Literature DB >> 24753216

Fast T2 mapping with multiple echo, Caesar cipher acquisition and model-based reconstruction.

Christopher L Lankford1, Richard D Dortch, Mark D Does.   

Abstract

PURPOSE: Fast, quantitative T2 mapping is of value to both clinical and research environments. However, many protocols utilizing fast spin echo (FSE) pulse sequences contain acceleration-induced artifacts that are compounded when fitting parameter maps, especially in the presence of imperfect refocusing. This work presents a B1 -corrected, model-based reconstruction and associated Cartesian FSE phase-encode ordering that provides enhanced accuracy in T2 estimates compared with other common accelerated protocols. THEORY AND METHODS: The method, known as multiple echo, Caesar cipher acquisition and model-based reconstruction (ME-CAMBREC), directly fitted T2 , flip angle, and proton density maps on a row-by-row basis to k-space data using the extended phase graph model. Regularization was enforced in order to minimize noise amplification effects. ME-CAMBREC was evaluated in computational and physical phantoms, as well as human brain, and compared with other FSE-based T2 mapping protocols, DESPOT2, and parallel imaging acceleration.
RESULTS: In computational, phantom, and human experiments, ME-CAMBREC provided T2 maps with fewer artifacts and less or similar error compared with other methods tested at moderate-to-high acceleration factors. In vivo, ME-CAMBREC provided error rates approximately one-half those of other methods.
CONCLUSION: Directly fitting multi-echo data to k-space using the extended phase graph can increase fidelity of T2 maps significantly, especially when using an appropriate phase-encode ordering.
© 2014 Wiley Periodicals, Inc.

Entities:  

Keywords:  T2; extended phase graph; fast imaging; model-based reconstruction; nonlinear reconstruction

Mesh:

Year:  2014        PMID: 24753216      PMCID: PMC4201905          DOI: 10.1002/mrm.25221

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


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