Literature DB >> 31429994

In-phase zero TE musculoskeletal imaging.

Mathias Engström1, Graeme McKinnon2, Cristina Cozzini3, Florian Wiesinger3.   

Abstract

PURPOSE: To introduce a new method for in-phase zero TE (ipZTE) musculoskeletal MR imaging.
METHODS: ZTE is a 3D radial imaging method, which is sensitive to chemical shift off-resonance signal interference, especially around fat-water tissue interfaces. The ipZTE method addresses this fat-water chemical shift artifact by acquiring each 3D radial spoke at least twice with varying readout gradient amplitude and hence varying effective sampling time. Using k-space-based chemical shift decomposition, the acquired data is then reconstructed into an in-phase ZTE image and an out-of-phase disturbance.
RESULTS: The ipZTE method was tested for knee, pelvis, brain, and whole-body. The obtained images demonstrate exceptional soft-tissue uniformity free from out-of-phase disturbances apparent in the original ZTE images. The chemical shift decomposition was found to improve SNR at the cost of reduced image resolution.
CONCLUSION: The ipZTE method can be used as an averaging mechanism to eliminate fat-water chemical shift artifacts and improve SNR. The method is expected to improve ZTE-based musculoskeletal imaging and pseudo CT conversion as required for PET/MR attenuation correction and MR-guided radiation therapy planning.
© 2019 International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  ZTE; artifact; chemical shift; correction; in-phase; musculoskeletal

Year:  2019        PMID: 31429994     DOI: 10.1002/mrm.27928

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


  3 in total

1.  Qualitative and quantitative analysis of 3D T1 Silent imaging.

Authors:  Francesca Di Giuliano; Silvia Minosse; Eliseo Picchi; Valentina Ferrazzoli; Valerio Da Ros; Massimo Muto; Chiara Adriana Pistolese; Francesco Garaci; Roberto Floris
Journal:  Radiol Med       Date:  2021-06-15       Impact factor: 3.469

2.  Unsupervised-learning-based method for chest MRI-CT transformation using structure constrained unsupervised generative attention networks.

Authors:  Hidetoshi Matsuo; Mizuho Nishio; Munenobu Nogami; Feibi Zeng; Takako Kurimoto; Sandeep Kaushik; Florian Wiesinger; Atsushi K Kono; Takamichi Murakami
Journal:  Sci Rep       Date:  2022-06-30       Impact factor: 4.996

3.  Motion corrected silent ZTE neuroimaging.

Authors:  Emil Ljungberg; Tobias C Wood; Ana Beatriz Solana; Steven C R Williams; Gareth J Barker; Florian Wiesinger
Journal:  Magn Reson Med       Date:  2022-04-05       Impact factor: 3.737

  3 in total

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