ITHM fMRI

Slide2: 

Phase Encode (applied before readout) Frequency Encode (applied at time of readout)

Slide3: 

Phase differences imposed by the applied gradients are systematic. Phase differences due to T2 and T2* induced inhomogeneities are randomly distributed, greater and less than the imposed phase. The net phase of the MRI signal measured at a voxel is the same as that imposed by the applied gradient, but the magnitude is reduced because of the partial cancellation.

The Need for Speed…: 

The Need for Speed… understand k-space. understand how to move around k-space What do we need to cover all of k-space in a single TR?

Slide6: 

Any function(image) in space or time can be approximated by a sum of sinusoidal functions http://www.jhu.edu/~signals/fourier2/index.html

The more high frequency components you add to the equation, the more sharp changes you can fit: 

The more high frequency components you add to the equation, the more sharp changes you can fit http://www.jhu.edu/~signals/fourier2/index.html

Signals that change rapidly require more high frequency components to adequately describe: 

Signals that change rapidly require more high frequency components to adequately describe http://www.jhu.edu/~signals/fourier2/index.html

Signals that change rapidly require more high frequency components to adequately describe: 

http://www.jhu.edu/~signals/fourier2/index.html Signals that change rapidly require more high frequency components to adequately describe

Signals that change rapidly require more high frequency components to adequately describe: 

http://www.jhu.edu/~signals/fourier2/index.html Signals that change rapidly require more high frequency components to adequately describe

Slide11: 

Any function(image) in space or time can be approximated by a sum of sinusoidal functions http://www.jhu.edu/~signals/fourier2/index.html

Slide12: 

Low frequencies are at the center of k-space

Slide13: 

Any function(image) in space or time can be approximated by a sum of sinusoidal functions http://www.jhu.edu/~signals/fourier2/index.html

Slide14: 

MRI data is collected in “K-space” And then transformed (Fourier) into a spatial image SEE ALSO http://www.revisemri.com/tools/kspace/index.htm

Slide17: 

Typical path through k-space for anatomical MRI

Slide18: 

Another Nobel Prize winning invention: Echo Planar Imaging

Slide21: 

Typical path through k-space for anatomical MRI

Slide22: 

Another Nobel Prize winning invention: Echo Planar Imaging

T1 vs. T2: 

T1 vs. T2 Source: Mark Cohen’s web slides Weighting T1 or T2 or T2* means you have maximized the contrast between tissues according to that property and minimized contrast according to other properties MRI signal magnitude is a function of both the T1 and T2 properties of the tissue at that location

Slide27: 

T1 T2

But why would they get out of phase?: 

But why would they get out of phase? Because the magnetic field is not the same strength everywhere. It varies on both a macroscopic and microscopic scale. f = Bo T2 depends on the microscopic variations (due to chemical bonds, molecular structure, etc) T2* depends on the macroscopic variations (due to tissue density, hemoglobin state, etc)

Slide29: 

BOLD fMRI: Blood Oxygen Level Dependent

fMRI and the BOLD Response: 

Localized Change in Neural Activity Local Increased Oxygen Consumption Local Increased Blood Flow Local Decrease in Deoxyhemoglobin More Uniform Local Magnetic Field Local Increase in MRI signal fMRI and the BOLD Response

Sensitizing MRI to Blood Flow Changes: 

Sensitizing MRI to Blood Flow Changes Kwong, et al., Proc. Natl. Acad. Sci. (USA) 89:5675 (1992).