Phase estimation for magnetic resonance imaging near metal prostheses

Philip J. Bones; Laura J. King; Rick P. Millane

doi:10.1117/12.2188662

21 September 2015 Phase estimation for magnetic resonance imaging near metal prostheses

Philip J. Bones, Laura J. King, Rick P. Millane

Author Affiliations +

Proceedings Volume 9600, Image Reconstruction from Incomplete Data VIII; 960007 (2015) https://doi.org/10.1117/12.2188662
Event: SPIE Optical Engineering + Applications, 2015, San Diego, California, United States

Abstract

Magnetic resonance imaging (MRI) has the potential to be the best technique for assessing complications in patients with metal orthopedic implants. The presence of fat can obscure definition of the other soft tissues in MRI images, so fat suppression is often required. However, the performance of existing fat suppression techniques is inadequate near implants, due to very significant magnetic field perturbations induced by the metal. The three-point Dixon technique is potentially a method of choice as it is able to suppress fat in the presence of inhomogeneities, but the success of this technique depends on being able to accurately calculate the phase shift. This is generally done using phase unwrapping and/or iterative reconstruction algorithms. Most current phase unwrapping techniques assume that the phase function is slowly varying and phase differences between adjacent points are limited to less than π radians in magnitude. Much greater phase differences can be present near metal implants. We present our experience with two phase unwrapping techniques which have been adapted to use prior knowledge of the implant. The first method identifies phase discontinuities before recovering the phase along paths through the image. The second method employs a transform to find the least squares solution to the unwrapped phase. Simulation results indicate that the methods show promise.

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Philip J. Bones, Laura J. King, and Rick P. Millane "Phase estimation for magnetic resonance imaging near metal prostheses", Proc. SPIE 9600, Image Reconstruction from Incomplete Data VIII, 960007 (21 September 2015); https://doi.org/10.1117/12.2188662

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