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 T, Saake M, Szczepankiewicz F, Bickelhaupt S, Uder M, Laun FB (2023)

Publication Type: Journal article

Publication year: 2023

Journal

PLoS ONE Public Library of Science

Book Volume: 18

Article Number: e0291273

Journal Issue: 10 OCTOBER

DOI: 10.1371/journal.pone.0291273

Abstract

Purpose 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. Methods 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. 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 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). 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 M1–M2-compensation does not exist. However, among the examined encodings, the 84%-M1–M2-compensated encodings provided a suitable tradeoff.

Authors with CRIS profile

Tobit Führes Professur für quantitative MR-Bildgebung (Heisenberg-Professur) Marc Saake Medizinische Fakultät Sebastian Bickelhaupt Institute of Radiology Michael Uder Lehrstuhl für Diagnostische Radiologie Frederik Bernd Laun Professur für quantitative MR-Bildgebung (Heisenberg-Professur)

Involved external institutions

Lund University / Lunds universitet SE Sweden (SE)

How to cite

APA:

Führes, T., Saake, M., Szczepankiewicz, F., Bickelhaupt, S., Uder, M., & Laun, F.B. (2023). Impact of velocity- and acceleration-compensated encodings on signal dropout and black-blood state in diffusion-weighted magnetic resonance liver imaging at clinical TEs. PLoS ONE, 18(10 OCTOBER). https://dx.doi.org/10.1371/journal.pone.0291273

MLA:

Führes, Tobit, et al. "Impact of velocity- and acceleration-compensated encodings on signal dropout and black-blood state in diffusion-weighted magnetic resonance liver imaging at clinical TEs." PLoS ONE 18.10 OCTOBER (2023).

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