Stopyra Wiktor, Voytsekhivskyy Oleksiy, Grzybowski Andrzej
MW-Med Eye Centre, 31-416 Krakow, Poland.
Department of Medicine, University of Applied Sciences, 34-400 Nowy Targ, Poland.
Life (Basel). 2025 Jan 1;15(1):45. doi: 10.3390/life15010045.
To compare the accuracy of seven artificial intelligence (AI)-based intraocular lens (IOL) power calculation formulas in medium-long Caucasian eyes regarding the root-mean-square absolute error (RMSAE), the median absolute error (MedAE) and the percentage of eyes with a prediction error (PE) within ±0.5 D. Data on Caucasian patients who underwent uneventful phacoemulsification between May 2018 and September 2023 in MW-Med Eye Center, Krakow, Poland and Kyiv Clinical Ophthalmology Hospital Eye Microsurgery Center, Kyiv, Ukraine were reviewed. Inclusion criteria, i.e., complete biometric and refractive data, were applied. Exclusion criteria were as follows: intraoperative or postoperative complications, previous eye surgery or corneal diseases, postoperative BCVA less than 0.8, and corneal astigmatism greater than 2.0 D. Prior to phacoemulsification, IOL power was computed using SRK/T, Holladay1, Haigis, Holladay 2, and Hoffer Q. The refraction was measured three months after cataract surgery. Post-surgery intraocular lens calculations for Hill-RBF 3.0, Kane, PEARL-DGS, Ladas Super Formula AI (LSF AI), Hoffer QST, Karmona, and Nallasamy were performed. RMSAE, MedAE, and the percentage of eyes with a PE within ±0.25 D, ±0.50 D, ±0.75 D, and ±1.00 were counted. Two hundred fourteen eyes with axial lengths ranging from 24.50 mm to 25.97 mm were tested. The Hill-RBF 3.0 formula yielded the lowest RMSAE (0.368), just before Pearl-DGS (0.374) and Hoffer QST (0.378). The lowest MedAE was achieved by Hill-RBF 3.0 (0.200), the second-lowest by LSF AI (0.210), and the third-lowest by Kane (0.228). The highest percentage of eyes with a PE within ±0.50 D was obtained by Hill-RBF 3.0, LSF AI, and Pearl-DGS (86.45%, 85.51%, and 85.05%, respectively). The Hill-RBF 3.0 formula provided highly accurate outcomes in medium-long eyes. All studied AI-based formulas yielded good results in IOL power calculation.
为了比较七种基于人工智能（AI）的人工晶状体（IOL）屈光度计算公式在白种人中长眼轴眼中的准确性，评估均方根绝对误差（RMSAE）、中位数绝对误差（MedAE）以及预测误差（PE）在±0.5 D范围内的眼的百分比。回顾了2018年5月至2023年9月在波兰克拉科夫的MW-Med眼科中心和乌克兰基辅临床眼科医院眼显微手术中心接受顺利白内障超声乳化手术的白种患者的数据。应用了纳入标准，即完整的生物测量和屈光数据。排除标准如下：术中或术后并发症、既往眼部手术或角膜疾病、术后最佳矫正视力（BCVA）低于0.8以及角膜散光大于2.0 D。在白内障超声乳化手术前，使用SRK/T、Holladay1、Haigis、Holladay 2和Hoffer Q计算IOL屈光度。在白内障手术后三个月测量屈光。对Hill-RBF 3.0、Kane、PEARL-DGS、Ladas超级公式AI（LSF AI）、Hoffer QST、Karmona和Nallasamy进行术后人工晶状体计算。计算RMSAE、MedAE以及PE在±0.25 D、±0.50 D、±0.75 D和±1.00 D范围内的眼的百分比。对214只眼轴长度在24.50 mm至25.97 mm之间的眼睛进行了测试。Hill-RBF 3.0公式产生的RMSAE最低（0.368），仅次于Pearl-DGS（0.374）和Hoffer QST（0.378）。Hill-RBF
