Publication: Cohort profile: a collaborative multicentre study of retinal optical coherence tomography in 539 patients with neuromyelitis optica spectrum disorders (CROCTINO)
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Program
KU-Authors
KU Authors
Co-Authors
Specovius, Svenja
Zimmermann, Hanna G.
Oertel, Frederike Cosima
Chien, Claudia
Bereuter, Charlotte
Cook, Lawrence J.
Lana Peixoto, Marco Aurelio
Fontenelle, Mariana Andrade
Kim, Ho Jin
Hyun, Jae-Won
Advisor
Publication Date
2020
Language
English
Type
Journal Article
Journal Title
Journal ISSN
Volume Title
Abstract
Purpose: optical coherence tomography (OCT) captures retinal damage in neuromyelitis optica spectrum disorders (NMOSD). Previous studies investigating OCT in NMOSD have been limited by the rareness and heterogeneity of the disease. The goal of this study was to establish an image repository platform, which will facilitate neuroimaging studies in NMOSD. Here we summarise the profile of the Collaborative OCT in NMOSD repository as the initial effort in establishing this platform. This repository should prove invaluable for studies using OCT to investigate NMOSD. Participants: the current cohort includes data from 539 patients with NMOSD and 114 healthy controls. These were collected at 22 participating centres from North and South America, Asia and Europe. The dataset consists of demographic details, diagnosis, antibody status, clinical disability, visual function, history of optic neuritis and other NMOSD defining attacks, and OCT source data from three different OCT devices. Findings to date: the cohort informs similar demographic and clinical characteristics as those of previously published NMOSD cohorts. The image repository platform and centre network continue to be available for future prospective neuroimaging studies in NMOSD. For the conduct of the study, we have refined OCT image quality criteria and developed a cross-device intraretinal segmentation pipeline. Future plans: we are pursuing several scientific projects based on the repository, such as analysing retinal layer thickness measurements, in this cohort in an attempt to identify differences between distinct disease phenotypes, demographics and ethnicities. The dataset will be available for further projects to interested, qualified parties, such as those using specialised image analysis or artificial intelligence applications.
Description
Source:
BMJ Open
Publisher:
BMJ Publishing Group
Keywords:
Subject
Medicine, General and internal medicine