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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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Nonlinear DeltaR*2 effects in perfusion quantification using bolus-tracking MRI.

Fernando Calamante¹, Alan Connelly, Matthias J P van Osch

¹Brain Research Institute, Melbourne, Australia. fercala@brain.org.au

Magnetic Resonance in Medicine

|January 24, 2009

Summary

This summary is machine-generated.

The linear assumption in perfusion MRI causes significant errors in contrast agent concentration. Using a quadratic model greatly reduces these errors, improving quantification for brain disease assessment like acute stroke.

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Area of Science:

Medical Imaging
Biophysics
Neuroscience

Background:

Dynamic susceptibility contrast MRI estimates contrast agent concentration from DeltaR*2 changes.
The linear relationship between contrast agent concentration and DeltaR*2 in arterial blood is a common but invalid assumption.
This invalid assumption introduces significant errors in perfusion measurements.

Purpose of the Study:

To characterize perfusion errors arising from the invalid linear assumption in dynamic susceptibility contrast MRI.
To evaluate the effectiveness of a quadratic model and relative quantification in reducing these errors.
To advocate for the adoption of a more accurate model for improved perfusion quantification.

Main Methods:

Characterization of perfusion errors using dynamic susceptibility contrast MRI data.
Comparison of error magnitudes between linear and quadratic models for contrast agent concentration estimation.
Assessment of error reduction through relative perfusion quantification.

Main Results:

Large perfusion errors were observed when the linear assumption was applied.
These errors were significantly dependent on the selected tissue relaxivity.
The quadratic model substantially reduced errors, with further reduction achieved using relative quantification.

Conclusions:

The linear assumption in perfusion MRI is invalid and leads to substantial errors.
A quadratic model offers improved accuracy for contrast agent concentration estimation.
Relative perfusion quantification further minimizes errors, enhancing the reliability of perfusion MRI for diagnosing brain diseases such as acute stroke.