Research progress on prediction of postoperative intraocular lens position

Autor:	Jun Hu, Wan-Ping Zhang, Dan-Min Cao, Qiong Lei
Jazyk:	angličtina
Rok vydání:	2024
Předmět:	anterior chamber depth artificial intelligence crystalline lens geometry effective lens position Ophthalmology RE1-994
Zdroj:	Indian Journal of Ophthalmology, Vol 72, Iss Suppl 2, Pp S176-S182 (2024)
Druh dokumentu:	article
ISSN:	0301-4738 1998-3689
DOI:	10.4103/IJO.IJO_1839_23
Popis:	With the progress in refractive cataract surgery, more intraocular lens (IOL) power formulas have been introduced with the aim of reducing the postoperative refractive error. The postoperative IOL position is critical to IOL power calculations. Therefore, the improvements in postoperative IOL position prediction will enable better selection of IOL power and postoperative refraction. In the past, the postoperative IOL position was mainly predicted by preoperative anterior segment parameters such as preoperative axial length (AL), anterior chamber depth (ACD), and corneal curvature. In recent years, some novel methods including the intraoperative ACD, crystalline lens geometry, and artificial intelligence (AI) of prediction of postoperative IOL position have been reported. This article attempts to give a review about the research progress on prediction of the postoperative IOL position.
Databáze:	Directory of Open Access Journals
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