Abstract #2850
Investigating the consequences for connectomic metrics of methods to correct fibre tracking biases
Chun-Hung Yeh 1 , Robert Smith 1 , Xiaoyun Liang 1 , Fernando Calamante 1,2 , and Alan Connelly 1,2
1
The Florey Institute of Neuroscience and
Mental Health, Heidelberg, Victoria, Australia,
2
Department
of Medicine, Austin Health and Northern Health,
University of Melbourne, Melbourne, Victoria, Australia
Quantification of structural connectomics based on
streamline connection density is known to be problematic
due to the fundamental limitations of diffusion MRI
tractography. This study demonstrates how common brain
network metrics of structural connectomes vary
considerably when novel streamline reconstruction
techniques such as ACT (anatomically-constrained
tractography) and SIFT (spherical-deconvolution informed
filtering of tractograms) are applied, and that a
popular heuristic correction for streamline connection
density based on length scaling is not an adequate
substitute for these methods, highlighting the necessity
for the use of such advanced reconstruction techniques
to provide connectome construction with robust and
accurate quantitative properties.
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