Evidence map›Paper›PMID 40827890›Full record

ArticleJournal of cataract and refractive surgery2026

Validation of a new implantable collamer lens sizing algorithm based on SS-OCT images.

Pierre Zéboulon, Nicole Mechleb, Maria Rizk, Roxane Flamant, Tobias Duncker, Raphael Neuhann, Damien Gatinel, Alain Saad

Abstract readMulticenter StudyValidation Study
In one paragraph

Article in Journal of cataract and refractive surgery, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

8 authors.

Pierre ZéboulonFrom the Department of Anterior and Refractive Surgery, Rothschild Foundation Hospital, Paris, France (Zéboulon, Mechleb, Rizk, Flamant, Gatinel, Saad); Institute of Ophthalmology, Halle, Germany (Duncker); Dr. Neuhann's Eye Clinic, Munich, Germany.ORCID 0000-0003-2192-3210
Tobias Duncker
Raphael Neuhann
Damien Gatinel

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo evaluate the performance of a new deep learning-based implantable collamer lens (ICL) sizing model that uses raw swept-source optical coherence tomography (SS-OCT) images as an input.

settingMulticenter European study.

designRetrospective external validation study.

methodsPatients implanted with EVO ICL V4 at 2 European clinics between October 2019 and April 2024 were analyzed. Preoperative OCT images and implanted ICL data were processed by the model under study, which predicted vault, confidence levels, and the probability of achieving a postoperative vault within 250 to 750 μm (P250-750). Predictions were compared with actual postoperative vaults, and performance metrics such as mean absolute error (MAE), P250-750 accuracy, and postoperative vault distribution were assessed. Preoperative images were evaluated blinded from the postoperative results.

results848 eyes from 429 patients were included. The mean postoperative vault was 476 ± 235 μm, with a model MAE of 146 ± 113 μm, significantly outperforming the STAAR nomogram (186 ± 149 μm; P < .001). The model correctly predicted vaults within ±250 μm in 81.7% of cases and ±300 μm in 90.7%. Among cases outside the 250 to 750 μm range (28.9%), the model recommended more appropriate sizes in 70.6%. P250-750 was comparable with the actual proportion of eyes achieving a satisfactory vault for P250-750 >60%. In cases requiring lens exchange, the model's suggested size aligned with the final implanted size in 81.8% of cases.

conclusionsThis deep learning-based model, using raw OCT images, provided accurate ICL sizing predictions and valuable metrics such as P250-750 to assist clinical decision-making. This approach may reduce sizing errors and improve patient outcomes. The model is available for ANTERION SS-OCT users at safevaulticl.com .

Indexed as

AlgorithmsDeep LearningLens Implantation, IntraocularMyopiaPhakic Intraocular LensesTomography, Optical CoherenceAdultFemaleHumansMaleMiddle AgedRetrospective StudiesVisual Acuity

Identifiers

PMID40827890
PMCPMC12777588

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.