The Cerebral Vascular Enhancement Effect in Establishing Diffusion Tensor Imaging Protocols

The focus of this paper is to investigate the significance of the cerebral vascular enhancement effect on diffusion tensor imaging (DTI) datasets and in establishing appropriate DTI imaging protocols. Two DTI scans are performed on each subject during the same imaging session. Between DTI scans, 22 minutes of a visual tracking experiment and 3 minutes of an alternating breath hold experiment are performed. These functional tasks, in particular the breath hold task, increase the blood flow and volume to study the vascular enhancement between the two DTI scans. Data collected from four healthy control subjects are analyzed in DTI Studio and quantified using fractional anisotropy. ROIs were selected in close proximity to the blood supply from three main cerebral arteries (posterior, middle, and anterior). Preliminary results suggest that there is a significant cerebral vascular enhancement effect between a DTI scan performed at the beginning of the experiment versus a DTI scan performed at the end of the experiment.

[1]  Mark D'Esposito,et al.  Variation of BOLD hemodynamic responses across subjects and brain regions and their effects on statistical analyses , 2004, NeuroImage.

[2]  Susumu Mori,et al.  Fiber tracking: principles and strategies – a technical review , 2002, NMR in biomedicine.

[3]  R. Buxton,et al.  A Model for the Coupling between Cerebral Blood Flow and Oxygen Metabolism during Neural Stimulation , 1997, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[4]  M. Alexander,et al.  Principles of Neural Science , 1981 .

[5]  E. Ritenour,et al.  Medical Imaging Physics , 1992 .

[6]  R. Buxton,et al.  Dynamics of blood flow and oxygenation changes during brain activation: The balloon model , 1998, Magnetic resonance in medicine.

[7]  G. Bruce Pike,et al.  Origins of the BOLD post-stimulus undershoot , 2009, NeuroImage.

[8]  Ching-Po Lin,et al.  Validation of Diffusion Tensor Magnetic Resonance Axonal Fiber Imaging with Registered Manganese-Enhanced Optic Tracts , 2001, NeuroImage.

[9]  F. Hillary,et al.  The Influence of Neuropathology on the fMRI Signal: A Measurement of Brain or Vein? , 2007, The Clinical neuropsychologist.

[10]  Hangyi Jiang,et al.  DtiStudio: Resource program for diffusion tensor computation and fiber bundle tracking , 2006, Comput. Methods Programs Biomed..

[11]  B. Min,et al.  Cerebral Lateralization Index Based on Intensity of Bold Signal of FMRI , 2008, The International journal of neuroscience.

[12]  K. Uğurbil,et al.  Effect of Basal Conditions on the Magnitude and Dynamics of the Blood Oxygenation Level-Dependent fMRI Response , 2002, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[13]  R. Traystman Regulation of Cerebral Blood Flow by Carbon Dioxide , 1997 .