目的：评估新一代基于人工智能(artificial intelligence,AI)的人工晶状体(intraocular lens,IOL)计算公式的准确性。方法：本研究为回顾性研究，纳入因白内障行晶状体超声乳化联合IOL植入术的262例患者262眼。在术前，通过IOLMaster700获取角膜曲率、角膜白到白、中央角膜厚度、前房深度、晶状体厚度以及眼轴长度。使用第三代公式(SRK/T、Holladay 1和Hoffer Q)、Barrett UniversalⅡ(BUⅡ)、新一代AI公式(Kane、Pearl-DGS、Hill-RBF 3.0、Hoffer QST和Jin-AI)对术后屈光状态进行计算，并与术后实际的屈光状态进行比较。在将预测误差(prediction error,PE)归零后，分析了各公式的标准差(standard deviation,SD)、绝对误差均值(mean absolute error,MAE)、绝对误差中位数(median absolute error,MedAE)以及PE在±0.25、±0.50、±1.00、±2.00 D范围内的百分比。结果：基于AI的IOL屈光力计算公式的SD、MAE和MedAE的范围分别为0.37 D(Kane和Jin-AI)至0.39 D(Hoffer QST)、0.28 D(Hill-RBF 3.0和Jin-AI)至0.31 D(Hoffer QST)以及0.21 D(Hill-RBF3.0和Jin-AI)至0.24 D(HofferQST)；均低于第三代公式(SD：0.43 D~0.45 D；MAE：0.34 D；MedAE：0.25 D~0.28 D)。在所有公式中，Jin-AI公式预测误差在±0.50 D的比例最高，为84.73%，Kane(84.35%)和BUⅡ(83.97%)公式次之。结论：在IOL屈光力预测上，与传统第三代公式相比，新一代基于AI的公式表现出更高的准确性，可以使更多的患者在术后获得预期的屈光状态。

Objective: To evaluate the accuracy of new generation artificial intelligence (AI)-based intraocular lens (IOL)power calculation formulas. Methods: This retrospective study included a total of 262 eyes from 262 patients with cataract who underwent uneventful phacoemulsification combined with IOL implantation. Keratometry, corneal white-to-white, central corneal thickness, anterior chamber depth, lens thickness, and axial length were measured by the IOL Master 700 before surgery. Predicted refractive errors were calculated by the third-generation formulas (SRK/T, Holladay 1, and Hoffer Q), Barrett UniversalⅡ (BUⅡ), and the newer-generation AI formulas (Kane, Pearl-DGS, Hill-RBF 3.0, Hoffer QST, and Jin-AI), and were compared with the actual postoperative refractive value. After adjusting the prediction error (PE) to zero, the standard deviation (SD), mean absolute error (MAE), median absolute error (MedAE), and the percentage of a PE within the range of ±0.25 diopter (D), ±0.50 D, ±1.00 D, and ±2.00 D were analyzed. Results: The SD, MAE, and MedAE of the AI-based formulas ranged from 0.37 D (Kane and Jin-AI) to 0.39 D (Hoffer QST), 0.28 D (Hill-RBF 3.0 and Jin-AI) to 0.31 D (Hoffer QST), and 0.21 D (Hill-RBF 3.0 and Jin-AI) to 0.24 D (Hoffer QST), respectively. These values were all lower than those of the third-generation formula (SD: 0.43 D to 0.45 D; MAE: 0.34 D; MedAE: 0.25 D to 0.28 D). Among all the formulas, the Jin-AI formula had the highest proportion of a PE within ±0.50 D (84.73%), followed by Kane (84.35%) and BUⅡ (83.97%) formulas. Conclusion: The new AI-based IOL formulas show higher accuracy compared with the traditional third-generation ones in predicting IOL power. thereby enabling more patients to achieve the expected refractive outcomes after surgery

