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Neuroimaging standards for research into small vessel disease—advances since 2013

Cited 131 time in Web of Science Cited 155 time in Scopus
Authors

Duering, Marco; Biessels, Geert Jan; Brodtmann, Amy; Chen, Christopher; Cordonnier, Charlotte; de Leeuw, Frank-Erik; Debette, Stéphanie; Frayne, Richard; Jouvent, Eric; Rost, Natalia S; ter Telgte, Annemieke; Al-Shahi Salman, Rustam; Backes, Walter H; Bae, Hee-Joon; Brown, Rosalind; Chabriat, Hugues; De Luca, Alberto; deCarli, Charles; Dewenter, Anna; Doubal, Fergus N; Ewers, Michael; Field, Thalia S; Ganesh, Aravind; Greenberg, Steven; Helmer, Karl G; Hilal, Saima; Jochems, Angela C C; Jokinen, Hanna; Kuijf, Hugo; Lam, Bonnie Y K; Lebenberg, Jessica; MacIntosh, Bradley J; Maillard, Pauline; Mok, Vincent C T; Pantoni, Leonardo; Rudilosso, Salvatore; Satizabal, Claudia L; Schirmer, Markus D; Schmidt, Reinhold; Smith, Colin; Staals, Julie; Thrippleton, Michael J; van Veluw, Susanne J; Vemuri, Prashanthi; Wang, Yilong; Werring, David; Zedde, Marialuisa; Akinyemi, Rufus O; Del Brutto, Oscar H; Markus, Hugh S; Zhu, Yi-Cheng; Smith, Eric E; Dichgans, Martin; Wardlaw, Joanna M

Issue Date
2023-07
Publisher
The Lancet Publishing Group
Citation
The Lancet Neurology, Vol.22 No.7, pp.602-618
Abstract
Cerebral small vessel disease (SVD) is common during ageing and can present as stroke, cognitive decline, neurobehavioural symptoms, or functional impairment. SVD frequently coexists with neurodegenerative disease, and can exacerbate cognitive and other symptoms and affect activities of daily living. Standards for Reporting Vascular Changes on Neuroimaging 1 (STRIVE-1) categorised and standardised the diverse features of SVD that are visible on structural MRI. Since then, new information on these established SVD markers and novel MRI sequences and imaging features have emerged. As the effect of combined SVD imaging features becomes clearer, a key role for quantitative imaging biomarkers to determine sub-visible tissue damage, subtle abnormalities visible at high-field strength MRI, and lesion-symptom patterns, is also apparent. Together with rapidly emerging machine learning methods, these metrics can more comprehensively capture the effect of SVD on the brain than the structural MRI features alone and serve as intermediary outcomes in clinical trials and future routine practice. Using a similar approach to that adopted in STRIVE-1, we updated the guidance on neuroimaging of vascular changes in studies of ageing and neurodegeneration to create STRIVE-2.
ISSN
1474-4422
URI
https://hdl.handle.net/10371/205246
DOI
https://doi.org/10.1016/S1474-4422(23)00131-X
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  • Department of Medicine
Research Area 뇌경색, 뇌졸중, 혈관성 인지장애 및 치매

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