Downloaded from http://journals.lww.com/jcrs by BhDMf5ePHKbH4TTImqenVGBWJMQ4hzAO4tKHLM/6u1SJBPznv31FcCRePai//EH9 on 08/24/2020 ARTICLE Comparison of various intraocular lens formulas using a new high-resolution swept-source optical coherence tomographer Eszter Szalai, MD, PhD, Noemi Toth, MD, Zsofia Kolkedi, MD, Csaba Varga, MD, Adrienne Csutak, MD, PhD Purpose: To compare vergence, artificial intelligence, and com- bined intraocular lens (IOL) calculation formulas using a new swept- source optical coherence tomographer (SS-OCT) and to analyze their performance based on manifest and estimated refractive outcomes of cataract surgery. Setting: Department of Ophthalmology, University of P ´ ecs Med- ical School, P ´ ecs, Hungary. Design: Retrospective data analysis. Methods: Optical biometry readings of patients who underwent uneventful cataract removal and implantation of a monofocal acrylic IOL were used to predict IOL power with Barrett Universal II (BUII), Haigis, Hoffer Q, Holladay 1, Radial Basis Function (RBF) 2.0, Kane, Ladas Super Formula, and SRK/T. All the implanted IOLs were calculated by using the Haigis formula. The arithmetic prediction error and median and mean absolute refractive errors for all formulas were computed. The percentage of eyes within ±0.25 diopters (D), ±0.50 D, and ±1.0 D of prediction error was calculated. Results: A total of 95 eyes of 95 patients with a mean age of 68.80 ± 7.57 years were included. There was a statistically significant difference in absolute prediction error across the 8 IOL calculation formulas (P < .0001). Haigis showed the lowest mean absolute error, and it differed significantly from the BUII, Hoffer Q, Holladay 1, Ladas, RBF 2.0, and SRK/T formulas (P < .05). In terms of eyes within ±0.25 D, ±0.50 D, and ±1.0 D of prediction error, the Haigis formula showed the overall best performance. Conclusions: The results indicated that a recently developed SS- OCT provided accurate ocular biometry measurements before cataract surgery, and the Haigis formula incorporated in its software enabled precise calculation of IOL refractive power. J Cataract Refract Surg 2020; 46:1138–1141 Copyright © 2020 Published by Wolters Kluwer on behalf of ASCRS and ESCRS I nstrumentation and preoperative planning of cataract surgery have changed profoundly since its first in- troduction in 1949. Accurate calculation of the intraocular lens (IOL) is one of the most important determinants of surgical outcome and patient satisfaction. Performance of IOL power calculation formulas has been evolving rapidly from the refraction-based methods to the artificial intelligence–based formulas. 1,2 Variables used in these formulas are axial length (AL), keratometry (K), anterior chamber depth (ACD, mea- sured from the epithelium to the anterior lens surface), lens thickness (LT), central corneal thickness (CCT), corneal di- ameter (CD), patient age, and gender. The most recent third- generation optical biometers using swept-source optical co- herence tomography (SS-OCT) technology are able to provide data on corneal surfaces, anterior chamber parameters, thickness of the crystalline lens, and corneal pachymetry. 3 The purpose of this study was to compare third- and fourth- generation vergence, artificial intelligence, and combined IOL power calculation formulas using a recently developed mul- timodal high-resolution SS-OCT and to analyze their per- formance based on manifest and estimated refractive outcomes of cataract surgery. METHODS Study Design Retrospective data analysis was performed on 95 eyes of 95 patients (54 women [57%]; 51 left eyes [54%]). All patients had a negative history of ocular disease (other than refractive errors excluding corneal ectasias), trauma, or previous ocular surgery. Biometry was performed preoperatively using a recently introduced high- wavelength swept-source anterior segment OCT (ANTERION, Heidelberg Engineering GmbH). All patients underwent uneventful phacoemulsification and implantation of a monofocal acrylic IOL. The implanted IOLs were Medicontur 690AB (Medical Engineering Ltd.) in 39 eyes (41.05%), Akreos Adapt AO (Bausch & Lomb, Inc.) in 30 eyes (32.43%), Alcon SA60AT (Alcon Laboratories Inc.) in 12 eyes (12.63%), Alcon SN60WF (Alcon Laboratories Inc.) in 11 eyes (11.58%), and Alcon Clareon (Alcon Laboratories Inc.) in 3 eyes Submitted: April 4, 2020 | Final revision submitted: June 21, 2020 | Accepted: June 24, 2020 From the Department of Ophthalmology, University of P ´ ecs Medical School, P ´ ecs, Hungary. Corresponding author: Eszter Szalai, MD, PhD, Department of Ophthalmology, University of P ´ ecs Medical School, R ´ akóczi u. 2, 7623 P ´ ecs, Hungary. Email: szalai.eszter@pte.hu. 1138 Copyright © 2020 Published by Wolters Kluwer on behalf of ASCRS and ESCRS Published by Wolters Kluwer Health, Inc. 0886-3350/$ - see frontmatter https://doi.org/10.1097/j.jcrs.0000000000000329 Copyright © 2020 Published by Wolters Kluwer on behalf of ASCRS and ESCRS. Unauthorized reproduction of this article is prohibited.