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.
Highlights
Organ failure caused by iron overload is a major cause of death in patients with iron load disease
We propose a new algorithm for T2* estimation in magnitude MR images called ADAPtive T2* estimation from combined Signal models (ADAPTS)
Precision in terms of the 95% confidence interval (CI) ranged from 0.08–4.30 ms for the cardiac TEs and 0.06– 4.74 ms for the liver TEs
Summary
Organ failure caused by iron overload is a major cause of death in patients with iron load disease. Accurate quantification of organ iron load has been shown useful in tailoring the therapy for such patients [1]. MR imaging is used as the current reference standard to assess iron load in different organs. It is noninvasive, has documented high reliability and has been validated to biopsies in the heart and liver [2,3,4,5,6,7]
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