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Utility of icobrain for brain volumetry in multiple sclerosis clinical practice
AL. Nguyen, MP. Sormani, D. Horakova, EH. Havrdova, MH. Barnett, N. De Stefano, M. Battaglini, M. Vaneckova, E. Lui, F. Gaillard, PM. Desmond, H. Prime, M. Datta, A. Van der Walt, VG. Jokubaitis, F. Podevyn, R. Zivadinov, B. Weinstock-Guttman,...
Jazyk angličtina Země Nizozemsko
Typ dokumentu časopisecké články, multicentrická studie
- MeSH
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- magnetická rezonanční tomografie * MeSH
- mozek * diagnostické zobrazování patologie MeSH
- relabující-remitující roztroušená skleróza diagnostické zobrazování farmakoterapie patologie MeSH
- retrospektivní studie MeSH
- roztroušená skleróza diagnostické zobrazování patologie MeSH
- velikost orgánu MeSH
- Check Tag
- dospělí MeSH
- lidé středního věku MeSH
- lidé MeSH
- mužské pohlaví MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- multicentrická studie MeSH
BACKGROUND: Few studies on multiple sclerosis (MS) have explored the variability of percentage brain volume change (PBVC) measurements obtained from different clinical MRIs. In a retrospective multicentre cohort study, we quantified the variability of annualised PBVC in clinical MRIs. METHODS: Clinical MRIs of relapse-onset MS patients were assessed by icobrain. Volumetric data were analysed on same-scanner and different-scanner MRI pairs if they passed quality control criteria. Alignment similarity between two images had to be comparable to same-scanner scan-rescan images. RESULTS: Of 6826 MRIs, 85 % had appropriate volumetric sequences and 4446 serial MRI pairs were analysed. 3334 (75 %) MRI pairs from 1207 patients met the inclusions. The PBVC of included MRI pairs showed variance of 0.78 % for same-scanner pairs and 0.80 % for different-scanner pairs. Further selection of included MRI pairs with the best variance resulted in 1885 (42 %) MRI pairs with PBVC variance of 0.34 %. Excluded MRI pairs with poor alignment similarity had variances of 2.97 % for same-scanner pairs and 20.79 % for different-scanner pairs. CONCLUSION: Icobrain should be utilised for PBVC determination only on selected MRIs with the best alignment similarity. Applying strict selection criteria for the included MRI pairs and longitudinal imaging on the same scanner remain mandatory to reduce PBVC variability.
AI supported modelling in clinical sciences Vrije Universiteit Brussel Brussels Belgium
Brain and Mind Centre University of Sydney Sydney Australia
Centre for Brain and Mental Health Hunter Medical Research Institute Newcastle Australia
Centro de Esclerosis Múltiple de Buenos Aires Buenos Aires Argentina
CORe Department of Medicine University of Melbourne Melbourne Australia
Department GF Ingrassia Section of Neurosciences University of Catania Catania Italy
Department of Engineering University of Oxford Oxford United Kingdom
Department of Health Sciences Biostatistics Unit University of Genoa Genoa Italy
Department of Medical Imaging Royal Melbourne Hospital Melbourne Australia
Department of Medicine Surgery and Neuroscience University of Siena Siena Italy
Department of Neurology Ghent University Hospital Gent Belgium
Department of Neurology John Hunter Hospital Newcastle Australia
Department of Neurology State University of New York at Buffalo Buffalo United States
Department of Neurology Université Catholique de Louvain Brussels Belgium
Department of Neuroscience School of Translational Medicine Monash University Melbourne Australia
Department of Radiology Box Hill Hospital Melbourne Australia
Department of Radiology University of Melbourne Melbourne Australia
Icometrix Research and Development Leuven Belgium
National MS Center Melsbroek Melsbroek Belgium
Neuroimmunology Centre Royal Melbourne Hospital University of Melbourne Melbourne Australia
School of Medicine and Public Health University of Newcastle Newcastle Australia
Citace poskytuje Crossref.org
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