Treffer: Intraocular lens calculation formula developed using artificial intelligence for ultrasonic biometry.

Title:
Intraocular lens calculation formula developed using artificial intelligence for ultrasonic biometry.
Authors:
Kuiava VA; Departamento de Oftalmologia, Hospital de Clínicas de Porto Alegre, Porto Alegre, RS, Brazil., Kuiava EL; Departamento de Engenharia Elétrica, Centro Universitário Internacional, São Miguel do Oeste, Santa Catarina, Brazil., Chielli EO; Departamento de Ciências pela Vida, Universidade do Oeste de Santa Catarina São Miguel do Oeste, Santa Catarina, Brazil., Ruschel DM; Departamento de Oftalmologia, Hospital de Clínicas de Porto Alegre, Porto Alegre, RS, Brazil., Marafon SB; Departamento de Oftalmologia, Hospital de Clínicas de Porto Alegre, Porto Alegre, RS, Brazil.
Source:
Arquivos brasileiros de oftalmologia [Arq Bras Oftalmol] 2025 Apr 28; Vol. 88 (4), pp. e20240083. Date of Electronic Publication: 2025 Apr 28 (Print Publication: 2025).
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Conselho Brasileiro de Oftalmologia Country of Publication: Brazil NLM ID: 0400645 Publication Model: eCollection Cited Medium: Internet ISSN: 1678-2925 (Electronic) Linking ISSN: 00042749 NLM ISO Abbreviation: Arq Bras Oftalmol Subsets: MEDLINE
Imprint Name(s):
Publication: São Paulo : Conselho Brasileiro de Oftalmologia
Original Publication: São Paulo.
MeSH Terms:
Biometry*/methods , Lenses, Intraocular* , Artificial Intelligence*, Humans ; Middle Aged ; Aged ; Refraction, Ocular/physiology ; Female ; Male ; Reproducibility of Results ; Phacoemulsification/methods ; Lens Implantation, Intraocular/methods ; Adult ; Aged, 80 and over
Entry Date(s):
Date Created: 20250429 Date Completed: 20250429 Latest Revision: 20250429
Update Code:
20250429
DOI:
10.5935/0004-2749.2024-0083
PMID:
40298745
Database:
MEDLINE

Weitere Informationen

Purpose: We developed an artificial intelligence program for calculating intraocular lenses and analyzed its accuracy rate via ultrasonic biometry. This endeavor is aimed at enhancing precision and efficacy in the selection of intraocular lenses, particularly in cases where optical biometry is unavailable.
Methods: Data was collected from the Hospital de Clínicas de Porto Alegre, which included cases of phacoemulsification with intraocular lens implantation, in which the lens selection was based on ultrasonic biometry. The program, implemented in Python, Java, and PHP, employs the ridge regression method. Two design options were developed: a basic model, which uses only keratometry variables (K1 and K2), axial size and final target refraction in the spherical equivalent, and an advanced model, which incorporates preoperative refraction and the patient's age. The Universal Barrett II formula was used to compare both models.
Results: The sample consisted of 486 eyes from 313 patients, with 350 eyes used for program training and 136 for program validation. The spherical equivalent hit rates, with a variation of ±0.5 D, were 86% and 87.5% for the basic and advanced models, respectively, with no statistically significant difference between them. With the Barret Universal II formula, the success rate was 69%, which was significantly different from the values of the two aforementioned models (p<0.0001). The system was better for medium and long eyes but worse for short eyes (<=22.00 mm).
Conclusion: The developed artificial intelligence program was superior to the Barrett formula in terms of performance, in the general context and within the subgroup of patients with longer eyes. This innovation can considerably contribute to the selection of intraocular lenses, particularly in cases where optical biometry is unavailable.