TY - JOUR
T1 - Artificial intelligence extension of the OSCAR-IB criteria
AU - Petzold, Axel
AU - Albrecht, Philipp
AU - Balcer, Laura
AU - Bekkers, Erik
AU - Brandt, Alexander U
AU - Calabresi, Peter A
AU - Deborah, Orla Galvin
AU - Graves, Jennifer S
AU - Green, Ari
AU - Keane, Pearse A
AU - Nij Bijvank, Jenny A
AU - Sander, Josemir W
AU - Paul, Friedemann
AU - Saidha, Shiv
AU - Villoslada, Pablo
AU - Wagner, Siegfried K
AU - Yeh, E Ann
AU - IMSVISUAL, ERN-EYE Consortium
A2 - Hamann, Steffen Ellitsgaard
A2 - Pihl-Jensen, Gorm
N1 - © 2021 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.
PY - 2021/7
Y1 - 2021/7
N2 - Artificial intelligence (AI)-based diagnostic algorithms have achieved ambitious aims through automated image pattern recognition. For neurological disorders, this includes neurodegeneration and inflammation. Scalable imaging technology for big data in neurology is optical coherence tomography (OCT). We highlight that OCT changes observed in the retina, as a window to the brain, are small, requiring rigorous quality control pipelines. There are existing tools for this purpose. Firstly, there are human-led validated consensus quality control criteria (OSCAR-IB) for OCT. Secondly, these criteria are embedded into OCT reporting guidelines (APOSTEL). The use of the described annotation of failed OCT scans advances machine learning. This is illustrated through the present review of the advantages and disadvantages of AI-based applications to OCT data. The neurological conditions reviewed here for the use of big data include Alzheimer disease, stroke, multiple sclerosis (MS), Parkinson disease, and epilepsy. It is noted that while big data is relevant for AI, ownership is complex. For this reason, we also reached out to involve representatives from patient organizations and the public domain in addition to clinical and research centers. The evidence reviewed can be grouped in a five-point expansion of the OSCAR-IB criteria to embrace AI (OSCAR-AI). The review concludes by specific recommendations on how this can be achieved practically and in compliance with existing guidelines.
AB - Artificial intelligence (AI)-based diagnostic algorithms have achieved ambitious aims through automated image pattern recognition. For neurological disorders, this includes neurodegeneration and inflammation. Scalable imaging technology for big data in neurology is optical coherence tomography (OCT). We highlight that OCT changes observed in the retina, as a window to the brain, are small, requiring rigorous quality control pipelines. There are existing tools for this purpose. Firstly, there are human-led validated consensus quality control criteria (OSCAR-IB) for OCT. Secondly, these criteria are embedded into OCT reporting guidelines (APOSTEL). The use of the described annotation of failed OCT scans advances machine learning. This is illustrated through the present review of the advantages and disadvantages of AI-based applications to OCT data. The neurological conditions reviewed here for the use of big data include Alzheimer disease, stroke, multiple sclerosis (MS), Parkinson disease, and epilepsy. It is noted that while big data is relevant for AI, ownership is complex. For this reason, we also reached out to involve representatives from patient organizations and the public domain in addition to clinical and research centers. The evidence reviewed can be grouped in a five-point expansion of the OSCAR-IB criteria to embrace AI (OSCAR-AI). The review concludes by specific recommendations on how this can be achieved practically and in compliance with existing guidelines.
KW - Algorithms
KW - Artificial Intelligence/trends
KW - Big Data
KW - Cohort Studies
KW - Humans
KW - Nervous System Diseases/diagnostic imaging
KW - Retina/diagnostic imaging
KW - Tomography, Optical Coherence/methods
UR - http://www.scopus.com/inward/record.url?scp=85105998632&partnerID=8YFLogxK
U2 - 10.1002/acn3.51320
DO - 10.1002/acn3.51320
M3 - Review
C2 - 34008926
SN - 2328-9503
VL - 8
SP - 1528
EP - 1542
JO - Annals of Clinical and Translational Neurology
JF - Annals of Clinical and Translational Neurology
IS - 7
ER -