Impact and Correction of an Anterior Phakic Intraocular Lens on Swept-Source Optical Coherence Tomography Biometry

Author:

Barbosa Ribeiro Bruno,Monteiro Sílvia,Heitor Marques João,Abreu Ana Carolina,Pinto Maria do Céu

Abstract

Purpose: To evaluate the impact of anterior chamber phakic intraocular lens (pIOL) on swept-source optical coherence tomography (SS-OCT) biometric measurements and IOL power calculation. Methods: This retrospective analysis of 67 eyes of 49 patients with previous anterior chamber pIOL implantation analyzed the accuracy of automatic segmentation of the anterior surface of the crystalline lens and its impact on anterior chamber depth (ACD, measured from epithelium to lens), lens thickness measurements, and IOL power calculation. The sample was divided into two groups: correct detection of the anterior surface of the crystalline lens and inaccurate detection. Segmentation of eyes from the inaccurate detection group was manually corrected and ACD and lens thickness were calculated using ImageJ software. IOL power was calculated using 7 formulas for both measurements. Results: The anterior surface of the crystalline lens was mis-identified in 13 (19.4%) eyes. ACD was underestimated (Δ −0.85 ± 0.33 mm, P < .001) and lens thickness was overestimated (Δ +0.81 ± 0.25 mm, P < .001). Manual correction changed the target spherical equivalent only in the Haigis formula ( P = .009). After correction for segmentation bias, the Pearl DGS, Cooke K6, and EVO 2.0 formulas showed the lowest prediction error, with the Pearl DGS showing greatest accuracy within ±1.00 diopters of prediction error range (81.0%). Conclusions: SS-OCT biometry misidentifies the anterior surface of the crystalline lens in a significant proportion, resulting in significant IOL power calculation error in the Haigis formula. Manual proofing of segmentation is mandatory in every patient with anterior chamber pIOL implantation. After correct segmentation, the Pearl DGS, Cooke K6, and EVO seem to be the best formulas. [ J Refract Surg . 2024;40(8):e562–e568.]

Publisher

SLACK, Inc.

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