Anatomical location of transcallosal sensorimotor fibers in the human brain: Diffusion tensor tractography study

2013 ◽  
Vol 4 (3) ◽  
Author(s):  
Jung Seo ◽  
Sung Jang

AbstractMany diffusion tensor tractography (DTT) studies have reported on the topography of transcallosal fibers (TCF). However, little detailed anatomical information on TCF that can be easily applied for clinical purposes is known. Using probabilistic DTT, we attempted to determine the anatomical location of the TCF for motor and sensory function in the human brain. A total of 51 healthy subjects were recruited for this study. Diffusion tensor images (DTIs) were obtained at 1.5 T, and four TCF for the premotor cortex (PMC), the primary motor cortex (M1) for hand and leg, and the primary somatosensory cortex (S1) were obtained using FMRIB software. Locations of the TCF were defined as the highest probabilistic location on the midsagittal slice of the corpus callosum. We measured distances between the most anterior and posterior points of the corpus callosum. The relative mean distances of the highest probabilistic location for the precentral knob PMC (Brodmann area 6 anterior to the precentral knob), hand M1, leg M1, and precentral knob S1 (postcentral gyrus posterior to the precentral knob) TCF were 48.99%, 59.78%, 67.93%, and 73,48% from the most anterior point of the CC, respectively. According to our findings, the precentral knob PMC, hand M1, leg M1, and precentral knob S1 TCF were located at the anterior body, posterior body, posterior body, and isthmus according to Witelson’s classification, respectively.

2012 ◽  
Vol 508 (1) ◽  
pp. 9-12 ◽  
Author(s):  
Sang Seok Yeo ◽  
Min Cheol Chang ◽  
Yong Hyun Kwon ◽  
Young Jin Jung ◽  
Sung Ho Jang

NeuroImage ◽  
2010 ◽  
Vol 52 (1) ◽  
pp. 20-31 ◽  
Author(s):  
Catherine Lebel ◽  
Saul Caverhill-Godkewitsch ◽  
Christian Beaulieu

2020 ◽  
Author(s):  
Zhongping Zhang ◽  
Dhanashree Vernekar ◽  
Wenshu Qian ◽  
Mina Kim

Abstract Background: To investigate the effect of using an Rician nonlocal means (NLM) filter on quantification of diffusion tensor (DT)- and diffusion kurtosis (DK)-derived metrics in various anatomical regions of the human brain and the spinal cord, when combined with a constrained linear least squares (CLLS) approach.Methods: Prospective brain data from 9 healthy subjects and retrospective spinal cord data from 5 healthy subjects from a 3T MRI scanner were included in the study. Prior to tensor estimation, registered diffusion weighted images were denoised by an optimized blockwise NLM filter with CLLS. Mean kurtosis (MK), radial kurtosis (RK), axial kurtosis (AK), mean diffusivity (MD), radial diffusivity (RD), axial diffusivity (AD) and fractional anisotropy (FA), were determined in anatomical structures of the brain and the spinal cord. DTI and DKI metrics, signal-to-noise ratio (SNR) and Chi-square values were quantified in distinct anatomical regions for all subjects, with and without Rician denoising. Results: The averaged SNR significantly increased with Rician denoising by a factor of 2 while the averaged Chi-square values significantly decreased up to 61 % in the brain and up to 43% in the spinal cord after Rician NLM filtering. In the brain, the mean MK varied from 0.70 (putamen) to 1.27 (internal capsule) while AK and RK varied from 0.58 (corpus callosum) to 0.92 (cingulum) and from 0.70 (putamen) to 1.98 (corpus callosum), respectively. In the spinal cord, FA varied from 0.78 in lateral column to 0.81 in dorsal column while MD varied from 0.91 × 10−3 mm2/s (lateral) to 0.93 × 10−3 mm2/s (dorsal). RD varied from 0.34 × 10−3 mm2/s (dorsal) to 0.38 × 10−3 mm2/s (lateral) and AD varied from 1.96 × 10−3 mm2/s (lateral) to 2.11 × 10−3 mm2/s (dorsal).Conclusions: Our results show Rician denoising NLM filter incorporated with CLLS significantly increases SNR and reduces estimation errors of DT- and KT-derived metrics, providing the reliable metrics estimation with adequate SNR levels.


2019 ◽  
Vol 18 (4) ◽  
pp. 761-769 ◽  
Author(s):  
Qing Ji ◽  
Angela Edwards ◽  
John O. Glass ◽  
Tara M. Brinkman ◽  
Zoltan Patay ◽  
...  

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