Artificial intelligence extension of the OSCAR-IB criteria

被引:31
作者
Petzold, Axel [1 ,2 ]
Albrecht, Philipp [3 ]
Balcer, Laura [4 ,5 ]
Bekkers, Erik [6 ]
Brandt, Alexander U. [7 ]
Calabresi, Peter A. [8 ]
Deborah, Orla Galvin [9 ]
Graves, Jennifer S. [10 ]
Green, Ari [11 ]
Keane, Pearse A. [1 ]
Bijvank, Jenny A. Nij [2 ]
Sander, Josemir W. [12 ,13 ,14 ]
Paul, Friedemann [15 ,16 ,17 ,18 ,19 ]
Saidha, Shiv [8 ]
Villoslada, Pablo [20 ,21 ]
Wagner, Siegfried K. [1 ]
Yeh, E. Ann [22 ,23 ]
机构
[1] Moorfields Eye Hosp, UCL Queen Sq Inst Neurol, Natl Hosp Neurol & Neurosurg, City Rd,Queen Sq, London, England
[2] Amsterdam UMC, Neuroophthalmol Expert Ctr, Amsterdam, Netherlands
[3] Heinrich Heine Univ, Med Fac, Dept Neurol, Dusseldorf, Germany
[4] NYU Grossman Sch Med, Dept Neurol, New York, NY USA
[5] NYU Grossman Sch Med, Dept Populat Hlth & Ophthalmol, New York, NY USA
[6] AMLAB, Amsterdam, Netherlands
[7] Univ Calif Irvine, Dept Neurol, Irvine, CA 92717 USA
[8] Johns Hopkins Univ, Sch Med, Dept Neurol, Baltimore, MD 21205 USA
[9] Retina Int, Dublin, Ireland
[10] UC, Dept Neurosci, San Diego, CA USA
[11] Univ Calif San Francisco, Dept Neurol, San Francisco, CA USA
[12] NIHR UCL Hosp Biomed Res Ctr, UCL Queen Sq Inst Neurol, London, England
[13] Chalfont Ctr Epilepsy, Gerrards Cross, England
[14] Stichting Epilepsie Instellingen Nederland SEIN, Heemstede, Netherlands
[15] Max Delbruck Ctr Mol Med, Expt & Clin Res Ctr, Berlin, Germany
[16] Charite Univ Med Berlin, Berlin, Germany
[17] Free Univ Berlin, Berlin, Germany
[18] Humboldt Univ, Berlin, Germany
[19] Berlin Inst Hlth, Berlin, Germany
[20] Univ Barcelona, Inst Invest Biomed August Pi Sunyer DIBAPS, Barcelona, Spain
[21] Univ Barcelona, Hosp Clin, Barcelona, Spain
[22] Univ Toronto, Hosp Sick Children, Dept Pediat, Div Neurol,Div Neurosci, Toronto, ON, Canada
[23] Univ Toronto, Mental Hlth SickKids Res Inst, Toronto, ON, Canada
基金
英国医学研究理事会;
关键词
OPTICAL COHERENCE TOMOGRAPHY; MICROCYSTIC MACULAR EDEMA; INNER NUCLEAR LAYER; MULTIPLE-SCLEROSIS; RETINAL PATHOLOGY; DISEASE; OCT; DEGENERATION; SEGMENTATION; ASSOCIATION;
D O I
10.1002/acn3.51320
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
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.
引用
收藏
页码:1528 / 1542
页数:15
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