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Impact of thresholding on the consistency and sensitivity of diffusion MRI‐based brain networks in patients with cerebral small vessel disease

INTRODUCTION: Thresholding of low‐weight connections of diffusion MRI‐based brain networks has been proposed to remove false‐positive connections. It has been previously established that this yields more reproducible scan–rescan network architecture in healthy subjects. In patients with brain diseas...

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Detalles Bibliográficos
Autores principales: De Brito Robalo, Bruno M., Vlegels, Naomi, Leemans, Alexander, Reijmer, Yael D., Biessels, Geert Jan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9120729/
https://www.ncbi.nlm.nih.gov/pubmed/35413156
http://dx.doi.org/10.1002/brb3.2523
Descripción
Sumario:INTRODUCTION: Thresholding of low‐weight connections of diffusion MRI‐based brain networks has been proposed to remove false‐positive connections. It has been previously established that this yields more reproducible scan–rescan network architecture in healthy subjects. In patients with brain disease, network measures are applied to assess inter‐individual variation and changes over time. Our aim was to investigate whether thresholding also achieves improved consistency in network architecture in patients, while maintaining sensitivity to disease effects for these applications. METHODS: We applied fixed‐density and absolute thresholding on brain networks in patients with cerebral small vessel disease (SVD, n = 86; ≈24 months follow‐up), as a clinically relevant exemplar condition. In parallel, we applied the same methods in healthy young subjects (n = 44; scan–rescan interval ≈4 months) as a frame of reference. Consistency of network architecture was assessed with dice similarity of edges and intraclass correlation coefficient (ICC) of edge‐weights and hub‐scores. Sensitivity to disease effects in patients was assessed by evaluating interindividual variation, changes over time, and differences between those with high and low white matter hyperintensity burden, using correlation analyses and mixed ANOVA. RESULTS: Compared to unthresholded networks, both thresholding methods generated more consistent architecture over time in patients (unthresholded: dice = .70; ICC: .70–.78; thresholded: dice = .77; ICC: .73–.83). However, absolute thresholding created fragmented nodes. Similar observations were made in the reference group. Regarding sensitivity to disease effects in patients, fixed‐density thresholds that were optimal in terms of consistency (densities: .10–.30) preserved interindividual variation in global efficiency and node strength as well as the sensitivity to detect effects of time and group. Absolute thresholding produced larger fluctuations of interindividual variation. CONCLUSIONS: Our results indicate that thresholding of low‐weight connections, particularly when using fixed‐density thresholding, results in more consistent network architecture in patients with longer rescan intervals, while preserving sensitivity to disease effects.