Cargando…

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

PURPOSE: The study aims to develop easy-to-implement concomitant field-compensated gradient waveforms with varying velocity-weighting (M(1)) and acceleration-weighting (M(2)) levels and to evaluate their efficacy in correcting signal dropouts and preserving the black-blood state in liver diffusion-w...

Descripción completa

Detalles Bibliográficos
Autores principales: Führes, Tobit, Saake, Marc, Szczepankiewicz, Filip, Bickelhaupt, Sebastian, Uder, Michael, Laun, Frederik Bernd
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10553293/
https://www.ncbi.nlm.nih.gov/pubmed/37796773
http://dx.doi.org/10.1371/journal.pone.0291273
_version_ 1785116135109165056
author Führes, Tobit
Saake, Marc
Szczepankiewicz, Filip
Bickelhaupt, Sebastian
Uder, Michael
Laun, Frederik Bernd
author_facet Führes, Tobit
Saake, Marc
Szczepankiewicz, Filip
Bickelhaupt, Sebastian
Uder, Michael
Laun, Frederik Bernd
author_sort Führes, Tobit
collection PubMed
description PURPOSE: The study aims to develop easy-to-implement concomitant field-compensated gradient waveforms with varying velocity-weighting (M(1)) and acceleration-weighting (M(2)) 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. METHODS: Numerically optimized gradient waveforms were adapted using a novel method that allows for the simultaneous tuning of M(1)- and M(2)-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 (M(1) = 0), acceleration-compensated (M(1) = M(2) = 0), 84%-M(1)–M(2)-compensated, 67%-M(1)–M(2)-compensated) at b-values of 50 and 800 s/mm(2) 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. RESULTS: 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 M(1)–M(2)-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 μm(2)/ms for monopolar vs. < 0.12 μm(2)/ms for the other encodings). CONCLUSION: 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 M(1)–M(2)-compensation does not exist. However, among the examined encodings, the 84%-M(1)–M(2)-compensated encodings provided a suitable tradeoff.
format Online
Article
Text
id pubmed-10553293
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-105532932023-10-06 Impact of velocity- and acceleration-compensated encodings on signal dropout and black-blood state in diffusion-weighted magnetic resonance liver imaging at clinical TEs Führes, Tobit Saake, Marc Szczepankiewicz, Filip Bickelhaupt, Sebastian Uder, Michael Laun, Frederik Bernd PLoS One Research Article PURPOSE: The study aims to develop easy-to-implement concomitant field-compensated gradient waveforms with varying velocity-weighting (M(1)) and acceleration-weighting (M(2)) 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. METHODS: Numerically optimized gradient waveforms were adapted using a novel method that allows for the simultaneous tuning of M(1)- and M(2)-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 (M(1) = 0), acceleration-compensated (M(1) = M(2) = 0), 84%-M(1)–M(2)-compensated, 67%-M(1)–M(2)-compensated) at b-values of 50 and 800 s/mm(2) 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. RESULTS: 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 M(1)–M(2)-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 μm(2)/ms for monopolar vs. < 0.12 μm(2)/ms for the other encodings). CONCLUSION: 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 M(1)–M(2)-compensation does not exist. However, among the examined encodings, the 84%-M(1)–M(2)-compensated encodings provided a suitable tradeoff. Public Library of Science 2023-10-05 /pmc/articles/PMC10553293/ /pubmed/37796773 http://dx.doi.org/10.1371/journal.pone.0291273 Text en © 2023 Führes et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Führes, Tobit
Saake, Marc
Szczepankiewicz, Filip
Bickelhaupt, Sebastian
Uder, Michael
Laun, Frederik Bernd
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
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10553293/
https://www.ncbi.nlm.nih.gov/pubmed/37796773
http://dx.doi.org/10.1371/journal.pone.0291273
work_keys_str_mv AT fuhrestobit impactofvelocityandaccelerationcompensatedencodingsonsignaldropoutandblackbloodstateindiffusionweightedmagneticresonanceliverimagingatclinicaltes
AT saakemarc impactofvelocityandaccelerationcompensatedencodingsonsignaldropoutandblackbloodstateindiffusionweightedmagneticresonanceliverimagingatclinicaltes
AT szczepankiewiczfilip impactofvelocityandaccelerationcompensatedencodingsonsignaldropoutandblackbloodstateindiffusionweightedmagneticresonanceliverimagingatclinicaltes
AT bickelhauptsebastian impactofvelocityandaccelerationcompensatedencodingsonsignaldropoutandblackbloodstateindiffusionweightedmagneticresonanceliverimagingatclinicaltes
AT udermichael impactofvelocityandaccelerationcompensatedencodingsonsignaldropoutandblackbloodstateindiffusionweightedmagneticresonanceliverimagingatclinicaltes
AT launfrederikbernd impactofvelocityandaccelerationcompensatedencodingsonsignaldropoutandblackbloodstateindiffusionweightedmagneticresonanceliverimagingatclinicaltes