目的：探索使用注意力机制和Pix2Pix生成对抗网络预测年龄相关性白内障患者术中行飞秒激光弧形角膜切开术后角膜地形图。

方法：回顾性病例系列研究。选取2018-03/2020-03山西省眼科医院年龄相关性白内障患者术中行飞秒激光弧形角膜切开术患者87例105眼。收集患者术前及术后角膜地形图210张分为训练集(180张)、测试集(30张)用于模型训练和测试。采用峰值信噪比(PSNR)、结构相似性(SSIM)、Alpins散光矢量分析，比较不同注意力机制下术后角膜地形图预测结果的准确性。

结果：基于注意力机制和Pix2Pix网络可以预测术后角膜地形图，其中基于Self-Attention注意力机制的模型预测效果最好，PSNR和SSIM达到了16.048、0.7661。真实的和生成的角膜地形图在3mm和5mm环上的误差矢量， 误差矢量轴位，术源性散光和矫正比比较差异均无统计学意义(均P>0.05)。

结论：基于Self-Attention注意力机制和Pix2Pix网络可以对术后角膜地形图做到良好的预测，可以为眼科临床医生的手术规划和术后效果提供参考。

METHODS:In this retrospective case series study, the 210 preoperative and postoperative corneal topographies from 87 age-related cataract patients(105 eyes)undergoing femtosecond laser arcuate keratotomy at Shanxi Eye Hospital between March 2018 and March 2020 were selected and divided into a training set(180)and a test set(30)for model training and testing. The peak signal-to-noise ratio(PSNR), structural similarity(SSIM)and Alpins astigmatism vector analysis were used to compare the accuracy of postoperative corneal topography prediction under different attention mechanisms.

RESULTS:The model based on attention mechanism and Pix2Pix network can predict postoperative corneal topography, among which the model based on Self-Attention mechanism has the best prediction effect, with PSNR and SSIM reaching 16.048 and 0.7661, respectively. There were no statistically significant differences in the difference vector, difference vector axis position, surgically induced astigmatism, and correction index between real and generated corneal topography on the 3mm and 5mm rings(all P>0.05).

CONCLUSION:Based on the Self-Attention mechanism and Pix2Pix network, the postoperative corneal topography can be well predicted, which can provide reference for the surgical planning and postoperative effects of ophthalmic clinicians.