Literature DB >> 30358001

Ultrashort echo time imaging for quantification of hepatic iron overload: Comparison of acquisition and fitting methods via simulations, phantoms, and in vivo data.

Aaryani Tipirneni-Sajja1,2, Ralf B Loeffler1, Axel J Krafft1,3, Andrea N Sajewski1, Robert J Ogg1, Jane S Hankins4, Claudia M Hillenbrand1.   

Abstract

BACKGROUND: Current R2*-MRI techniques for measuring hepatic iron content (HIC) use various acquisition types and fitting models.
PURPOSE: To evaluate the accuracy and precision of R2*-HIC acquisition and fitting methods. STUDY TYPE: Signal simulations, phantom study, and prospective in vivo cohort. POPULATION: In all, 132 patients (58/74 male/female, mean age 17.7 years). FIELD STRENGTH/SEQUENCE: 2D-multiecho gradient-echo (GRE) and ultrashort echo time (UTE) acquisitions at 1.5T. ASSESSMENT: Synthetic MR signals were created to mimic published GRE and UTE methods, using different R2* values (25-2000 s-1 ) and signal-to-noise ratios (SNR). Phantoms with varying iron concentrations were scanned at 1.5T. In vivo data were analyzed from 132 patients acquired at 1.5T. R2* was estimated by fitting using three signal models. Accuracy and precision of R2* measurements for UTE acquisition parameters (SNR, echo spacing [ΔTE], maximum echo time [TEmax ]) and fitting methods were compared for simulated, phantom, and in vivo datasets. STATISTICAL TESTS: R2* accuracy was determined from the relative error and by linear regression analysis. Precision was evaluated using coefficient of variation (CoV) analysis.
RESULTS: In simulations, all models had high R2* accuracy (error <5%) and precision (CoV <10%) for all SNRs, shorter ΔTE (≤0.5 msec), and longer TEmax (≥10.1 msec); except the constant offset model overestimated R2* at the lowest SNR. In phantoms and in vivo, all models produced similar R2* values for different SNRs and shorter ΔTEs (slopes: 0.99-1.06, R2 > 0.99, P < 0.001). In all experiments, R2* results degraded for high R2* values with longer ΔTE (≥1 msec). In vivo, shorter and longer TEmax gave similar R2* results (slopes: 1.02-1.06, R2 > 0.99, P < 0.001) for the noise subtraction model for 25≤R2*≤2000 s-1 . However, both quadratic and constant offset models, using shorter TEmax (≤4.7 msec) overestimated R2* and yielded high CoVs up to ∼170% for low R2* (<250 s-1 ). DATA
CONCLUSION: UTE with TEmax ≥ 10.1 msec and ΔTE ≤ 0.5 msec yields accurate R2* estimates over the entire clinical HIC range. Monoexponential fitting with noise subtraction is the most robust signal model to changes in UTE parameters and achieves the highest R2* accuracy and precision. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:1475-1488.
© 2018 International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  R2* quantification; hepatic iron overload; signal models; ultrashort echo time

Mesh:

Substances:

Year:  2018        PMID: 30358001      PMCID: PMC6768432          DOI: 10.1002/jmri.26325

Source DB:  PubMed          Journal:  J Magn Reson Imaging        ISSN: 1053-1807            Impact factor:   4.813


  23 in total

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3.  Comparison of whole liver and small region-of-interest measurements of MRI liver R2* in children with iron overload.

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

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5.  Radial Ultrashort TE Imaging Removes the Need for Breath-Holding in Hepatic Iron Overload Quantification by R2* MRI.

Authors:  Aaryani Tipirneni-Sajja; Axel J Krafft; M Beth McCarville; Ralf B Loeffler; Ruitian Song; Jane S Hankins; Claudia M Hillenbrand
Journal:  AJR Am J Roentgenol       Date:  2017-05-15       Impact factor: 3.959

6.  Quantitative R2* MRI of the liver with rician noise models for evaluation of hepatic iron overload: Simulation, phantom, and early clinical experience.

Authors:  Takeshi Yokoo; Qing Yuan; Julien Sénégas; Andrea J Wiethoff; Ivan Pedrosa
Journal:  J Magn Reson Imaging       Date:  2015-05-21       Impact factor: 4.813

7.  Quantitative ultrashort echo time imaging for assessment of massive iron overload at 1.5 and 3 Tesla.

Authors:  Axel J Krafft; Ralf B Loeffler; Ruitian Song; Aaryani Tipirneni-Sajja; M Beth McCarville; Matthew D Robson; Jane S Hankins; Claudia M Hillenbrand
Journal:  Magn Reson Med       Date:  2017-01-16       Impact factor: 4.668

8.  Progression of iron overload in sickle cell disease.

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9.  Trends in transfusion burden among long-term survivors of childhood hematological malignancies.

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10.  Clinical and histological characterization of liver disease in patients with transfusion-dependent beta-thalassemia. A multicenter study of 117 cases.

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  2 in total

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

Authors:  Aaryani Tipirneni-Sajja; Ralf B Loeffler; Jane S Hankins; Cara Morin; Claudia M Hillenbrand
Journal:  J Magn Reson Imaging       Date:  2021-02-26       Impact factor: 5.119

2.  Value of liver iron concentration in healthy volunteers assessed by MRI.

Authors:  Marzanna Obrzut; Vitaliy Atamaniuk; Kevin J Glaser; Jun Chen; Richard L Ehman; Bogdan Obrzut; Marian Cholewa; Krzysztof Gutkowski
Journal:  Sci Rep       Date:  2020-10-21       Impact factor: 4.379

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