Literature DB >> 32406125

Multi-parametric liver tissue characterization using MR fingerprinting: Simultaneous T1 , T2 , T2 *, and fat fraction mapping.

Olivier Jaubert1, Cristobal Arrieta2, Gastão Cruz1, Aurélien Bustin1, Torben Schneider3, Georgios Georgiopoulos1, Pier-Giorgio Masci1, Carlos Sing-Long2,4, Rene M Botnar1,5, Claudia Prieto1,5.   

Abstract

PURPOSE: Quantitative T1 , T2 , T2 *, and fat fraction (FF) maps are promising imaging biomarkers for the assessment of liver disease, however these are usually acquired in sequential scans. Here we propose an extended MR fingerprinting (MRF) framework enabling simultaneous liver T1 , T2 , T2 *, and FF mapping from a single ~14 s breath-hold scan.
METHODS: A gradient echo (GRE) liver MRF sequence with nine readouts per TR, low flip angles (5-15°), varying magnetisation preparation and golden angle radial trajectory is acquired at 1.5T to encode T1 , T2 , T2 *, and FF simultaneously. The nine-echo time-series are reconstructed using a low-rank tensor constrained reconstruction and used to fit T2 *, B0 and to separate the water and fat signals. Water- and fat-specific T1 , T2, and M0 are obtained through dictionary matching, whereas FF estimation is extracted from the M0 maps. The framework was evaluated in a standardized T1 /T2 phantom, a water-fat phantom, and 12 subjects in comparison to reference methods. Preliminary clinical feasibility is shown in four patients.
RESULTS: The proposed water T1 , water T2 , T2 *, and FF maps in phantoms showed high coefficients of determination (r2 > 0.97) relative to reference methods. Measured liver MRF values in vivo (mean ± SD) for T1 , T2 , T2 *, and FF were 671 ± 60 ms, 43.2 ± 6.8 ms, 29 ± 6.6 ms, and 3.2 ± 2.6% with biases of 92 ms, -7.1 ms, -1.4 ms, and 0.63% when compared to conventional methods.
CONCLUSION: A nine-echo liver MRF sequence allows for quantitative multi-parametric liver tissue characterization in a single breath-hold scan of ~14 s. Future work will aim to validate the proposed approach in patients with liver disease.
© 2020 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  MR fingerprinting; T1 mapping; T2 mapping; T2* mapping; fat fraction; liver MRI; quantitative mapping

Mesh:

Year:  2020        PMID: 32406125     DOI: 10.1002/mrm.28311

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


  11 in total

Review 1.  Magnetic resonance fingerprinting: an overview.

Authors:  Charit Tippareddy; Walter Zhao; Jeffrey L Sunshine; Mark Griswold; Dan Ma; Chaitra Badve
Journal:  Eur J Nucl Med Mol Imaging       Date:  2021-05-26       Impact factor: 9.236

2.  Spectroscopy-based multi-parametric quantification in subjects with liver iron overload at 1.5T and 3T.

Authors:  Gregory Simchick; Ruiyang Zhao; Gavin Hamilton; Scott B Reeder; Diego Hernando
Journal:  Magn Reson Med       Date:  2021-09-23       Impact factor: 4.668

3.  Free-breathing multitasking multi-echo MRI for whole-liver water-specific T1 , proton density fat fraction, and R 2 quantification.

Authors:  Nan Wang; Tianle Cao; Fei Han; Yibin Xie; Xiaodong Zhong; Sen Ma; Alan Kwan; Zhaoyang Fan; Hui Han; Xiaoming Bi; Mazen Noureddin; Vibhas Deshpande; Anthony G Christodoulou; Debiao Li
Journal:  Magn Reson Med       Date:  2021-08-21       Impact factor: 4.668

4.  Repeatability of MR fingerprinting in normal cervix and utility in cervical carcinoma.

Authors:  Mandi Wang; Jose A U Perucho; Peng Cao; Varut Vardhanabhuti; Di Cui; Yiang Wang; Pek-Lan Khong; Edward S Hui; Elaine Y P Lee
Journal:  Quant Imaging Med Surg       Date:  2021-09

5.  Ex-vivo human pancreatic specimen evaluation by 7 Tesla MRI: a prospective radiological-pathological correlation study.

Authors:  Rosa Cervelli; Matteo Cencini; Andrea Cacciato Insilla; Giacomo Aringhieri; Ugo Boggi; Daniela Campani; Michela Tosetti; Laura Crocetti
Journal:  Radiol Med       Date:  2022-08-19       Impact factor: 6.313

6.  Multiparametric quantitative renal MRI in children and young adults: comparison between healthy individuals and patients with chronic kidney disease.

Authors:  Jonathan R Dillman; Stefanie W Benoit; Deep B Gandhi; Andrew T Trout; Jean A Tkach; Katherine VandenHeuvel; Prasad Devarajan
Journal:  Abdom Radiol (NY)       Date:  2022-03-02

Review 7.  MR fingerprinting of the prostate.

Authors:  Wei-Ching Lo; Ananya Panda; Yun Jiang; James Ahad; Vikas Gulani; Nicole Seiberlich
Journal:  MAGMA       Date:  2022-04-13       Impact factor: 2.533

Review 8.  Cardiac magnetic resonance fingerprinting: Trends in technical development and potential clinical applications.

Authors:  Brendan L Eck; Scott D Flamm; Deborah H Kwon; W H Wilson Tang; Claudia Prieto Vasquez; Nicole Seiberlich
Journal:  Prog Nucl Magn Reson Spectrosc       Date:  2020-11-06       Impact factor: 9.795

9.  Simultaneous T1 , T2 , and T relaxation mapping of the lower leg muscle with MR fingerprinting.

Authors:  Azadeh Sharafi; Katherine Medina; Marcelo W V Zibetti; Smita Rao; Martijn A Cloos; Ryan Brown; Ravinder R Regatte
Journal:  Magn Reson Med       Date:  2021-02-08       Impact factor: 3.737

10.  MOCOnet: Robust Motion Correction of Cardiovascular Magnetic Resonance T1 Mapping Using Convolutional Neural Networks.

Authors:  Ricardo A Gonzales; Qiang Zhang; Bartłomiej W Papież; Konrad Werys; Elena Lukaschuk; Iulia A Popescu; Matthew K Burrage; Mayooran Shanmuganathan; Vanessa M Ferreira; Stefan K Piechnik
Journal:  Front Cardiovasc Med       Date:  2021-11-23
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