Quantification of track-weighted imaging (TWI): characterisation of within-subject reproducibility and between-subject variability.
Recently several novel image contrasts derived from whole-brain fibre tracking-data (tractograms) have been introduced. The novel contrasts of these track-weighted imaging (TWI) methods may provide important information for clinical neuroscience studies. However, before they can be used reliably to generate quantitative measures, it is important to characterise their within-subject reproducibility, and between-subject variability. In this work we compute the within-subject reproducibility (intra-scan, intra-session and inter-session), and between-subject variability of TWI for a number of different TWI contrasts across multiple subjects. The results are used in simple voxel-wise power calculations within illustrative regions of interest to provide guidelines for required sample sizes and observable effect sizes for individual subjects and between groups. It was found that the required sample sizes and observable effect sizes varied considerably between different TWI maps and for different ROIs. For some TWI contrast and ROI combinations, the power calculations yielded clinically practical values. These results provide important information concerning the potential usefulness and sensitivity of TWI maps for individual diagnosis, longitudinal studies and group comparisons, as well as for study designs.
Brain Research Institute, Florey Institute of Neuroscience and Mental Health, Heidelberg, Victoria, Australia.
Lisa
L
Willats
Brain Research Institute, Florey Institute of Neuroscience and Mental Health, Heidelberg, Victoria, Australia.
David
D
Raffelt
Brain Research Institute, Florey Institute of Neuroscience and Mental Health, Heidelberg, Victoria, Australia; Department of Medicine, Austin Health and Northern Health, University of Melbourne, Melbourne, Victoria, Australia.
Robert E
RE
Smith
Brain Research Institute, Florey Institute of Neuroscience and Mental Health, Heidelberg, Victoria, Australia; Department of Medicine, Austin Health and Northern Health, University of Melbourne, Melbourne, Victoria, Australia.
J-Donald
JD
Tournier
Brain Research Institute, Florey Institute of Neuroscience and Mental Health, Heidelberg, Victoria, Australia; Department of Medicine, Austin Health and Northern Health, University of Melbourne, Melbourne, Victoria, Australia.
Alan
A
Connelly
Brain Research Institute, Florey Institute of Neuroscience and Mental Health, Heidelberg, Victoria, Australia; Department of Medicine, Austin Health and Northern Health, University of Melbourne, Melbourne, Victoria, Australia. Electronic address: fercala@brain.org.au.
Fernando
F
Calamante
D000328:Adult; D000465:Algorithms; D001921:Brain; D001931:Brain Mapping / Q000379:methods*; D056324:Diffusion Tensor Imaging / Q000379:methods*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008297:Male; D015203:Reproducibility of Results
2nd order integration over fibre orientation distributions fibre-tracking algorithm; ADC; AFD; APM; BS; CSD; CV; DWI; Diffusion MRI; EPI; FA; FOD; FWHM; Fibre-tracking; HARDI; PC; ROI; Reproducibility; Super-resolution; TDI; TE; TR; TW; TWI; Track-density imaging; Track-weighted imaging; WM; WS; apparent diffusion coefficient; apparent fibre density; average pathlength mapping; between-subject; coefficient of variation; constrained spherical deconvolution; diffusion weighted imaging; echo time; echo-planar imaging; fibre orientation distribution; fractional anisotropy; full-width at half-maximum; high angular resolution diffusion imaging; iFOD2; percentage change; region of interest; repetition time; track-density imaging; track-weighted; track-weighted imaging; white matter; within-subject