目的：比较六种新一代人工晶状体(intraocular lens,IOL)屈光力计算公式[Barrett Universal Ⅱ(BUⅡ)、Emmetropia Verifying Optical(EVO)、Hill-Radial Basis Function (Hill-RBF)、Kane、Ladas Super Formula(LSF)、T2]和传统公式(Haigis、Hoffer Q、Holladay 1、SRK/T)的准确性。方法：纳入2022年1—6月于温州医科大学附属眼视光医院接受白内障手术患者。收集患者的年龄、性别、眼轴(axial length,AL)、平均角膜曲率(mean keratometry,Kmean)、前房深度、IOL常数和屈光力，术后医学验光结果。对上述10种公式进行准确性分析，包括平均预测误差(mean prediction error,ME)及其标准差、平均绝对预测误差(mean absolute prediction error,MAE)、绝对预测误差中位数(median absolute prediction error,MedAE)、绝对预测误差最大值(maximum absolute prediction error,MaxAE)、预测误差落在±0.25、±0.5、±0.75、±1.00 D范围内的百分比(%±0.25 D、%±0.50 D、%±0.75 D、%±1.00 D)。结果：共纳入506例(506眼)。Kane的MAE最低(0.411)。Hill-RBF的%±0.25 D最高(40.91%)，EVO的%±0.50 D或%±0.75 D最高(分别为69.37%、86.17%)，BUⅡ和Hill-RBF的%±1.00 D最高(均为94.07%)。总体上各种公式间，MAE、%±0.50 D、%±0.75 D、%±1.00 D比较差异存在统计学意义(P<0.05)，但两两比较仅发现%±0.75 D中，EVO(86.17%)、Hill-RBF(85.97%)、Kane(85.57%)与HofferQ(81.42%)比较差异存在统计学意义(均P<0.05)。AL亚组中，长AL组的EVO(0.390)、Hill-RBF(0.388)、T2(0.423)、Kane(0.393)四种公式的MAE与Hoffer Q(0.681)、Holladay 1(0.654)比较差异存在统计学意义(均P<0.05)，EVO(74.47%)的%±0.50 D与Hoffer Q(46.81%)比较差异存在统计学意义(P=0.017)。结论：新一代IOL屈光力计算公式在IOL屈光力计算上均具有较好的准确性，但对于不同的眼轴长度与角膜曲率值的眼球，需要选择适合的计算公式，以进一步提高预测准确性。

Objective: This study aimed to compare the accuracy of six new generation intraocular lenses (IOL) refractive power calculation formulas (Barrett Universal Ⅱ [BU Ⅱ ], Emmetropia Verifying Optical [EVO], Hill-Radial Basis Function [Hill-RBF], Kane, Ladas Super Formula [LSF], T2) and traditional formulas (Haigis, Hoffer Q, Holladay 1, SRK/ T). Methods: The patients who received cataract surgery in the Eye Hospital of Wenzhou Medical University from January 2022 to June 2022 were included in this study. Age, gender, axial length (AL), mean keratometry, anterior chamber depth, IOL constant and power, and postoperative refraction results were collected. The prediction accuracy of these ten IOL power calculation formulas was analyzed, including mean prediction error (ME) and its standard deviation, mean absolute prediction error (MAE), median absolute prediction error (MedAE), maximum absolute prediction error (MaxAE), the percentage of eyes of PE within the range of ±0.25 D, ±0.5 D, ±0.75 D, ±1.0 D (%±0.25 D,%±0.50 D, %±0.75 D, %±1.00 D). Results: 506 eyes of 506 patients were included. Kane has the lowest MAE (0.411).%±0.25 D of Hill-RBF was the highest (40.91%), %±0.50 D or %±0.75 D of EVO was the highest (69.37%, 86.17%), and %±1.00 D of BU Ⅱ and Hill-RBF was the highest (94.07%). There are significant differences in MAE, %±0.50 D, %±0.75 D, and %±1.00 D among all formulas (P<0.05). Still, pairwise comparison only found differences between EVO (86.17%), Hill-RBF (85.97%), Kane (85.57%), and Hoffer Q (81.42%) in %±0.75 D (all P<0.05). In AL subgroup, the MAE of EVO (0.390), Hill-RBF (0.388), T2 (0.423) and Kane (0.393) in long AL group was different from that of Hoffer Q (0.681) and Holladay 1 (0.654) (all P<0.05), the difference of %±0.50D of EVO (74.47%) compared with Hoffer Q (46.81%) (P=0.017). Conclusion: The new generation of IOL power calculation formulas have good accuracy in IOL power prediction, but for eyes with different axial lengths and keratometry, it is necessary to optimize the selection of formulas to improve the prediction accuracy further.

Ⅱ期人工晶状体(intraocular lens,IOL)植入常用于矫正先天性白内障摘除术后无晶状体眼状态。IOL屈光力计算是影响儿童Ⅱ期IOL植入术后视功能发育和改善的关键因素之一。现有IOL屈光力计算公式是基于成人有晶状体眼的数据研发，能准确预测成人眼IOL植入的屈光力，但是对儿童Ⅱ期IOL植入的屈光力预测准确性欠佳，主要原因包括：1)儿童II期植入术前为无晶状体眼，缺乏部分公式定义中的有晶状体眼的前房深度(是指从角膜前表面中央顶点到晶状体前表面的距离)和晶状体厚度。2)公式根据囊袋内植入IOL预测屈光力，但儿童Ⅱ期IOL睫状沟植入术在临床上应用更为广泛。当IOL植入睫状沟时有效晶状体位置发生前移，可能引起屈光预测误差。3)成人眼的发育已完成，目标屈光度多为正视或近视眼(-3.00 ~ +1.00 D)，但是儿童眼仍在发育，需针对其特性测算合适的远视目标屈光度(+0.50 ~ +12.00 D)以适应眼球发育引起的屈光变化。为使Ⅱ期IOL植入患儿达到术前预设的目标屈光度，对现有公式进行选择与优化至关重要。

