I-SCREEN: Development of an AI-based infrastructure for community-wide screening and prediction of progression in age-related macular degeneration providing accessible shared care

Marie Louise Enzendorfer; Gregor S Reiter; Hrvoje Bogunović; Sophie Riedl; Julia Mai; Johannes Schrittwieser; Christoph Stapf; Virginia Mares; Matjaž Mihelčič; Julie-Anne Little; Polona Jaki-Mekjavić; Daniel Barthelmes; Katja Hatz; Javier Zarranz-Ventura; Catherine Creuzot-Garcher; Ruth Hogg; Amir Sadeghipour; Ursula Schmidt-Erfurth

doi:10.1038/s41433-026-04487-0

I-SCREEN: Development of an AI-based infrastructure for community-wide screening and prediction of progression in age-related macular degeneration providing accessible shared care

, Marie Louise Enzendorfer
, Gregor S Reiter
, Hrvoje Bogunović
, Sophie Riedl
, Julia Mai
, Johannes Schrittwieser
, Christoph Stapf
, Virginia Mares
, Matjaž Mihelčič
, Julie-Anne Little
, Polona Jaki-Mekjavić
, Daniel Barthelmes
, Katja Hatz
, Javier Zarranz-Ventura
, Catherine Creuzot-Garcher
, Ruth Hogg
, Amir Sadeghipour
, Ursula Schmidt-Erfurth

Research output: Contribution to journal › Article › peer-review

7 Downloads (Pure)

Abstract

Objectives
This work describes the design and methodological framework of the I-SCREEN project, which aims to develop an artificial intelligence (AI)-based infrastructure utilising optical coherence tomography (OCT) for early detection of AMD and assessment of progression risk.

Methods
The pan-European project is conducted across clinics and optometry/optician practices in six European countries. I-SCREEN encompasses seven work packages covering community-based AMD identification, clinical follow-up, AI development and project dissemination. Three interconnected clinical studies are carried out by optometry/optician practices (PYRENEES) and ophthalmology clinics (SUDETES and APENNINES).

Results
The PYRENEES study is a prospective, cross-sectional study evaluating the feasibility of detecting subclinical AMD in optometry/optician practices under ophthalmologist supervision via telemedicine. A robust screening network comprising 28 community-based optometry/optician practices and 7 ophthalmology clinics has been established. Patients with suspected non-neovascular AMD are referred to partnered clinics. In the hospital setting, patients with early or intermediate AMD are followed in the longitudinal SUDETES study, while patients with non-foveal geographic atrophy are invited to take part in the APENNINES study. Data obtained inform AI development for community-based AMD detection and monitoring. Predictive modelling will further enable personalised risk assessments.

Conclusions
I-SCREEN brings together multidisciplinary experts across Europe to establish an AI-driven shared care model for AMD detection and monitoring. By combining high-quality OCT imaging from community practices with longitudinal clinical studies, the initiative provides novel insights into early AMD progression and establishes a foundation for innovative AI-based detection and prediction throughout the real-world population.

Original language	English
Pages (from-to)	1806-1814
Number of pages	9
Journal	Eye (London, England)
Volume	40
Issue number	12
Early online date	5 May 2026
DOIs	https://doi.org/10.1038/s41433-026-04487-0
Publication status	Published online - 5 May 2026

Bibliographical note

Funding

The I(eye)-SCREEN project is funded by the European Union, EIC-2023-PATHFINDEROPEN-01 (I-SCREEN, grant no. 101130093), by UK Research and Innovation (UKRI) under the UK government’s Horizon Europe funding guarantee, and by the Swiss State Secretariat for Education, Research and Innovation (SERI). Views and opinions expressed are however those of the authors only and do not necessarily reflect those of the European Union or the European Innovation Council and SMEs Executive Agency (EISMEA). Neither the European Union nor the granting authority can be held responsible for them. Open access funding provided by Medical University of Vienna.

Funders	Funder number
101130093
European Union	101130093, EIC-2023-PATHFINDEROPEN-01

Keywords

Humans
Cross-Sectional Studies
Tomography, Optical Coherence/methods
Macular Degeneration/diagnosis
Prospective Studies
Disease Progression
Artificial Intelligence
Optometry
Telemedicine
Mass Screening/methods
Europe
Female

