Introducing The Lens Diameter To Iol Power Calculation (Part Of The 1000 Eyes Lens Power Trial)
Published 2023
- 41st Congress of the ESCRS
Reference: FP05.04
| Type: Free paper
| DOI:
10.82333/98ba-6249
Authors:
Leon Pomberger* 1
, Klemens Waser 2
, Haidar Khalil 2
, Marina Casazza 2
, Lisa Tasch 2
, Matthias Bolz 2
, Nino Hirnschall 2
1Ophthalmology,Johannes Kepler University,Linz,Austria;Ophthalmology,Kepler University Clinic,Linz,Austria, 2Ophthalmology,Kepler University Clinic,Linz,Austria;Ophthalmology,Johannes Kepler University,Linz,Austria
Purpose
To develop an artificial intelligence-based method for forecasting the postoperative lens position, leveraging preoperative lens diameter as a predictive feature, and to investigate the impact of lens diameter on postoperative refraction
Setting
Department of Ophthalmology and Optometry, Johannes Kepler University, Linz, Austria ; Department of Ophthalmology, Medical University Graz, Austria; Department of Ophthalmology, Medical University Sankt Pölten, Austria
Methods
This multi-center study included 1000 eyes that underwent cataract surgery between July 2021 and January 2022. All eyes received a swept-source OCT biometry (IOL Master 700) followed by implantation of a monofocal hydrophobic open loop haptic IOL. Study examination was performed minimum 4 weeks and maximum 24 months after surgery and included optical biometry, autorefraction as well as subjective refraction. Main parameter for the AI based approached were the preoperative lens diameter and the postoperative anterior chamber depth as well the subjective postoperative refraction.
Results
In total, 1000 eyes of 1000 patients were included at three recruitment centers. The AL of the included eyes ranged from 19.86mm - 31.61mm with a mean eye length of 23.49 (SD 1.36). The mean preoperative anterior chamber depth was 3.13mm (SD 0.47mm), the mean measured postoperative anterior chamber depth was 4.76mm (SD 0.51mm). Preliminary data show that the preoperative lens diameter could have a high predictive value for the effective postoperative lens position. A novel AI based concept for predicting the postoperative anterior chamber depth and the effective lens position will be presented at the ESCRS meeting.
Conclusions
The recently developed artificial intelligence-based model can predict the effective postoperative lens position (ELP) with greater precision compared to previous approaches. As a result, this model could potentially lead to a reduction in the incidence of refractive surprises following cataract surgery.