Automated biometry of human ocular anterior segment based on spectral domain optical coherence tomography

Background Ultra-long scan depth OCT can achieve imaging of full range of human ocular anterior segment.However, the measurement of the dimension of anterior segment from the OCT image with high speed and precision is a challenge at present.The software of automatic data processing is still lack in analyzing spectral domain OCT. Objective This study was to perform the automatic biometry and data processing of human ocular anterior segment OCT image by using self-developed automatic detection software and evaluate the accuracy and repeatability of this method. Methods Twenty eyes of 10 normal subjects were included in Eye Hospital of Wenzhou Medical University from June to July 2013.The OCT image of anterior eye segments were obtained with custom-made ultra-long scan depth OCT under the informed consent.An automatic software algorithm was developed for the biometric measurement on these OCT images, including boundary segmentation, image registration and optical correction of OCT images.The boundary segmentation algorithm utilized the axial gradient information of OCT images and the shortest path search principal based on the dynamic programming to optimize edge finding.Central corneal thickness (CCT), anterior chamber depth (ACD), pupil diameter (PD), lens thickness (LT), radius of lens anterior curvatures (LAC) and radius of lens of posterior curvatures (LPC) were automatically and manually measured, and the validity of automatic detection algorithm was assessed by calculating the intraclass correlation coefficient (ICC) between the automatic and manual measurements, and the repeatability was validated by calculating the coefficient of repeatability (COR) between repeated measurement.This study was approved by the Ethic Committee of Wenzhou Medical University and informed consent was obtained from all subjects. Results There were no significant differences in the results of CCT, ACD, PD, LT, LAC and LPC between the automatic and manual measurements (P=0.205, 0.167, 0.285, 0.127, 0.102, 0.074). The results were consistent between automatic and manual measurements (all at ICC>0.75). The repeated measurement values were consistent in CCT, ACD and LT in both automatic and manual modes (all at ICC>0.75). The reproducibilities of automatic biometry in PD and LAC (ICC=0.793, 0.872; COR=2.90, 5.79) were better than those of manual mode (ICC=0.631, 0.579; COR=5.62, 10.46); while the reproducibility of automatic biometry in LPC (ICC=0.663; COR=6.17) was lower than that of manual mode (ICC=0.794, COR=4.79). Conclusions Self-developed automatic detection software appears to be accurate and repeatable in measuring dimension of spectral domain OCT images.This automatic software algorithm can be used for the biometry and monitor of human ocular anterior segment. Key words: Biometry/methods; Tomography, optical coherence/methods; Automatic data processing; Anterior eye segment/anatomyh Reproducibility