Access to Document

10.1038/s41433-026-04487-0Licence: CC BY

s41433-026-04487-0.cleanedFinal published version, 859 KBLicence: CC BY

Cite this

, Enzendorfer, M. L., Reiter, G. S., Bogunović, H., Riedl, S., Mai, J., Schrittwieser, J., Stapf, C., Mares, V., Mihelčič, M., Little, J.-A., Jaki-Mekjavić, P., Barthelmes, D., Hatz, K., Zarranz-Ventura, J., Creuzot-Garcher, C., Hogg, R., & Sadeghipour, A., & Schmidt-Erfurth, U. (2026). I-SCREEN: Development of an AI-based infrastructure for community-wide screening and prediction of progression in age-related macular degeneration providing accessible shared care. Eye (London, England), 40(12), 1806-1814. Advance online publication. https://doi.org/10.1038/s41433-026-04487-0

@article{40914dca408243ab995afba011d24f6c,

title = "I-SCREEN: Development of an AI-based infrastructure for community-wide screening and prediction of progression in age-related macular degeneration providing accessible shared care",

abstract = "Objectives This work describes the design and methodological framework of the I-SCREEN project, which aims to develop an artificial intelligence (AI)-based infrastructure utilising optical coherence tomography (OCT) for early detection of AMD and assessment of progression risk. Methods The pan-European project is conducted across clinics and optometry/optician practices in six European countries. I-SCREEN encompasses seven work packages covering community-based AMD identification, clinical follow-up, AI development and project dissemination. Three interconnected clinical studies are carried out by optometry/optician practices (PYRENEES) and ophthalmology clinics (SUDETES and APENNINES). Results The PYRENEES study is a prospective, cross-sectional study evaluating the feasibility of detecting subclinical AMD in optometry/optician practices under ophthalmologist supervision via telemedicine. A robust screening network comprising 28 community-based optometry/optician practices and 7 ophthalmology clinics has been established. Patients with suspected non-neovascular AMD are referred to partnered clinics. In the hospital setting, patients with early or intermediate AMD are followed in the longitudinal SUDETES study, while patients with non-foveal geographic atrophy are invited to take part in the APENNINES study. Data obtained inform AI development for community-based AMD detection and monitoring. Predictive modelling will further enable personalised risk assessments. Conclusions I-SCREEN brings together multidisciplinary experts across Europe to establish an AI-driven shared care model for AMD detection and monitoring. By combining high-quality OCT imaging from community practices with longitudinal clinical studies, the initiative provides novel insights into early AMD progression and establishes a foundation for innovative AI-based detection and prediction throughout the real-world population.",

keywords = "Humans, Cross-Sectional Studies, Tomography, Optical Coherence/methods, Macular Degeneration/diagnosis, Prospective Studies, Disease Progression, Artificial Intelligence, Optometry, Telemedicine, Mass Screening/methods, Europe, Female",

author = "Enzendorfer, \{Marie Louise\} and Reiter, \{Gregor S\} and Hrvoje Bogunovi{\'c} and Sophie Riedl and Julia Mai and Johannes Schrittwieser and Christoph Stapf and Virginia Mares and Matja{\v z} Mihel{\v c}i{\v c} and Julie-Anne Little and Polona Jaki-Mekjavi{\'c} and Daniel Barthelmes and Katja Hatz and Javier Zarranz-Ventura and Catherine Creuzot-Garcher and Ruth Hogg and Amir Sadeghipour and Ursula Schmidt-Erfurth",

note = "{\textcopyright} The Author(s) 2026 ",

year = "2026",

month = may,

day = "5",

doi = "10.1038/s41433-026-04487-0",

language = "English",

volume = "40",

pages = "1806--1814",

journal = "Eye (London, England)",

issn = "0950-222X",

publisher = "Springer Nature",

number = "12",

}

Enzendorfer, ML, Reiter, GS, Bogunović, H, Riedl, S, Mai, J, Schrittwieser, J, Stapf, C, Mares, V, Mihelčič, M, Little, J-A, Jaki-Mekjavić, P, Barthelmes, D, Hatz, K, Zarranz-Ventura, J, Creuzot-Garcher, C, Hogg, R & Sadeghipour, A & Schmidt-Erfurth, U 2026, 'I-SCREEN: Development of an AI-based infrastructure for community-wide screening and prediction of progression in age-related macular degeneration providing accessible shared care', Eye (London, England), vol. 40, no. 12, pp. 1806-1814. https://doi.org/10.1038/s41433-026-04487-0

I-SCREEN: Development of an AI-based infrastructure for community-wide screening and prediction of progression in age-related macular degeneration providing accessible shared care. /; Enzendorfer, Marie Louise; Reiter, Gregor S et al.
In: Eye (London, England), Vol. 40, No. 12, 30.08.2026, p. 1806-1814.

