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Magnetic Resonance Imaging of Multiple Sclerosis at 7.0 Tesla

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Convex optimized diffusion encoding (CODE) gradient waveforms for minimum echo time and bulk motion-compensated

Eric Aliotta^1,2, Holden H Wu^1,2, Daniel B Ennis^1,2

¹Department of Radiological Sciences, University of California, Los Angeles, California, USA.

Magnetic Resonance in Medicine

|February 23, 2016

Summary

This summary is machine-generated.

Convex optimized diffusion encoding (CODE) significantly enhances signal-to-noise ratio (SNR) for diffusion-weighted imaging (DWI) across brain, liver, and cardiac applications. This advanced technique also improves robustness against bulk motion in liver and heart imaging.

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Area of Science:

Magnetic Resonance Imaging
Diffusion-Weighted Imaging
Biomedical Engineering

Background:

Diffusion-weighted imaging (DWI) is crucial for assessing tissue microstructure.
Bulk motion during DWI can lead to artifacts and inaccurate measurements.
Optimizing gradient waveforms is key to improving image quality and motion robustness.

Purpose of the Study:

To evaluate convex optimized diffusion encoding (CODE) gradient waveforms.
To achieve minimum echo time and bulk motion-compensated DWI.
To assess CODE's performance in neuro, liver, and cardiac imaging.

Main Methods:

Designed diffusion-encoding gradient waveforms using the CODE framework.
Employed CODE, CODE-M1 (first moment nulled), and CODE-M1M2 (first and second moment nulled) sequences.
Acquired ADC maps in healthy subjects (n=10) and compared them to monopolar, bipolar, and motion-compensated methods.

Main Results:

CODE significantly improved SNR for neuro ADC maps compared to monopolar encoding.
CODE-M1 demonstrated lower and more spatially uniform liver ADCs with higher SNR than bipolar.
CODE-M1M2 showed lower cardiac ADCs than monopolar and higher SNR than motion-compensated methods.

Conclusions:

CODE significantly enhances SNR for ADC mapping in the brain, liver, and heart.
CODE substantially improves DWI bulk motion robustness in the liver and heart.
CODE represents a significant advancement in diffusion imaging techniques.