期刊
NEUROIMAGE
卷 47, 期 -, 页码 T98-T106出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2008.06.034
关键词
Two-tensor tractography; Diffusion tensor imaging; Crossing fibers; Corticospinal tract
资金
- NCI NIH HHS [R25 CA089017] Funding Source: Medline
- NCRR NIH HHS [U41 RR019703-045853, P41 RR013218, U41 RR019703-01A29003, P41-RR13218, U41 RR019703, U41 RR019703-028713, U41 RR019703-037948, U41-RR019703] Funding Source: Medline
- NIMH NIH HHS [R03 MH076012, R01 MH074794, R01-MH074794] Funding Source: Medline
- NINDS NIH HHS [K08 NS048063-05, K08 NS048063] Funding Source: Medline
An inherent drawback of the traditional diffusion tensor model is its limited ability to provide detailed information about multidirectional fiber architecture within a voxel. This leads to erroneous fiber tractography results in locations where fiber bundles cross each other. This may lead to the inability to visualize clinically important tracts such as the lateral projections of the corticospinal tract. In this report, we present a deterministic two-tensor extended Streamline Tractography (XST) technique, which successfully traces through regions of crossing fibers. We evaluated the method on simulated and in vivo human brain data, comparing the results with the traditional single-tensor and with a probabilistic tractography technique. By tracing the corticospinal tract and correlating with fMRI-determined motor cortex in both healthy subjects and patients with brain tumors, we demonstrate that two-tensor deterministic streamline tractography can accurately identify fiber bundles consistent with anatomy and previously not detected by conventional single-tensor tractography. When compared to the dense connectivity maps generated by probabilistic tractography, the method is computationally efficient and generates discrete geometric pathways that are simple to visualize and clinically useful. Detection of crossing white matter pathways can improve neurosurgical visualization of functionally relevant white matter areas. (C) 2008 Elsevier Inc. All rights reserved.
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