Research output: Contribution to journal › Article › peer-review

TY - JOUR

T1 - I-SCREEN: Development of an AI-based infrastructure for community-wide screening and prediction of progression in age-related macular degeneration providing accessible shared care

AU - Enzendorfer, Marie Louise

AU - Reiter, Gregor S

AU - Bogunović, Hrvoje

AU - Riedl, Sophie

AU - Mai, Julia

AU - Schrittwieser, Johannes

AU - Stapf, Christoph

AU - Mares, Virginia

AU - Mihelčič, Matjaž

AU - Little, Julie-Anne

AU - Jaki-Mekjavić, Polona

AU - Barthelmes, Daniel

AU - Hatz, Katja

AU - Zarranz-Ventura, Javier

AU - Creuzot-Garcher, Catherine

AU - Hogg, Ruth

AU - Sadeghipour, Amir

AU - Schmidt-Erfurth, Ursula

N1 - © The Author(s) 2026

PY - 2026/5/5

Y1 - 2026/5/5

N2 - Objectives This work describes the design and methodological framework of the I-SCREEN project, which aims to develop an artificial intelligence (AI)-based infrastructure utilising optical coherence tomography (OCT) for early detection of AMD and assessment of progression risk. Methods The pan-European project is conducted across clinics and optometry/optician practices in six European countries. I-SCREEN encompasses seven work packages covering community-based AMD identification, clinical follow-up, AI development and project dissemination. Three interconnected clinical studies are carried out by optometry/optician practices (PYRENEES) and ophthalmology clinics (SUDETES and APENNINES). Results The PYRENEES study is a prospective, cross-sectional study evaluating the feasibility of detecting subclinical AMD in optometry/optician practices under ophthalmologist supervision via telemedicine. A robust screening network comprising 28 community-based optometry/optician practices and 7 ophthalmology clinics has been established. Patients with suspected non-neovascular AMD are referred to partnered clinics. In the hospital setting, patients with early or intermediate AMD are followed in the longitudinal SUDETES study, while patients with non-foveal geographic atrophy are invited to take part in the APENNINES study. Data obtained inform AI development for community-based AMD detection and monitoring. Predictive modelling will further enable personalised risk assessments. Conclusions I-SCREEN brings together multidisciplinary experts across Europe to establish an AI-driven shared care model for AMD detection and monitoring. By combining high-quality OCT imaging from community practices with longitudinal clinical studies, the initiative provides novel insights into early AMD progression and establishes a foundation for innovative AI-based detection and prediction throughout the real-world population.

AB - Objectives This work describes the design and methodological framework of the I-SCREEN project, which aims to develop an artificial intelligence (AI)-based infrastructure utilising optical coherence tomography (OCT) for early detection of AMD and assessment of progression risk. Methods The pan-European project is conducted across clinics and optometry/optician practices in six European countries. I-SCREEN encompasses seven work packages covering community-based AMD identification, clinical follow-up, AI development and project dissemination. Three interconnected clinical studies are carried out by optometry/optician practices (PYRENEES) and ophthalmology clinics (SUDETES and APENNINES). Results The PYRENEES study is a prospective, cross-sectional study evaluating the feasibility of detecting subclinical AMD in optometry/optician practices under ophthalmologist supervision via telemedicine. A robust screening network comprising 28 community-based optometry/optician practices and 7 ophthalmology clinics has been established. Patients with suspected non-neovascular AMD are referred to partnered clinics. In the hospital setting, patients with early or intermediate AMD are followed in the longitudinal SUDETES study, while patients with non-foveal geographic atrophy are invited to take part in the APENNINES study. Data obtained inform AI development for community-based AMD detection and monitoring. Predictive modelling will further enable personalised risk assessments. Conclusions I-SCREEN brings together multidisciplinary experts across Europe to establish an AI-driven shared care model for AMD detection and monitoring. By combining high-quality OCT imaging from community practices with longitudinal clinical studies, the initiative provides novel insights into early AMD progression and establishes a foundation for innovative AI-based detection and prediction throughout the real-world population.

KW - Humans

KW - Cross-Sectional Studies

KW - Tomography, Optical Coherence/methods

KW - Macular Degeneration/diagnosis

KW - Prospective Studies

KW - Disease Progression

KW - Artificial Intelligence

KW - Optometry

KW - Telemedicine

KW - Mass Screening/methods

KW - Europe

KW - Female

UR - https://www.scopus.com/pages/publications/105039874815

U2 - 10.1038/s41433-026-04487-0

DO - 10.1038/s41433-026-04487-0

M3 - Article

C2 - 42129346

SN - 0950-222X

VL - 40

SP - 1806

EP - 1814

JO - Eye (London, England)

JF - Eye (London, England)

IS - 12

ER -

I-SCREEN: Development of an AI-based infrastructure for community-wide screening and prediction of progression in age-related macular degeneration providing accessible shared care

Abstract

Bibliographical note

Funding

Keywords

Access to Document

Other files and links

Fingerprint

Cite this