Diffusion Tensor Imaging and Tractography
The Neurosurgical arm of the NCIGT is making strides in delineating the tracts of the human brain through tractography generated through diffusion tensor imaging (DTI) techniques. Eventually, through tractography, we will be able to align anatomical understanding of brain tracts with an understanding of their functional activation through knowledge from fMRI.
The NCIGT's tractography efforts to date are now being translated into its surgical navigation software platform, 3D Slicer, to enable multiple types of displays of these views of the brain during operations. Efforts with international collaborators are underway to extract and make viewable the full extent of the cortical spinal tract by using diffusion imaging data to perform two-tensor tractography, a method developed within the NCIGT. Also underway is research work on measuring the influence of tumors on the corticalspinal tract and motor function in patients using DTI tractography as well as two-tensor and stochastic tractography methods.
A recent milestone met by the Core was the development of a quantitative model of the biological source of the DTI signal. The more that is understood about the source of the DTI signal captured through MRI, the more that can be determined about neural water diffusion and tissue characteristics to improve our 3D understanding of brain anatomy.
New DTI methods also include estimating, from MRI scans of the brain, the restricted water in brain tissue from high b-value data so as to make decisions before surgery about what tissue is healthy, tumor or edematous. Used already, prior to surgery, with MRI scans of patients with brain tumors, a fast, high b-value, clinical DTI scan protocol yielded the restricted water fraction. NCIGT researchers theorize that in areas of suspected edema around tumors, if a population of restricted water still exists, some brain tissue may still be viable. An abstract of this work shows images of the scans following analysis.
Recently an automatic method was introduced called tract-based morphometry, or TBM, for the measurement and analysis of diffusion MRI data along white matter fiber tracts. Using subject-specific tractography bundle segmentations, we generate an arc length parameterization of the bundle with point correspondences across all fibers and all subjects, allowing tract-based measurement and analysis. The TBM approach brings analysis of DTI data into the clinically and neuroanatomically relevant framework of tract anatomy.
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Publications
- O'Donnell L, Westin C, Golby A. Tract-based morphometry for white matter group analysis. Neuroimage. 2009 Apr 15;45(3):832-44. PMID: 19154790.
- Voineskos A, O'Donnell L, Lobaugh N, Markant D, Ameis S, Niethammer M, Mulsant B, Pollock B, Kennedy J, Westin C, Shenton M. Quantitative examination of a novel clustering method using magnetic resonance diffusion tensor tractography. Neuroimage. 2009 Apr 1;45(2):370-6. PMID: 19159690. PMCID: PMC2646811.
- Dauguet J, Peled S, Berezovskii V, Delzescaux T, Warfield S, Born R, Westin C. Comparison of fiber tracts derived from in-vivo DTI tractography with 3D histological neural tract tracer reconstruction on a macaque brain. Neuroimage. 2007 Aug 15;37(2):530-8. PMID: 17604650.
- Peled S. New perspectives on the sources of white matter DTI signal. IEEE Trans Med Imaging. 2007 Nov;26(11):1448-55. PMID: 18041260.
- O'Donnell L, Westin C, Golby A. Tract-Based Morphometry. Int Conf Med Image Comput Comput Assist Interv. 2007;10(Pt 2):161-168. PMID: 18044565.
- Peled S, Friman O, Jolesz F, Westin CF. Geometrically constrained two-tensor model for crossing tracts in DWI. Magn Reson Imaging. 2006 Nov;24(9):1263-70. PMID: 17071347.
Involved Research Investigators
- Alexandra Golby, PI (Golby Lab)
- Sharon Peled, PhD
- Carl-Fredrik Westin, PhD
- Lauren O’Donnell, PhD
- Isaiah Norton
- Haiying Liu, MEng, MSc