Purpose

To determine the capabilities of a multilayer perceptron (MLP) for calculating the power of an intraocular lens (IOL) to be implanted and in achieving a given postoperative stable refraction.

Setting

Cuban Institute of Ophthalmology, Havana, Cuba.

Design

Retrospective review.

Methods

The study comprised data of patients who had uneventful phacoemulsification cataract surgery with implantation of a biconvex acrylic foldable IOL (type RYCF, model Ocuflex) in the capsular bag over 6 years. Exclusion criteria were previous intraocular or refractive corneal surgery, any corneal disease, pathological or complicated cataracts, intraoperative complications, preoperative astigmatism beyond 3.0 diopters (D), postoperative corrected distance visual acuity worse than 20/40, missing postoperative refractive information, eyes with an axial length (AL) shorter than 19.36 mm, eyes with an AL longer than 27.0 mm, average corneal keratometry (K) power lower than 36.0 D or higher than 50.9 D, and refractive surprises greater than ±3.0 D. The data were used to train an MLP to predict the value of the IOL power required for attaining a given postoperative refraction. Using AL, K value, and predicted and real postoperative refraction as input data, the output of the MLP was the IOL power.

Results

The study comprised 15 728 eyes of 15 728 patients. The trained neural networks predicted the value of the implanted IOL with an error less than 0.5 D in more than 95% of patients, even for a case in which a surgeon was not included in the training process.

Conclusions

The accuracy attained by the trained MLP is high, indicating the feasibility of a prospective study leading to a new method of predicting the IOL power in refractive surgery with an error lower than the current prediction methods.

中文翻译：

---

在人工晶状体屈光力计算中使用多层感知器

目的

确定多层感知器（MLP）的能力，以计算要植入的人工晶状体（IOL）的能力并实现给定的术后稳定屈光度。

设置

古巴哈瓦那古巴眼科研究所。

设计

回顾性审查。

方法

该研究包括6年内在双囊性丙烯酸折叠性IOL（RYCF型，Ocuflex型）植入双凸丙烯酸折叠式白内障手术的患者的数据。排除标准为先前的眼内或屈光性角膜手术，任何角膜疾病，病理性或复杂性白内障，术中并发症，术前散光度数超过3.0屈光度（D），术后矫正远视力低于20/40，缺少术后屈光性信息，眼轴长度（AL）短于19.36毫米，眼睛长于27.0毫米，平均角膜角膜曲率（K）屈光度低于36.0 D或高于50.9 D，屈光不正大于±3.0 D. 数据用于训练MLP，以预测获得给定术后屈光度所需的IOL功率值。使用AL，K值以及预测的和实际的术后屈光度作为输入数据，MLP的输出为IOL屈光度。

结果

该研究包括15 728名患者的15 728只眼睛。受过训练的神经网络可以预测植入的IOL的价值，在超过95％的患者中误差小于0.5 D，即使是在培训过程中未包括外科医生的情况下。

结论

训练有素的MLP所获得的准确性很高，这表明前瞻性研究的可行性导致了一种新的方法来预测屈光手术中的IOL功率，其误差低于目前的预测方法。