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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
by
Vlegels, Naomi
, De Brito Robalo, Bruno M.
, Leemans, Alexander
, Biessels, Geert Jan
, Reijmer, Yael D.
in
Algorithms
/ Alzheimer's disease
/ cerebral small vessel disease
/ Datasets
/ diffusion tensor imaging
/ Magnetic resonance imaging
/ network density
/ network reproducibility
/ network thresholding
/ Original
/ Patients
/ Reproducibility
/ Software
/ Transient ischemic attack
/ Young adults
2022
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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
by
Vlegels, Naomi
, De Brito Robalo, Bruno M.
, Leemans, Alexander
, Biessels, Geert Jan
, Reijmer, Yael D.
in
Algorithms
/ Alzheimer's disease
/ cerebral small vessel disease
/ Datasets
/ diffusion tensor imaging
/ Magnetic resonance imaging
/ network density
/ network reproducibility
/ network thresholding
/ Original
/ Patients
/ Reproducibility
/ Software
/ Transient ischemic attack
/ Young adults
2022
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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
by
Vlegels, Naomi
, De Brito Robalo, Bruno M.
, Leemans, Alexander
, Biessels, Geert Jan
, Reijmer, Yael D.
in
Algorithms
/ Alzheimer's disease
/ cerebral small vessel disease
/ Datasets
/ diffusion tensor imaging
/ Magnetic resonance imaging
/ network density
/ network reproducibility
/ network thresholding
/ Original
/ Patients
/ Reproducibility
/ Software
/ Transient ischemic attack
/ Young adults
2022
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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
Journal Article
Impact of thresholding on the consistency and sensitivity of diffusion MRI‐based brain networks in patients with cerebral small vessel disease
2022
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Overview
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. In this study, we investigated whether thresholding methods that have been shown to improve scan–rescan reproducibility of diffusion‐based brain networks in healthy young subjects are also applicable to datasets of elderly patients with brain pathology, scanned over much longer time frames. We examined whether thresholding achieves improved consistency in network architecture, while maintaining sensitivity to biological effects in patients with cerebral small vessel disease.
Publisher
John Wiley & Sons, Inc,John Wiley and Sons Inc,Wiley
Subject
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