Background: Cataract surgery has been recently developed from sight rehabilitating surgery to accurate refractive surgery. The precise concentration of intraocular lens (IOL) is crucial for postoperative high visual quanlity. The three-dimentional (3D) images of ocular anterior segment captured by optial coherence tomography (OCT) make it possible to evaluate the IOL position in 3D space, which provide insights into factors relavant to the visual quanlity and better design of new functional IOL. The deep learning algorithm potentially quantify the IOL position in an objective and efficient way. Methods: The region-based fully convolutional network (R-FCN) was used to recogonize and delineate the IOL configuration in 3D OCT images. Scleral spur was identified automatically. Then the tilt angle of the IOL relative to the scleral spur plane along with its decentration with respect to the pupil were calculated. Repeatability and reliability of the method was evaluated by the intraclass correlation coefficient. Results: After improvement, the R-FCN network recognition efficiency of IOL configuration reached 0.910. The ICC of reliability and repeatability of the method is 0.867 and 0.901. The average tilt angle of the IOL relative to scleral spur is located in 1.65 +/- 1.00 degrees. The offsets dx and dy occurring in the early X and Y directions of the IOL are 0.29 +/- 0.22 and 0.33 +/- 0.24 mm, respectively. The IOL offset distance is 0.44 +/- 0.33 mm. Conclusions: We proposed a practical method to quantify the IOL postion in 3D space based on OCT images and assisted by an algorithm.
基金：
Beijing Municipal Administration of Hospitals' Youth Programme [QML20180202]; National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [U1713220]
第一作者机构：[1]Capital Med Univ,Beijing Tongren Hosp,Beijing Inst Ophthalmol,Beijing,Peoples R China
共同第一作者：
通讯作者：
通讯机构：[4]Capital Med Univ,Beijing Tongren Hosp,Beijing Key Lab Ophthalmol & Visual Sci,Beijing Tongren Eye Ctr,Beijing,Peoples R China[*1]Capital Med Univ,Beijing Tongren Hosp,Ophthalmol Dept,Dong Jiao Min Xiang 1,Beijing,Peoples R China
推荐引用方式(GB/T 7714)：
Xin Chen,Bian Gui-Bin,Zhang Haojie,et al.Optical coherence tomography-based deep learning algorithm for quantification of the location of the intraocular lens[J].ANNALS OF TRANSLATIONAL MEDICINE.2020,8(14):doi:10.21037/atm-20-4706.
APA：
Xin, Chen,Bian, Gui-Bin,Zhang, Haojie,Liu, Weipeng&Dong, Zhe.(2020).Optical coherence tomography-based deep learning algorithm for quantification of the location of the intraocular lens.ANNALS OF TRANSLATIONAL MEDICINE,8,(14)
MLA：
Xin, Chen,et al."Optical coherence tomography-based deep learning algorithm for quantification of the location of the intraocular lens".ANNALS OF TRANSLATIONAL MEDICINE 8..14(2020)
