Literature DB >> 33634923

Quantitative Susceptibility Mapping Using a Multispectral Autoregressive Moving Average Model to Assess Hepatic Iron Overload.

Aaryani Tipirneni-Sajja1,2, Ralf B Loeffler1,3, Jane S Hankins4, Cara Morin1, Claudia M Hillenbrand1,3.   

Abstract

BACKGROUND: R2*-MRI is clinically used to noninvasively assess hepatic iron content (HIC) to guide potential iron chelation therapy. However, coexisting pathologies, such as fibrosis and steatosis, affect R2* measurements and may thus confound HIC estimations.
PURPOSE: To evaluate whether a multispectral auto regressive moving average (ARMA) model can be used in conjunction with quantitative susceptibility mapping (QSM) to measure magnetic susceptibility as a confounder-free predictor of HIC. STUDY TYPE: Phantom study and in vivo cohort.
SUBJECTS: Nine iron phantoms covering clinically relevant R2* range (20-1200/second) and 48 patients (22 male, 26 female, median age 18 years). FIELD STRENGTH/SEQUENCE: Three-dimensional (3D) and two-dimensional (2D) multi-echo gradient echo (GRE) at 1.5 T. ASSESSMENT: ARMA-QSM modeling was performed on the complex 3D GRE signal to estimate R2*, fat fraction (FF), and susceptibility measurements. R2*-based dry clinical HIC values were calculated from the 2D GRE acquisition using a published R2*-HIC calibration curve as reference standard. STATISTICAL TESTS: Linear regression analysis was performed to compare ARMA R2* and susceptibility-based estimates to iron concentrations and dry clinical HIC values in phantoms and patients, respectively.
RESULTS: In phantoms, the ARMA R2* and susceptibility values strongly correlated with iron concentrations (R2  ≥ 0.9). In patients, the ARMA R2* values highly correlated (R2  = 0.97) with clinical HIC values with slope = 0.026, and the susceptibility values showed good correlation (R2  = 0.82) with clinical dry HIC values with slope = 3.3 and produced a dry-to-wet HIC ratio of 4.8. DATA
CONCLUSION: This study shows the feasibility that ARMA-QSM can simultaneously estimate susceptibility-based wet HIC, R2*-based dry HIC and FFs from a single multi-echo GRE acquisition. Our results demonstrate that both, R2* and susceptibility-based wet HIC values estimated with ARMA-QSM showed good association with clinical dry HIC values with slopes similar to published R2*-biopsy HIC calibration and dry-to-wet tissue weight ratio, respectively. Hence, our study shows that ARMA-QSM can provide potentially confounder-free assessment of hepatic iron overload. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.
© 2021 International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  R2*; fibrosis; iron overload; liver; susceptibility

Mesh:

Substances:

Year:  2021        PMID: 33634923      PMCID: PMC9223690          DOI: 10.1002/jmri.27584

Source DB:  PubMed          Journal:  J Magn Reson Imaging        ISSN: 1053-1807            Impact factor:   5.119


  30 in total

1.  Cardiovascular T2-star (T2*) magnetic resonance for the early diagnosis of myocardial iron overload.

Authors:  L J Anderson; S Holden; B Davis; E Prescott; C C Charrier; N H Bunce; D N Firmin; B Wonke; J Porter; J M Walker; D J Pennell
Journal:  Eur Heart J       Date:  2001-12       Impact factor: 29.983

2.  MRI R2 and R2* mapping accurately estimates hepatic iron concentration in transfusion-dependent thalassemia and sickle cell disease patients.

Authors:  John C Wood; Cathleen Enriquez; Nilesh Ghugre; J Michael Tyzka; Susan Carson; Marvin D Nelson; Thomas D Coates
Journal:  Blood       Date:  2005-04-28       Impact factor: 22.113

3.  Morphology enabled dipole inversion (MEDI) from a single-angle acquisition: comparison with COSMOS in human brain imaging.

Authors:  Tian Liu; Jing Liu; Ludovic de Rochefort; Pascal Spincemaille; Ildar Khalidov; James Robert Ledoux; Yi Wang
Journal:  Magn Reson Med       Date:  2011-04-04       Impact factor: 4.668

4.  R2* relaxometry for the quantification of hepatic iron overload: biopsy-based calibration and comparison with the literature.

Authors:  B Henninger; H Zoller; S Rauch; A Finkenstedt; M Schocke; W Jaschke; C Kremser
Journal:  Rofo       Date:  2015-04-15

5.  Simultaneous phase unwrapping and removal of chemical shift (SPURS) using graph cuts: application in quantitative susceptibility mapping.

Authors:  Jianwu Dong; Tian Liu; Feng Chen; Dong Zhou; Alexey Dimov; Ashish Raj; Qiang Cheng; Pascal Spincemaille; Yi Wang
Journal:  IEEE Trans Med Imaging       Date:  2014-10-08       Impact factor: 10.048

6.  Autoregressive moving average modeling for hepatic iron quantification in the presence of fat.

Authors:  Aaryani Tipirneni-Sajja; Axel J Krafft; Ralf B Loeffler; Ruitian Song; Armita Bahrami; Jane S Hankins; Claudia M Hillenbrand
Journal:  J Magn Reson Imaging       Date:  2019-02-13       Impact factor: 4.813

Review 7.  Susceptibility-weighted imaging and quantitative susceptibility mapping in the brain.

Authors:  Chunlei Liu; Wei Li; Karen A Tong; Kristen W Yeom; Samuel Kuzminski
Journal:  J Magn Reson Imaging       Date:  2014-10-01       Impact factor: 4.813

Review 8.  Monitoring long-term efficacy of iron chelation treatment with biomagnetic liver susceptometry.

Authors:  Roland Fischer; Antonio Piga; Paul Harmatz; Peter Nielsen
Journal:  Ann N Y Acad Sci       Date:  2005       Impact factor: 5.691

9.  A novel background field removal method for MRI using projection onto dipole fields (PDF).

Authors:  Tian Liu; Ildar Khalidov; Ludovic de Rochefort; Pascal Spincemaille; Jing Liu; A John Tsiouris; Yi Wang
Journal:  NMR Biomed       Date:  2011-03-08       Impact factor: 4.044

10.  Ultrashort Echo Time Quantitative Susceptibility Mapping (UTE-QSM) of Highly Concentrated Magnetic Nanoparticles: A Comparison Study about Different Sampling Strategies.

Authors:  Xing Lu; Hyungseok Jang; Yajun Ma; Saeed Jerban; Eric Y Chang; Jiang Du
Journal:  Molecules       Date:  2019-03-22       Impact factor: 4.411

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  1 in total

Review 1.  Noninvasive imaging of hepatic dysfunction: A state-of-the-art review.

Authors:  Ting Duan; Han-Yu Jiang; Wen-Wu Ling; Bin Song
Journal:  World J Gastroenterol       Date:  2022-04-28       Impact factor: 5.374

  1 in total

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