New IOL formula using anterior segment three-dimensional optical coherence tomography

Abstract

This retrospective study was aimed to compare prediction errors from various combinations of biometric data generated using optical coherence tomography (OCT) and develop a new intraocular lens (IOL) formula using biometric data. 145 eyes from 145 patients who underwent femtosecond laser-assisted cataract surgery (FLACS) were enrolled to the present study and they were divided into a training set (n = 92) and a test set (n = 53). Preoperative axial length (AL) and corneal radius were measured using partial coherence interferometry. The anterior chamber depth (ACD), lens meridian parameter (LMP), lens thickness (LT), thickness of anterior and posterior parts of the crystalline lens (aLT and pLT), and anterior segment length were measured by OCT. From a training set, we developed eight regression equations and analyzed the predictive accuracy. The regression equation using AL, LMP, and pLT (-1.143 + 0.148*AL + 0.428*LMP + 0.254*pLT) showed the strongest correlation with effective lens position (ELP) and smallest standard deviation of ELP prediction error. IOL formula generated using AL, LMP, and pLT yielded the highest predictive accuracy. In a test set, the new IOL formula also produced narrowest range of prediction error, smallest median absolute error, and highest percentages within ±0.25, ±0.50 than existing IOL formulas. The IOL formula considering AL, LMP and pLT will help to improve predictive accuracy in FLACS.