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09:53
Role of Diffusion MRI Tractography in Endoscopic Endonasal Skull Base Surgery
Published on: July 5, 2021
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Exploring the limits of network topology estimation using diffusion-based tractography and tracer studies in the
Kelly Shen1, Alexandros Goulas2, David S Grayson3
1Rotman Research Institute, Baycrest, Toronto, Ontario, Canada.
Neuroimage
|February 11, 2019
Summary
Noninvasive diffusion-weighted imaging (DWI) accurately estimates fiber tract strength and captures some brain connectome topology, like modularity. However, hub classification using network analysis metrics from DWI data remains inaccurate, requiring cautious interpretation.
Area of Science:
- Neuroscience
- Computational Biology
- Network Science
Background:
- Understanding brain function requires mapping structural connectivity (the connectome).
- Noninvasive diffusion-weighted imaging (DWI) is a key technique for in vivo connectome reconstruction.
- The accuracy of DWI-based connectomes for representing brain topology is not fully established.
Purpose of the Study:
- To evaluate the accuracy of DWI-based connectomes in representing the topological characteristics of structural brain networks.
- To compare DWI-derived connectome topology with data from invasive tracer studies.
Main Methods:
- Constructed macaque monkey connectomes using in vivo DWI data.
- Compared DWI-based connectomes with data from published invasive tracer studies.
- Analyzed topological properties including fiber tract strength, degree, modularity, and hub classification.
Main Results:
- DWI effectively estimated the strength of fiber tracts.
- Tractography-based connectomes accurately captured topological properties such as degree and modularity.
- Rich-club and core-periphery architectures were detectable.
- Hub classification using betweenness centrality and participation coefficient was inaccurate.
Conclusions:
- Noninvasive DWI can faithfully represent certain aspects of cortical topology.
- Network analytic measures for hub identification in DWI-based connectomes require cautious interpretation.
- DWI is a valuable tool for connectome research but has limitations in detailed network analysis.
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