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Ultrashort echo time imaging for quantification of hepatic iron overload: Comparison of acquisition and fitting methods via simulations, phantoms, and in vivo data
Author(s) -
TipirneniSajja Aaryani,
Loeffler Ralf B.,
Krafft Axel J.,
Sajewski Andrea N.,
Ogg Robert J.,
Hankins Jane S.,
Hillenbrand Claudia M.
Publication year - 2019
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.26325
Subject(s) - imaging phantom , accuracy and precision , coefficient of variation , echo (communications protocol) , echo time , gradient echo , nuclear magnetic resonance , in vivo , reproducibility , correlation coefficient , nuclear medicine , biomedical engineering , materials science , mathematics , magnetic resonance imaging , physics , computer science , statistics , medicine , radiology , computer network , microbiology and biotechnology , biology
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 [TE max ]) 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 TE max (≥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, R 2 > 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 TE max gave similar R2* results (slopes: 1.02–1.06, R 2 > 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 TE max (≤4.7 msec) overestimated R2* and yielded high CoVs up to ∼170% for low R2* (<250 s −1 ). Data Conclusion UTE with TE max ≥ 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.