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Optimized inversion‐prepared gradient echo imaging
Author(s) -
Kir Albert,
McMillan Alan
Publication year - 2012
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.23669
Subject(s) - imaging phantom , computer science , image quality , signal (programming language) , contrast (vision) , residual , image contrast , sensitivity (control systems) , echo (communications protocol) , algorithm , artificial intelligence , computer vision , image (mathematics) , physics , optics , computer network , programming language , electronic engineering , engineering
Purpose: To implement a method using an extended phase graph (EPG)‐based simulation to optimize inversion‐prepared gradient echo sequences with respect to signal and contrast within the shortest acquisition time. Materials and Methods: A critical issue in rapid gradient‐echo imaging is the effect of residual transverse magnetization between consecutive data acquisition windows. Various spoiling schemes have been proposed to mitigate this problem, and while spoiling is often considered to be perfect, imaging can be more truthfully described using the EPG. An EPG‐based simulation is used to analyze and predict the image signal and contrast to serve as a basis for sequence optimization. Results: Fourteen biological phantom experiments and five brain imaging experiments on each of five healthy volunteers was performed to validate and verify the accuracy of the EPG‐based simulation. In addition, two experiments on an in‐cranial cadaver brain were performed to show the ability of the proposed method for improving overall image quality. Conclusion: From the experiment results, it is demonstrated that optimization of 3D magnetization‐prepared rapid gradient‐echo imaging sequences can be performed with an EPG‐based simulation to manipulate the sequence parameters for generating images with highly specific signal and contrast characteristics for quantitative T1‐weighted human brain imaging. J. Magn. Reson. Imaging 2012;36:748–755. © 2012 Wiley Periodicals, Inc.