TY - JOUR
T1 - Systematic validation of structural brain networks in cerebral small vessel disease
AU - Dewenter, Anna
AU - Gesierich, Benno
AU - ter Telgte, Annemieke
AU - Wiegertjes, Kim
AU - Cai, Mengfei
AU - Jacob, Mina A.
AU - Marques, José P.
AU - Norris, David G.
AU - Franzmeier, Nicolai
AU - de Leeuw, Frank Erik
AU - Tuladhar, Anil M.
AU - Duering, Marco
N1 - Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Mengfei Cai was supported by the China Scholarship Council (201706100189). Nicolai Franzmeier was supported by the Hertie Foundation for clinical neurosciences.
Publisher Copyright:
© The Author(s) 2021.
PY - 2022/6/1
Y1 - 2022/6/1
N2 - 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.
AB - 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.
KW - Cerebral small vessel disease
KW - connectome
KW - diffusion MRI
KW - network analysis
KW - quantitative MRI marker
UR - http://www.scopus.com/inward/record.url?scp=85121723959&partnerID=8YFLogxK
U2 - 10.1177/0271678X211069228
DO - 10.1177/0271678X211069228
M3 - Article
AN - SCOPUS:85121723959
SN - 0271-678X
VL - 42
SP - 1020
EP - 1032
JO - Journal of Cerebral Blood Flow and Metabolism
JF - Journal of Cerebral Blood Flow and Metabolism
IS - 6
ER -