Assessing the Reliability of Template-Based Clustering for Tractography in Healthy Human Adults.

Front Neuroinform

Department of Medical Biophysics, Schulich School of Medicine and Dentistry, The University of Western Ontario, London, ON, Canada.

Published: February 2022

Tractography is a non-invasive technique to investigate the brain's structural pathways (also referred to as tracts) that connect different brain regions. A commonly used approach for identifying tracts is with template-based clustering, where unsupervised clustering is first performed on a template in order to label corresponding tracts in unseen data. However, the reliability of this approach has not been extensively studied. Here, an investigation into template-based clustering reliability was performed, assessing the output from two datasets: Human Connectome Project (HCP) and MyConnectome project. The effect of intersubject variability on template-based clustering reliability was investigated, as well as the reliability of both deep and superficial white matter tracts. Identified tracts were evaluated by assessing Euclidean distances from a dataset-specific tract average centroid, the volumetric overlap across corresponding tracts, and along-tract agreement of quantitative values. Further, two template-based techniques were employed to evaluate the reliability of different clustering approaches. Reliability assessment can increase the confidence of a tract identifying technique in future applications to study pathways of interest. The two different template-based approaches exhibited similar reliability for identifying both deep white matter tracts and the superficial white matter.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8891507PMC
http://dx.doi.org/10.3389/fninf.2022.777853DOI Listing

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