Systematic validation of structural brain networks in cerebral small vessel disease. Issue 6 (June 2022)

• Record Type: Journal Article
• Authors: Dewenter, Anna; Gesierich, Benno; ter Telgte, Annemieke; Wiegertjes, Kim; Cai, Mengfei; Jacob, Mina A; Marques, José P; Norris, David G; Franzmeier, Nicolai; de Leeuw, Frank-Erik; Tuladhar, Anil M; Duering, Marco
• Is Part Of: Journal of cerebral blood flow & metabolism. Volume 42:Issue 6(2022)
• Page Start: 1020
• Page End: 1032
• Publication Date: 2022-06
• Subjects: Cerebral small vessel disease -- connectome -- diffusion MRI -- network analysis -- quantitative MRI marker; Cerebral circulation -- Periodicals; Brain -- Metabolism -- Periodicals; Brain -- Blood-vessels -- Periodicals; Cerebrovascular disease -- Periodicals; 612.824
• DOI: 10.1177/0271678X211069228
• Languages: English
• ISSNs: 0271-678X

Abstract

Cerebral small vessel disease (SVD) is considered a disconnection syndrome, which can be quantified using structural brain network analysis obtained from diffusion MRI. Network analysis is a demanding analysis approach and the added benefit over simpler diffusion MRI analysis is largely unexplored in SVD. In this pre-registered study, we assessed the clinical and technical validity of network analysis in two non-overlapping samples of SVD patients from the RUN DMC study (n = 52 for exploration and longitudinal analysis and n = 105 for validation). We compared two connectome pipelines utilizing single-shell or multi-shell diffusion MRI, while also systematically comparing different node and edge definitions. For clinical validation, we assessed the added benefit of network analysis in explaining processing speed and in detecting short-term disease progression. For technical validation, we determined test-retest repeatability. Our findings in clinical validation show that structural brain networks provide only a small added benefit over simpler global white matter diffusion metrics and do not capture short-term disease progression. Test-retest reliability was excellent for most brain networks. Our findings question the added value of brain network analysis in clinical applications in SVD and highlight the utility of simpler diffusion MRI based markers.