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Tractography passes the test: Results from the diffusion-simulated connectivity (disco) challenge
Gabriel Girard1, Jonathan Rafael-Patiño2, Raphaël Truffet3
1CIBM Center for Biomedical Imaging, Switzerland; Radiology Department, Centre Hospitalier Universitaire Vaudois and University of Lausanne, Lausanne, Switzerland; Signal Processing Laboratory (LTS5), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
The Diffusion-Simulated Connectivity (DiSCo) challenge evaluated methods for estimating brain connectivity from diffusion MRI. While methods showed high correlation with ground truth, consistent false positives and negatives were observed.
Area of Science:
- Neuroimaging
- Computational Neuroscience
- Biophysics
Background:
- Estimating structural connectivity from diffusion-weighted magnetic resonance imaging (dMRI) is complex.
- Challenges include false-positive connections and misestimated connection weights.
Purpose of the Study:
- To evaluate state-of-the-art connectivity estimation methods.
- To utilize novel large-scale numerical phantoms with known ground-truth properties.
Main Methods:
- The MICCAI-CDMRI Diffusion-Simulated Connectivity (DiSCo) challenge was conducted.
- Diffusion signals were generated using Monte Carlo simulations for numerical phantoms.
- 14 teams participated, applying their connectivity estimation methods.
Main Results:
- Participating methods demonstrated high correlations between estimated and ground-truth connectivity weights.
- Binary connectivity was accurately identified by most methods.
- Consistent false positive and false negative connections were observed across all methods.
Conclusions:
- The DiSCo challenge provided valuable data for developing and assessing connectivity estimation techniques.
- Despite limitations of numerical phantoms, the study highlights areas for improvement in dMRI-based connectivity analysis.
- Future methods need to address persistent false positive and false negative connection estimations.
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