Predicting the vault after ICL implantation using intraoperative OCT: Establishment and application of models

Our findings demonstrate that iOCT enables accurate real-time intraoperative vault measurement, which reliably predicts postoperative vault dimensions. The developed ML model provides an objective, data-driven approach to optimize ICL orientation during surgery, potentially improving clinical outcomes.

Authors

Institutions

Publication Details

Journal
Journal of Cataract & Refractive Surgery
Published
2026-02-16
DOI
https://doi.org/10.1097/j.jcrs.0000000000001913
Primary Topic
Corneal surgery and disorders
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Predicting the vault after ICL implantation using intraoperative OCT: Establishment and application of models

Hong Yan, Xueyu Du
Journal of Cataract & Refractive Surgery
Corneal surgery and disorders
article

Predicting the vault after ICL implantation using intraoperative OCT: Establishment and application of models

Hong Yan, Xueyu Du
article en

Abstract

Our findings demonstrate that iOCT enables accurate real-time intraoperative vault measurement, which reliably predicts postoperative vault dimensions. The developed ML model provides an objective, data-driven approach to optimize ICL orientation during surgery, potentially improving clinical outcomes.

Journal of Cataract & Refractive Surgery
Northwest University (CN), Shanxi Eye Hospital (CN), Hanzhong Central Hospital (CN)
Openalex Percentile: Top 54%
Corneal surgery and disorders
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.