Identification of the Corticobulbar Tracts of the Tongue and Face Using Deterministic and Probabilistic DTI Fiber Tracking in Patients with Brain Tumor

Abstract

BACKGROUND AND PURPOSE The corticobulbar tract of the face and tongue, a critical white matter tract connecting the primary motor cortex and the pons, is rarely detected by deterministic DTI fiber tractography. Detection becomes even more difficult in the presence of a tumor. The purpose of this study was to compare identification of the corticobulbar tract by using deterministic and probabilistic tractography in patients with brain tumor. MATERIALS AND METHODS Fifty patients with brain tumor who underwent DTI were studied. Deterministic tractography was performed by using the fiber assignment by continuous tractography algorithm. Probabilistic tractography was performed by using a Monte Carlo simulation method. ROIs were drawn of the face and tongue motor homunculi and the pons in both hemispheres. RESULTS In all subjects, fiber assignment by continuous tractography was ineffectual in visualizing the entire course of the corticobulbar tract between the face and tongue motor cortices and the pons on either side. However, probabilistic tractography successfully visualized the corticobulbar tract from the face and tongue motor cortices in all patients on both sides. No significant difference (P < .08) was found between both sides in terms of the number of voxels or degree of connectivity. The fractional anisotropy of both the face and tongue was significantly lower on the tumor side (P < .03). When stratified by tumor type, primary-versus-metastatic tumors, no differences were observed between tracts in terms of the fractional anisotropy and connectivity values (P > .5). CONCLUSIONS Probabilistic tractography successfully reconstructs the face- and tongue-associated corticobulbar tracts from the lateral primary motor cortex to the pons in both hemispheres.

Localization of orofacial representation in the corona radiata, internal capsule and cerebral peduncle inMacaca mulatta

“…Although we found that the dorsal and ventral tracts are spatially segregated in the CR (Figure a,b), once within the superior region of the ICp these bundles overlapped extensively (Figure c). This identical fiber pattern of M1 orofacial dorsal and ventral tract segregation then IC pathway integration, as determined by MRI tractography, has been observed in the human subcortical white matter (Jenabi et al, ; Liégeois et al, ). Possibly related to the finding of merged orofacial pathways are DBS observations obtained from neurosurgical exploration of the IC at the AC‐PC level demonstrating that co‐activation of face and tongue muscle contractions occur extensively (59–62%) (Duerden et al, ).…”

“…Not surprisingly, in the CR we found fibers from the dorsal part of the M1 orofacial representation course dorsal to fibers emerging from the ventral part of the orofacial region (Figure 9a,b). Diffusion imaging observations have similarly shown segregated dorsal and ventral pathways emerging from the M1 orofacial region in the human brain (Jenabi, Peck, Young, Brennan, & Holodny, 2015;Li egeois, Tournier, Pigdon, Connelly, & Morgan, 2013). A number of relevant investigations indicate these pathways may mediate similar, but somewhat distinguishable functional properties.…”

Cerebellum and neurodegenerative diseases: Beyond conventional magnetic resonance imaging

“…Moreover, all these techniques can be analyzed with both deterministic and probabilistic fiber reconstruction models. While deterministic models reconstruct streamlines (virtual fiber tracts) taking into account the principle eigenvector of fractional anisotropy (FA) in each voxel, probabilistic models generate a connectivity map from a larger numbers of possible pathways, obtaining the probability of each voxel to be connected to another[ 66 ]. Regardless of the used approach, tractographic output can be used not only to reconstruct the spatial configuration of fiber tracts but also to measure diffusion parameters ( i.e ., FA or mean diffusivity) at voxel level.…”

Identification of Tendency to Alcohol Misuse From the Structural Brain Networks

“…The current study also corrected for eddy current using the ''eddy_correct'' function implemented in the FSL toolbox and used the FACT algorithm to reconstruct white matter fiber tracts. While the current approaches are acceptable ways to preprocess image data, future DTI studies using more upto-date preprocessing methodologies such as enabling of both eddy current-and susceptibility-induced distortion corrections (Sotiropoulos et al, 2013;Yamada et al, 2014), as well as fiber tracking by probabilistic tractography algorithm (Li et al, 2013;Jenabi et al, 2015), may outperform the current results.…”