Paper
9 March 2017 Stability of gradient field corrections for quantitative diffusion MRI
Baxter P. Rogers, Justin Blaber, E. Brian Welch, Zhaohua Ding, Adam W. Anderson, Bennett A. Landman
Author Affiliations +
Abstract
In magnetic resonance diffusion imaging, gradient nonlinearity causes significant bias in the estimation of quantitative diffusion parameters such as diffusivity, anisotropy, and diffusion direction in areas away from the magnet isocenter. This bias can be substantially reduced if the scanner- and coil-specific gradient field nonlinearities are known. Using a set of field map calibration scans on a large (29 cm diameter) phantom combined with a solid harmonic approximation of the gradient fields, we predicted the obtained b-values and applied gradient directions throughout a typical field of view for brain imaging for a typical 32-direction diffusion imaging sequence. We measured the stability of these predictions over time. At 80 mm from scanner isocenter, predicted b-value was 1-6% different than intended due to gradient nonlinearity, and predicted gradient directions were in error by up to 1 degree. Over the course of one month the change in these quantities due to calibration-related factors such as scanner drift and variation in phantom placement was <0.5% for b-values, and <0.5 degrees for angular deviation. The proposed calibration procedure allows the estimation of gradient nonlinearity to correct b-values and gradient directions ahead of advanced diffusion image processing for high angular resolution data, and requires only a five-minute phantom scan that can be included in a weekly or monthly quality assurance protocol.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Baxter P. Rogers, Justin Blaber, E. Brian Welch, Zhaohua Ding, Adam W. Anderson, and Bennett A. Landman "Stability of gradient field corrections for quantitative diffusion MRI", Proc. SPIE 10132, Medical Imaging 2017: Physics of Medical Imaging, 101324X (9 March 2017); https://doi.org/10.1117/12.2254609
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Cited by 7 scholarly publications.
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KEYWORDS
Diffusion

Calibration

Scanners

Diffusion magnetic resonance imaging

Magnetic resonance imaging

Solids

Brain mapping

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