Validation of a new t2* algorithm and its uncertainty value for cardiac and liver iron load determination from MRI magnitude images

Abstract

PurposeTo validate an automatic algorithm for offline T2* measurements, providing robust, vendor‐independent T2*, and uncertainty estimates for iron load quantification in the heart and liver using clinically available imaging sequences.MethodsA T2* region of interest (ROI)‐based algorithm was developed for robustness in an offline setting. Phantom imaging was performed on a 1.5 Tesla system, with clinically available multiecho gradient‐recalled‐echo (GRE) sequences for cardiac and liver imaging. A T2* single‐echo GRE sequence was used as reference. Simulations were performed to assess accuracy and precision from 2000 measurements. Inter‐ and intraobserver variability was obtained in a patient study (n = 23).ResultsSimulations: Accuracy, in terms of the mean differences between the proposed method and true T2* ranged from 0–0.73 ms. Precision, in terms of confidence intervals of repeated measurements, was 0.06–4.74 ms showing agreement between the proposed uncertainty estimate and simulations. Phantom study: Bias and variability were 0.26 ± 4.23 ms (cardiac sequence) and −0.23 ± 1.69 ms (liver sequence). Patient study: Intraobserver variability was similar for experienced and inexperienced observers (0.03 ± 1.44 ms versus 0.16 ± 2.33 ms). Interobserver variability was 1.0 ± 3.77 ms for the heart and −0.52 ± 2.75 ms for the liver.ConclusionThe proposed algorithm was shown to provide robust T2* measurements and uncertainty estimates over the range of clinically relevant T2* values. Magn Reson Med, 2015. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Magn Reson Med 75:1717–1729, 2016. © 2015 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance.

Automatic T2* determination for quantification of iron load in heart and liver: a comparison between automatic inline Maximum Likelihood Estimate and the truncation and offset methods

“…To help avoid possible clinical implications, however unlikely, an algorithm that includes reporting a T2* uncertainty value may be applied, as recently presented by Bidhult et al . ().…”

“…Further, it is unlikely that the small differences between methods, as measured in this study, should be clinically significant. To help avoid possible clinical implications, however unlikely, an algorithm that includes reporting a T2* uncertainty value may be applied, as recently presented by Bidhult et al (2015).…”

Characterization of acute TLR-7 agonist-induced hemorrhagic myocarditis in mice by multiparametric quantitative cardiac magnetic resonance imaging

“…The T 1 curve fitting was subsequently performed on a pixelwise basis on the remaining measured inversion times using a nonlinear least square three-parameter fit, which accounted for Look–Locker correction. Data analysis was performed in Segment version 2.0 (Segment, Medviso) (Bidhult et al, 2016a,b).…”

“…To improve accuracy of the in vivo trajectory measurement, we used 12 averages and ECG triggering. A pixelwise T 2 * mono-exponential fit was performed on the multiple echo T 2 * w-UTE images using Segment 2.0 (Segment, Medviso) (BidhulT et al, 2016a,b).…”

Detection of acute TLR-7 agonist-induced hemorrhagic myocarditis in mice by refined multi-parametric quantitative cardiac MRI

“…To improve the accuracy of the in vivo trajectory measurement, we used 12 averages and ECG triggering. A pixel wise T 2 * mono-exponential fit was performed on the multiple echo T 2 * w-UTE images using Segment 2.0 (Segment, Medviso) (17).…”