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A pilot study on protocol consistency and graph metric reproducibility in microstructure-weighted connectomes.
Maddalena Cavallo1,2, Mattia Ricchi2,3,4, Aaron Axford2
1Department of Physics and Astronomy, University of Bologna, Bologna, Italy.
Scientific Reports
|February 11, 2026
Summary
Microstructure-weighted connectomes show high reproducibility for key diffusion parameters like fractional anisotropy (FA) and mean diffusivity (MD). This supports their use as reliable biomarkers for brain connectivity in neurological disorders.
Area of Science:
- Neuroimaging
- Computational Neuroscience
- Biomedical Engineering
Background:
- Microstructure-weighted connectomes integrate diffusion parameters into structural brain networks.
- These biologically-informed networks show promise in detecting neurological alterations, such as in multiple sclerosis.
- However, the reproducibility of these microstructure-weighted connectomes is not well-established.
Purpose of the Study:
- To evaluate the reproducibility of brain connectomes weighted with diffusion tensor and Bingham-NODDI parameters.
- To assess the temporal, inter-site, and inter-protocol consistency of weighting parameters and graph metrics.
- To identify reliable weighting strategies and graph metrics for microstructure-weighted connectomes.
Main Methods:
- Utilized a four-shell diffusion magnetic resonance imaging (dMRI) acquisition protocol.
- Acquired phantom and in vivo (N=4) data for reproducibility assessments.
- Calculated coefficients of variation (CVs) and Bland-Altman biases for weighting parameters and graph metrics.
Main Results:
- Fractional anisotropy (FA), mean diffusivity (MD), intra-neurite volume fraction (INVF), and intra-cellular volume fraction (ICVF) demonstrated high reproducibility (CV < 5%).
- Orientation dispersion index and beta concentration parameter showed poor reproducibility (CV > 5%) and were excluded.
- Graph metrics from FA-, MD-, and INVF-weighted connectomes were consistent, with modularity being an exception.
- Extra-cellular volume fraction (ECVF)-weighted connectomes exhibited poor reproducibility (CV > 5%, ICC < 0.5).
Conclusions:
- Microstructure-weighted connectomes, particularly those using FA, MD, and INVF, demonstrate reliable reproducibility.
- Specific weighting strategies and graph metrics are identified as having the highest consistency.
- Findings support the potential of network metrics from weighted connectomes as biomarkers for altered brain connectivity in neurological conditions.
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