Secondary intraocular lens (IOL) implantation is a common treatment for pediatric aphakia. The accurate prediction of IOL power calculation plays a pivotal role in the postoperative development and improvement of visual function for pediatric secondary IOL implantation. Current IOL power calculation formulas were developed based on data from adult phakic eyes and displayed good performance in adult population. However, the formulas showed poor performance in pediatric aphakic population due to the following reasons: 1) In these pediatric aphakic patients, the unavailability of phakic anterior chamber depth (the distance from corneal epithelium to the anterior surface of the lens) and lens thickness (LT) greatly limits the application of some IOL power calculation formulas. 2) IOL power calculation formulas predict the effective lens position on the basis of in-the-bag IOL implantation, whereas sulcus implantation is more widely used in pediatric secondary implantation. Effective lens position in capsular placement is more posterior to ciliary sulcus IOL placement. When applying the initial IOL power calculated for capsular implantation to sulcus implantation, it can lead to refractive errors. 3) Adult eyes have completed their development, with target refractions often being emmetropic or myopic (-3.00 ~ +1.00 D), while pediatric eyes are still developing, necessitating the calculation of an appropriate hyperopic (+0.50 ~ +12.00 D) target refraction to accommodate refractive changes due to ocular growth.To achieve the predetermined target refractive outcomes, the selection and optimization of IOL power calculation formulas is critically important for pediatric secondary IOL implantation.

      精准的屈光规划——人工晶状体屈光力计算，是屈光性白内障手术的重要前提。人工晶状体计算公式使用患者术前的眼部生物学参数如眼轴长度、角膜曲率、前房深度、晶状体厚度等指标来预测患者在白内障术后的屈光状态。人工晶状体屈光力计算公式自1967年出现以来，不断发展革新，准确性得到了极大的提升。封面展示了几种基于不同原理而构建的计算公式：回归公式(以SRK公式为代表)、基于模型眼的会聚公式(以Holladay 1等为代表)、射线追踪公式(以Olsen为代表)与人工智能公式(以RBF为代表)。目前对于普通白内障患者，现有公式能够获得良好的预测准确性。然而，对于临床上很多特殊的患者(如眼球解剖参数异常、既往有其他眼病或眼部手术史)，如何准确预测术后的屈光状态仍存在较大的挑战。路途漫漫，学者们为提升人工晶状体屈光力计算准确性的努力却从未止步，力求为患者提供最佳的白内障手术效果。

      精准的屈光规划——人工晶状体屈光力计算，是屈光性白内障手术的重要前提。人工晶状体计算公式使用患者术前的眼部生物学参数如眼轴长度、角膜曲率、前房深度、晶状体厚度等指标来预测患者在白内障术后的屈光状态。人工晶状体屈光力计算公式自1967年出现以来，不断发展革新，准确性得到了极大的提升。封面展示了几种基于不同原理而构建的计算公式：回归公式(以SRK公式为代表)、基于模型眼的会聚公式(以Holladay 1等为代表)、射线追踪公式(以Olsen为代表)与人工智能公式(以RBF为代表)。目前对于普通白内障患者，现有公式能够获得良好的预测准确性。然而，对于临床上很多特殊的患者(如眼球解剖参数异常、既往有其他眼病或眼部手术史)，如何准确预测术后的屈光状态仍存在较大的挑战。路途漫漫，学者们为提升人工晶状体屈光力计算准确性的努力却从未止步，力求为患者提供最佳的白内障手术效果。

随着功能性人工晶状体的推广应用，白内障患者的屈光预测准确性日益受到重视。尽管人工晶状体屈光力计算公式在近年来不断发展革新，但解剖参数异常或既往有其他眼病、眼部手术史的白内障患者屈光预测仍存在挑战。根据生物学参数特点与病史选择适合的人工晶状体屈光力计算公式是准确进行白内障手术屈光预测的重要保障。

With the widespread application of functional intraocular lense (IOL), the accuracy of refractive prediction in cataract patients is increasingly important. Although IOL power calculation formulas have been innovated continuously in recent years, there are still challenges in predicting refractive powerin cataract patients with abnormal anatomical parameters, ocular comorbidities, or a history of ocular surgery. Based on the the characteristics of biological parameters and medical history to selcet appropriate IOL power formula, it is an important guarantee for accurate refractive prediction in cataract patients.