Abstract
There are many approaches for extracting useful visual and quantitative information from diffusion MRI imaging data reconstructed using the diffusion tensor imaging (DTI) method, including whole-brain, regional, and voxel-based approaches. However, the broad range of analysis approaches available and heterogeneous functionality in software tools developed to apply them make analyzing and interpreting DTI data particularly challenging.
This chapter provides an overview of the major DTI analysis techniques, including region-of-interest, tractography, and voxel-based analysis (VBA), as well as their strengths and weaknesses. Additionally, the chapter provides practical guidance on considerations that should be taken into account when choosing how to analyze DTI data, supported by a visual decision scheme and software checklist.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Soares JM, Marques P, Alves V, Sousa N. A hitchhiker’s guide to diffusion tensor imaging. Front Neurosci. 2013;7:31.
Mukherjee P, Berman JI, Chung SW, Hess CP, Henry RG. Diffusion tensor MR imaging and fiber tractography: theoretic underpinnings. AJNR Am J Neuroradiol. 2008;29(4):632–41.
Jones DK, Cercignani M. Twenty-five pitfalls in the analysis of diffusion MRI data. NMR Biomed. 2010;23(7):803–20.
Jbabdi S, Johansen-Berg H. Tractography: where do we go from here? Brain Connect. 2011;1(3):169–83.
Van Hecke W, Leemans A, Sage CA, Emsell L, Veraart J, Sijbers J, et al. The effect of template selection on diffusion tensor voxel-based analysis results. Neuroimage. 2011;55(2):566–73.
Burgel U, Madler B, Honey CR, Thron A, Gilsbach J, Coenen VA. Fiber tracking with distinct software tools results in a clear diversity in anatomical fiber tract portrayal. Cent Eur Neurosurg. 2009;70(1):27–35.
Suggested Reading
Jones DK, Knösche TR, Turner R. White matter integrity, fibre count, and other fallacies: the do’s and don’ts of diffusion MRI. NeuroImage. 2013;73:239–54.
Cercignani M. Ch 29: Strategies for patient-control comparison of diffusion MRI Data. In: Jones DK, editor. Diffusion MRI: theory, methods & applications. New York, NY: Oxford University Press; 2010. p. 485–99.
Acknowledgments
We would like to thank Ann Van De Winckel, Thibo Billiet, Alexander Leemans, and Dirk Smeets for providing us with some of the images and data sets that were used to create the figures in this chapter.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer Science+Business Media New York
About this chapter
Cite this chapter
Van Hecke, W., Emsell, L. (2016). Strategies and Challenges in DTI Analysis. In: Van Hecke, W., Emsell, L., Sunaert, S. (eds) Diffusion Tensor Imaging. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-3118-7_8
Download citation
DOI: https://doi.org/10.1007/978-1-4939-3118-7_8
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4939-3117-0
Online ISBN: 978-1-4939-3118-7
eBook Packages: MedicineMedicine (R0)