Manuel Schneider1, Gemini Janas2,3, Felix Lugauer1, Elisabeth Hoppe1, Dominik Nickel4, Brian M Dale5, Berthold Kiefer4, Andreas Maier1, Mustafa R Bashir2,3. 1. Pattern Recognition Lab, Department of Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany. 2. Radiology, Duke University Medical Center, Durham, North Carolina. 3. Center for Advanced Magnetic Resonance Development, Duke University Medical Center, Durham, North Carolina. 4. MR Applications Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany. 5. MR R&D Collaborations, Siemens Healthineers, Cary, North Carolina.
Abstract
PURPOSE: To develop a bipolar multi-echo MRI method for the accurate estimation of the adipose tissue fatty acid composition (FAC) using clinically relevant protocols at clinical field strength. METHODS: The proposed technique jointly estimates confounding factors (field map, R 2 * , eddy-current phase) and triglyceride saturation state parameters by fitting multi-echo gradient echo acquisitions to a complex signal model. The noise propagation behavior was improved by applying a low-rank enforcing denoising technique and by addressing eddy-current-induced phase discrepancies analytically. The impact of the total echo train duration on the FAC parameter map accuracy was analyzed in an oil phantom at 3T. Accuracy and reproducibility assessment was based on in vitro oil phantom measurements at two field strengths (3T and 1.5T) and with two different protocols. Repeatability was assessed in vivo in patients (n = 8) with suspected fatty liver disease using test-retest acquisitions in the abdominal subcutaneous, perirenal and mesenteric fat depots. RESULTS: Echo train readout durations of at least five times the conventional in-phase time were required for accurate FAC estimation in areas of high fat content. In vitro, linear regression and Bland-Altman analyses demonstrated strong (r > 0.94) and significant (P ≪ 0.01) correlations between measured and reference FACs for all acquisitions, with smaller overall intercepts and biases at 3T compared to 1.5T. In vivo, reported mean absolute differences between test and retest were 1.54%, 3.31%, and 2.63% for the saturated, mono-unsaturated, and poly-unsaturated fat component, respectively. CONCLUSIONS: Accurate and reproducible MRI-based FAC quantification within a breath-hold is possible at clinical field strengths.
PURPOSE: To develop a bipolar multi-echo MRI method for the accurate estimation of the adipose tissue fatty acid composition (FAC) using clinically relevant protocols at clinical field strength. METHODS: The proposed technique jointly estimates confounding factors (field map, R 2 * , eddy-current phase) and triglyceride saturation state parameters by fitting multi-echo gradient echo acquisitions to a complex signal model. The noise propagation behavior was improved by applying a low-rank enforcing denoising technique and by addressing eddy-current-induced phase discrepancies analytically. The impact of the total echo train duration on the FAC parameter map accuracy was analyzed in an oil phantom at 3T. Accuracy and reproducibility assessment was based on in vitro oil phantom measurements at two field strengths (3T and 1.5T) and with two different protocols. Repeatability was assessed in vivo in patients (n = 8) with suspected fatty liver disease using test-retest acquisitions in the abdominal subcutaneous, perirenal and mesenteric fat depots. RESULTS: Echo train readout durations of at least five times the conventional in-phase time were required for accurate FAC estimation in areas of high fat content. In vitro, linear regression and Bland-Altman analyses demonstrated strong (r > 0.94) and significant (P ≪ 0.01) correlations between measured and reference FACs for all acquisitions, with smaller overall intercepts and biases at 3T compared to 1.5T. In vivo, reported mean absolute differences between test and retest were 1.54%, 3.31%, and 2.63% for the saturated, mono-unsaturated, and poly-unsaturated fat component, respectively. CONCLUSIONS: Accurate and reproducible MRI-based FAC quantification within a breath-hold is possible at clinical field strengths.
Authors: Gavin Hamilton; Alex N Schlein; Tanya Wolfson; Guilherme M Cunha; Kathryn J Fowler; Michael S Middleton; Rohit Loomba; Claude B Sirlin Journal: NMR Biomed Date: 2020-03-03 Impact factor: 4.044
Authors: Matthias Jung; Susanne Rospleszcz; Maximilian T Löffler; Sven S Walter; Elke Maurer; Pia M Jungmann; Annette Peters; Johanna Nattenmüller; Christopher L Schlett; Fabian Bamberg; Lena S Kiefer; Thierno D Diallo Journal: Eur Radiol Date: 2022-10-14 Impact factor: 7.034
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