16 research outputs found
Diffusion Imaging in the Rat Cervical Spinal Cord
Magnetic resonance imaging (MRI) is the state of the art approach for assessing the status of the spinal cord noninvasively, and can be used as a diagnostic and prognostic tool in cases of disease or injury. Diffusion weighted imaging (DWI), is sensitive to the thermal motion of water molecules and allows for inferences of tissue microstructure. This report describes a protocol to acquire and analyze DWI of the rat cervical spinal cord on a small-bore animal system. It demonstrates an imaging setup for the live anesthetized animal and recommends a DWI acquisition protocol for high-quality imaging, which includes stabilization of the cord and control of respiratory motion. Measurements with diffusion weighting along different directions and magnitudes (b-values) are used. Finally, several mathematical models of the resulting signal are used to derive maps of the diffusion processes within the spinal cord tissue that provide insight into the normal cord and can be used to monitor injury or disease processes noninvasively.
The video component of this article can be found at http://www.jove.com/video/52390/ Introduction Magneti
Off-resonance and detuned surface coils for Bâ inhomogeneity in 7-Tesla MRI
Thesis (S.B.)--Massachusetts Institute of Technology, Dept. of Nuclear Science and Engineering, 2006."June 2006."Includes bibliographical references (p. [34]).A problem with high-field MRI is the lack of B1 homogeneity, particularly signal cancellation in the outer parts of the head. Here we attempt to correct this by adding surface coils. To adjust the mutual coupling, we vary the resonance properties of the added coil. A new agar-based head phantom was built, and two surface coils were built and tuned. The surface coils were placed in various configurations against the phantom to modify the B1 field with their presence, while images were taken using a 16-rung birdcage coil to transmit and receive. Trials were taken with various spacings between the surface coil and the phantom, while the resonance of the surface coil was either shifted in frequency by changing the voltage across a varactor diode, or detuned using a resonant detuning circuit. It was discovered that with a 1 cm spacing and a surface coil tuned just above resonance, SNR near the surface coil could be improved by upwards of 400%, with the trade-off of a reduced signal in other areas on the periphery of the head. Other configurations could achieve better B1 homogeneity at the expense of reduced SNR throughout the head. Future studies will explore the possibility of using more than one surface coil to improve SNR in more places on the periphery of the head.by Elizabeth K. Zakszewski.S.B
A diffusion-tensor-based white matter atlas for rhesus macaques.
Atlases of key white matter (WM) structures in humans are widely available, and are very useful for region of interest (ROI)-based analyses of WM properties. There are histology-based atlases of cortical areas in the rhesus macaque, but none currently of specific WM structures. Since ROI-based analysis of WM pathways is also useful in studies using rhesus diffusion tensor imaging (DTI) data, we have here created an atlas based on a publicly available DTI-based template of young rhesus macaques. The atlas was constructed to mimic the structure of an existing human atlas that is widely used, making results translatable between species. Parcellations were carefully hand-drawn on a principle-direction color-coded fractional anisotropy image of the population template. The resulting atlas can be used as a reference to which registration of individual rhesus data can be performed for the purpose of white-matter parcellation. Alternatively, specific ROIs from the atlas may be warped into individual space to be used in ROI-based group analyses. This atlas will be made publicly available so that it may be used as a resource for DTI studies of rhesus macaques
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A coronal slice of the WM atlas.
<p>Overlaid on a T1-W template (left) and an FA color map (right). AT-WMâ=âadjacent thalamus, BCCâ=âbody of corpus callosum, CgCâ=âsuperior cingulum bundle, CgHâ=âperihippocampal cingulum tract, CPâ=âcerebral peduncle, CSTâ=âcorticospinal tract, DPCRâ=âdorsal posterior corona radiata, ECâ=âexternal capsule, FXâ=âfornix, MCPâ=âmiddle cerebellar peduncle, SCRâ=âsuperior corona radiata, SLFâ=âsuperior longitudinal fasciculus, SSâ=âsagittal striatum, STâ=âstria terminalus.</p
Image showing overlap between manual (blue) and automatic (red) methods of defining tracts.
<p>Manual definitions of the corpus callosum and ALIC (anterior limb of the internal capsule (A, C) and the PTR (posterior thalamic radiation) (B, D) were drawn on the different template and compared to automatically defined regions. Overlap agreement appears in purple. Slices were selected that illustrated areas where the two segmentation methods disagreed.</p
Short range WM regions in top and left view.
<p>Short range WM regions in top and left view.</p
A sagittal slice of the WM atlas.
<p>Overlaid on a T1-W template. ACâ=âanterior commissure, AT-WMâ=âadjacent thalamus, AA-WMâ=âadjacent amygdala, ALICâ=âanterior limb of the internal capsule, BCCâ=âbody of corpus callosum, CgHâ=âperihippocampal cingulum tract, CPâ=âcerebral peduncle, CSTâ=âcorticospinal tract, DPCRâ=âdorsal posterior corona radiata, DPFâ=âdorsal prefrontal, FXâ=âfornix, GCCâ=âgenu of corpus callosum, ICPâ=âinferior cerebellar peduncle, MB-WMâ=âmidbrain, MCPâ=âmiddle cerebellar peduncle, OCâ=âolivocerebellar tract, PLICâ=âposterior limb of the internal capsule, SCCâ=âsplenium of corpus callosum, STâ=âstria terminalis, UNCâ=âuncinate fasciculus.</p