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Magnetic Resonance Imaging

Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...

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Correlating Behavioral Responses to fMRI Signals from Human Prefrontal Cortex: Examining Cognitive Processes Using Task Analysis

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Spin-history artifact during functional MRI: potential for adaptive correction.

Sadie E Yancey¹, David J Rotenberg, Fred Tam

¹Imaging Research, Sunnybrook Health Sciences Centre, Toronto, Ontario M4N 3M5, Canada and Department of Medical Biophysics, University of Toronto, Ontario M4N 3M5, Canada.

Medical Physics

|September 21, 2011

Summary

Adaptive correction effectively minimizes head motion artifacts in functional magnetic resonance imaging (fMRI). This technique shows promise for improving the robustness of fMRI scans, especially for patient populations sensitive to motion.

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Area of Science:

Magnetic Resonance Imaging
Neuroimaging Techniques
Biomedical Engineering

Background:

Functional magnetic resonance imaging (fMRI) is highly sensitive to head motion, which introduces artifacts.
Spin-history artifacts, caused by through-plane motion, are particularly challenging to correct with traditional postprocessing methods.

Purpose of the Study:

To quantitatively understand MRI signal behavior related to spin-history artifacts for robust adaptive correction.
To evaluate the effectiveness of adaptive correction in suppressing motion-induced artifacts in fMRI.

Main Methods:

Developed a numerical simulation to predict MRI artifact signal amplitude for various motions.
Compared simulation results with experimental data from phantom imaging at 3.0 T.
Performed human fMRI to demonstrate adaptive correction in the presence of spin-history artifacts.

Main Results:

Simulation and experimental results showed good agreement.
Artifact signal amplitude correlated linearly with motion speed, but time-courses were nonlinearly related to motion waveforms.
Adaptive correction effectively reduced spin-history artifacts and spurious activations during phantom and human fMRI.

Conclusions:

Adaptive correction, particularly with minimal lag, can significantly improve the robustness of fMRI.
This technique may broaden the applicability of fMRI to a wider range of participants, including those with difficulty remaining still.