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Joint estimation of chemical shift and quantitative susceptibility mapping (chemical QSM).


ABSTRACT: The purpose of this work is to address the unsolved problem of quantitative susceptibility mapping (QSM) of tissue with fat where both fat and susceptibility change the MR signal phase.The chemical shift of fat was treated as an additional unknown and was estimated jointly with susceptibility to provide the best data fitting using an automated and iterative algorithm. A simplified susceptibility model was used to calculate an updated value of the chemical shift based on the local magnetic field in each iteration. Numerical simulation, phantom experiments and in vivo imaging were performed. Artifacts were assessed by measuring the susceptibility variance in uniform regions. Accuracy was assessed by comparison with ground truth in simulation, and using a susceptibility matching approach in phantom.Using the proposed method, artifacts on the QSM image were markedly suppressed in all tested datasets compared with results generated using fixed chemical shifts. Accuracy of the estimated susceptibility was also improved in numerical simulation and phantom experiments.A joint estimation of fat content and magnetic susceptibility using an iterative chemical shift update was shown to improve image quality and accuracy on QSM images.

SUBMITTER: Dimov AV 

PROVIDER: S-EPMC4874185 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature

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Joint estimation of chemical shift and quantitative susceptibility mapping (chemical QSM).

Dimov Alexey V AV   Liu Tian T   Spincemaille Pascal P   Ecanow Jacob S JS   Tan Huan H   Edelman Robert R RR   Wang Yi Y  

Magnetic resonance in medicine 20140619 6


<h4>Purpose</h4>The purpose of this work is to address the unsolved problem of quantitative susceptibility mapping (QSM) of tissue with fat where both fat and susceptibility change the MR signal phase.<h4>Theory and methods</h4>The chemical shift of fat was treated as an additional unknown and was estimated jointly with susceptibility to provide the best data fitting using an automated and iterative algorithm. A simplified susceptibility model was used to calculate an updated value of the chemic  ...[more]

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