (P < 0.05).
This study demonstrates the potential of AI-based IOL calculation formulas, such as EVO 2.0 and Kane, for improving the accuracy of IOL power calculation in post-RK eyes undergoing cataract surgery. Established calculations, such as the ASCRS and Barrett True K formula, remain effective options, while under-utilized formulas, like the EKR65 and Camellin-Calossi formulas, show promise, emphasizing the need for further research and larger studies to validate and enhance IOL power calculation for this patient group.
本研究旨在评估12种不同的人工晶状体(IOL)屈光力计算公式在放射状角膜切开术(RK)后眼睛中的准确性。该调查利用了地形学/断层扫描设备和基于人工智能(AI)的计算器的最新进展,将结果与当前文献报道的结果进行比较,以评估该患者群体IOL计算的有效性和可预测性。
在这项回顾性研究中,分析了来自24名有RK病史且在胡普斯视力中心接受白内障手术的患者的37只眼睛。术前进行了生物测量和角膜地形图测量。术后6个月获得主观验光结果。使用了12种不同的IOL屈光力计算方法,包括美国白内障与屈光手术学会(ASCRS)RK术后在线公式,以及巴雷特真K、双K改良霍拉迪1、海吉斯-L、万能、卡梅林-卡洛西、正视验证光学(EVO)2.0、凯恩,以及人工智能增强预测和输出线性化-德贝莱马尼耶、加蒂内尔和萨德(PEARL-DGS)公式。结果指标包括中位数绝对误差(MedAE)、平均绝对误差(MAE)、算术平均误差(AME),以及每种公式在±0.50 D、±0.75 D和±1 D范围内实现屈光预测误差(RPE)的眼睛百分比。两名独立评审员还根据相关公式对文献进行了检索。
总体而言,表现最佳的IOL屈光力计算方法是卡梅林-卡洛西(MedAE = 0.515 D)、ASCRS平均值(MedAE = 0.535 D),以及基于EVO(MedAE = 0.545 D)和凯恩(MedAE = 0.555 D)的AI公式。EVO和凯恩公式以及ASCRS计算的表现相似,48.65%的眼睛在目标范围的±0.50 D内得分,而等效角膜曲率读数(EKR)65霍拉迪公式在目标范围的±0.25 D内得分的眼睛百分比最高(35.14%)。此外,EVO 2.0公式在±0.75 D RPE类别中有64.86%的眼睛得分,而凯恩公式在±1 D RPE类别中有75.68%的眼睛得分。既定公式和新一代公式之间的MAE没有显著差异(P > 0.05)。与ASCRS平均值和其他高性能公式相比,万能公式始终表现不佳(P < 0.05)。
本研究证明了基于AI的IOL计算公式(如EVO 2.0和凯恩)在提高接受白内障手术的RK术后眼睛IOL屈光力计算准确性方面的潜力。既定的计算方法(如ASCRS和巴雷特真K公式)仍然是有效的选择,而未充分利用的公式(如EKR65和卡梅林-卡洛西公式)显示出前景,强调需要进一步研究和更大规模的研究来验证和改进该患者群体的IOL屈光力计算。