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Spectroscopy‐based multi‐parametric quantification in subjects with liver iron overload at 1.5T and 3T
Author(s) -
Simchick Gregory,
Zhao Ruiyang,
Hamilton Gavin,
Reeder Scott B.,
Hernando Diego
Publication year - 2022
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.29021
Subject(s) - reproducibility , intraclass correlation , repeatability , cirrhosis , chronic liver disease , linear regression , correlation coefficient , nuclear medicine , chemistry , medicine , mathematics , statistics , chromatography
Purpose To evaluate the precision profile (repeatability and reproducibility) of quantitative STEAM‐MRS and to determine the relationships between multiple MR biomarkers of chronic liver disease in subjects with iron overload at both 1.5 Tesla (T) and 3T. Methods MRS data were acquired in patients with known or suspected liver iron overload. Two STEAM‐MRS sequences (multi‐TE and multi‐TE‐TR) were acquired at both 1.5T and 3T (same day), including test–retest acquisition. Each acquisition enabled estimation of R 1, R 2, and FWHM (each separately for water and fat); and proton density fat fraction. The test–retest repeatability and reproducibility across acquisition modes (multi‐TE vs. multi‐TE‐TR) of the estimates were evaluated using intraclass correlation coefficients, linear regression, and Bland‐Altman analyses. Multi‐parametric relationships between parameters at each field strength, across field strengths, and with liver iron concentration were also evaluated using linear and nonlinear regression. Results Fifty‐six (n = 56) subjects (10 to 73 years, 37 males/19 females) were successfully recruited. Both STEAM‐MRS sequences demonstrated good‐to‐excellent precision (intraclass correlation coefficient ≥ 0.81) for the quantification of R 1 water , R 2 water , FWHM water , and proton density fat fraction at both 1.5T and 3T. Additionally, several moderate ( R 2 = 0.50 to 0.69) to high ( R 2 ≥ 0.70) correlations were observed between biomarkers, across field strengths, and with liver iron concentration. Conclusions Over a broad range of liver iron concentration, STEAM‐MRS enables rapid and precise measurement of multiple biomarkers of chronic liver disease. By evaluating the multi‐parametric relationships between biomarkers, this work may advance the comprehensive MRS‐based assessment of chronic liver disease and may help establish biomarkers of chronic liver disease.