Synopsis
"We have acquired diffusion
MRI data and now want analyze them... Help!"
Such a cry for help is often the result of
bumping into unexpected complications at the early stage of analysis when
trying to make sense of diffusion MRI data. In this talk, I will walk you
through the most common "Oops" feelings that the novice may encounter
and guide you towards the "Aha" victory moments where these issues
get resolved.
For
the starting researcher, diffusion can cause a lot of confusion. For instance,
the signal magnitude in the images is inversely related to the amount of
diffusion, that is, lower signal intensities reflect higher diffusion rates.
Another example is the existence of multiple coordinate systems: the spatial
location and the “eigen” diffusion system, which – if they are not aligned
properly – could result in exotic color-encoding schemes and/or unexpected
fiber tractography results (see Figure). In this presentation, I will show
several of such examples where things went wrong, the “Oops” moments. By
providing the necessary background information to explain these issues, I hope
the “Aha” moments will follow afterwards.
Acknowledgements
The research of A.L. is supported by VIDI Grant 639.072.411 from the
Netherlands Organisation for Scientific Research (NWO).References
Relevant background information:
* Jones DK, Leemans A. Diffusion tensor imaging. Methods Mol Biol. 2011;711:127-44.
* Tournier JD, Mori S, Leemans A. Diffusion tensor imaging and beyond. Magn Reson Med. 2011;65(6):1532-56.
* Jones DK, Knösche TR, Turner R. White matter integrity, fiber count, and other fallacies: the do's and don'ts of diffusion MRI. Neuroimage. 2013;73:239-54.
* Leemans A, Jones DK. The B-matrix must be rotated when correcting for subject motion in DTI data. Magn Reson Med. 2009;61(6):1336-49.