Impact of velocity- and acceleration-compensated encodings on signal dropout and black-blood state in diffusion-weighted magnetic resonance liver imaging at clinical TEs.

<h4>Purpose</h4>The study aims to develop easy-to-implement concomitant field-compensated gradient waveforms with varying velocity-weighting (M1) and acceleration-weighting (M2) levels and to evaluate their efficacy in correcting signal dropouts and preserving the black-blood state in li...

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Published in:PLoS ONE
Main Authors: Tobit Führes, Marc Saake, Filip Szczepankiewicz, Sebastian Bickelhaupt, Michael Uder, Frederik Bernd Laun
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2023-01-01
Online Access:https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0291273&type=printable
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author Tobit Führes
Marc Saake
Filip Szczepankiewicz
Sebastian Bickelhaupt
Michael Uder
Frederik Bernd Laun
author_facet Tobit Führes
Marc Saake
Filip Szczepankiewicz
Sebastian Bickelhaupt
Michael Uder
Frederik Bernd Laun
author_sort Tobit Führes
collection DOAJ
container_title PLoS ONE
description <h4>Purpose</h4>The study aims to develop easy-to-implement concomitant field-compensated gradient waveforms with varying velocity-weighting (M1) and acceleration-weighting (M2) levels and to evaluate their efficacy in correcting signal dropouts and preserving the black-blood state in liver diffusion-weighted imaging. Additionally, we seek to determine an optimal degree of compensation that minimizes signal dropouts while maintaining blood signal suppression.<h4>Methods</h4>Numerically optimized gradient waveforms were adapted using a novel method that allows for the simultaneous tuning of M1- and M2-weighting by changing only one timing variable. Seven healthy volunteers underwent diffusion-weighted magnetic resonance imaging (DWI) with five diffusion encoding schemes (monopolar, velocity-compensated (M1 = 0), acceleration-compensated (M1 = M2 = 0), 84%-M1-M2-compensated, 67%-M1-M2-compensated) at b-values of 50 and 800 s/mm2 at a constant echo time of 70 ms. Signal dropout correction and apparent diffusion coefficients (ADCs) were quantified using regions of interest in the left and right liver lobe. The blood appearance was evaluated using two five-point Likert scales.<h4>Results</h4>Signal dropout was more pronounced in the left lobe (19%-42% less signal than in the right lobe with monopolar scheme) and best corrected by acceleration-compensation (8%-10% less signal than in the right lobe). The black-blood state was best with monopolar encodings and decreased significantly (p < 0.001) with velocity- and/or acceleration-compensation. The partially M1-M2-compensated encoding schemes could restore the black-blood state again. Strongest ADC bias occurred for monopolar encodings (difference between left/right lobe of 0.41 μm2/ms for monopolar vs. < 0.12 μm2/ms for the other encodings).<h4>Conclusion</h4>All of the diffusion encodings used in this study demonstrated suitability for routine DWI application. The results indicate that a perfect value for the level of M1-M2-compensation does not exist. However, among the examined encodings, the 84%-M1-M2-compensated encodings provided a suitable tradeoff.
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spelling doaj-art-ca45db4592e64957a89b4e612aa1fd6f2025-08-20T01:06:04ZengPublic Library of Science (PLoS)PLoS ONE1932-62032023-01-011810e029127310.1371/journal.pone.0291273Impact of velocity- and acceleration-compensated encodings on signal dropout and black-blood state in diffusion-weighted magnetic resonance liver imaging at clinical TEs.Tobit FühresMarc SaakeFilip SzczepankiewiczSebastian BickelhauptMichael UderFrederik Bernd Laun<h4>Purpose</h4>The study aims to develop easy-to-implement concomitant field-compensated gradient waveforms with varying velocity-weighting (M1) and acceleration-weighting (M2) levels and to evaluate their efficacy in correcting signal dropouts and preserving the black-blood state in liver diffusion-weighted imaging. Additionally, we seek to determine an optimal degree of compensation that minimizes signal dropouts while maintaining blood signal suppression.<h4>Methods</h4>Numerically optimized gradient waveforms were adapted using a novel method that allows for the simultaneous tuning of M1- and M2-weighting by changing only one timing variable. Seven healthy volunteers underwent diffusion-weighted magnetic resonance imaging (DWI) with five diffusion encoding schemes (monopolar, velocity-compensated (M1 = 0), acceleration-compensated (M1 = M2 = 0), 84%-M1-M2-compensated, 67%-M1-M2-compensated) at b-values of 50 and 800 s/mm2 at a constant echo time of 70 ms. Signal dropout correction and apparent diffusion coefficients (ADCs) were quantified using regions of interest in the left and right liver lobe. The blood appearance was evaluated using two five-point Likert scales.<h4>Results</h4>Signal dropout was more pronounced in the left lobe (19%-42% less signal than in the right lobe with monopolar scheme) and best corrected by acceleration-compensation (8%-10% less signal than in the right lobe). The black-blood state was best with monopolar encodings and decreased significantly (p < 0.001) with velocity- and/or acceleration-compensation. The partially M1-M2-compensated encoding schemes could restore the black-blood state again. Strongest ADC bias occurred for monopolar encodings (difference between left/right lobe of 0.41 μm2/ms for monopolar vs. < 0.12 μm2/ms for the other encodings).<h4>Conclusion</h4>All of the diffusion encodings used in this study demonstrated suitability for routine DWI application. The results indicate that a perfect value for the level of M1-M2-compensation does not exist. However, among the examined encodings, the 84%-M1-M2-compensated encodings provided a suitable tradeoff.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0291273&type=printable
spellingShingle Tobit Führes
Marc Saake
Filip Szczepankiewicz
Sebastian Bickelhaupt
Michael Uder
Frederik Bernd Laun
Impact of velocity- and acceleration-compensated encodings on signal dropout and black-blood state in diffusion-weighted magnetic resonance liver imaging at clinical TEs.
title Impact of velocity- and acceleration-compensated encodings on signal dropout and black-blood state in diffusion-weighted magnetic resonance liver imaging at clinical TEs.
title_full Impact of velocity- and acceleration-compensated encodings on signal dropout and black-blood state in diffusion-weighted magnetic resonance liver imaging at clinical TEs.
title_fullStr Impact of velocity- and acceleration-compensated encodings on signal dropout and black-blood state in diffusion-weighted magnetic resonance liver imaging at clinical TEs.
title_full_unstemmed Impact of velocity- and acceleration-compensated encodings on signal dropout and black-blood state in diffusion-weighted magnetic resonance liver imaging at clinical TEs.
title_short Impact of velocity- and acceleration-compensated encodings on signal dropout and black-blood state in diffusion-weighted magnetic resonance liver imaging at clinical TEs.
title_sort impact of velocity and acceleration compensated encodings on signal dropout and black blood state in diffusion weighted magnetic resonance liver imaging at clinical tes
url https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0291273&type=printable
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