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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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High-resolution Functional Magnetic Resonance Imaging Methods for Human Midbrain

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Head Motion and Correction Methods in Resting-state Functional MRI.

Masami Goto¹, Osamu Abe, Tosiaki Miyati

¹School of Allied Health Sciences, Kitasato University.

Magnetic Resonance in Medical Sciences : MRMS : an Official Journal of Japan Society of Magnetic Resonance in Medicine

|December 25, 2015

Summary

This summary is machine-generated.

Head motion significantly impacts resting-state functional MRI (RS-fMRI) brain connectivity studies. While current correction methods reduce noise, they do not eliminate it, necessitating motion quantification for accurate RS-fMRI analysis.

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Area of Science:

Neuroimaging
Cognitive Neuroscience
Biomedical Engineering

Background:

Resting-state functional magnetic resonance imaging (RS-fMRI) assesses brain connectivity during rest.
Physiological noise, particularly head motion, is a significant artifact in RS-fMRI.
Previous findings indicated motion differences between groups can create spurious connectivity results.

Purpose of the Study:

To review head motion artifacts in RS-fMRI.
To examine individual and patient population differences in head motion.
To evaluate current correction methods for head motion artifacts.

Main Methods:

Literature review of studies investigating head motion in RS-fMRI.
Analysis of existing motion correction techniques (e.g., scrubbing, regional displacement interaction).
Discussion of motion quantification methods (e.g., framewise displacement).

Main Results:

Numerous motion correction methods have been developed, showing partial success in mitigating motion's influence.
No current technique completely eliminates head motion artifacts.
Head motion differences between study groups can lead to inaccurate interpretations of functional connectivity.

Conclusions:

Quantifying participant head motion during RS-fMRI acquisition is crucial.
Further development of advanced motion correction strategies is needed to improve RS-fMRI analysis accuracy.
Understanding and addressing motion artifacts are vital for reliable neuroimaging research.