Analysis of accelerated 4D flow MRI in the murine aorta by radial acquisition and compressed sensing reconstruction
Abstract: Preclinical 4D flow MRI remains challenging and is restricted for parallel imaging acceleration due to the limited number of available receive channels. A radial acquisition with combined parallel imaging and temporal compressed sensing reconstruction was implemented to achieve accelerated preclinical 4D flow MRI. In order to increase the accuracy of the measured velocities, a quantitative evaluation of different temporal regularization weights for the compressed sensing reconstruction based on velocity instead of magnitude data is performed. A 3D radial retrospectively triggered phase contrast sequence with a combined parallel imaging and compressed sensing reconstruction with temporal regularization was developed. It was validated in a phantom and in vivo (C57BL/6 J mice), against an established fully sampled Cartesian sequence. Different undersampling factors (USFs [12, 15, 20, 30, 60]) were evaluated, and the effect of undersampling was analyzed in detail for magnitude and velocity data. Temporal regularization weights λ were evaluated for different USFs. Acceleration factors of up to 20 compared with full Nyquist sampling were achieved. The peak flow differences compared with the Cartesian measurement were the following: USF 12, 3.38%; USF 15, 4.68%; USF 20, 0.95%. The combination of 3D radial center‐out trajectories and compressed sensing reconstruction is robust against motion and flow artifacts and can significantly reduce measurement time to 30 min at a resolution of 180 μm3. Concisely, radial acquisition with combined compressed sensing and parallel imaging proved to be an excellent method for analyzing complex flow patterns in mice
- Standort
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Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
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Online-Ressource
- Sprache
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Englisch
- Anmerkungen
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NMR in biomedicine. - 33, 11 (2020) , e4394, ISSN: 1099-1492
- Ereignis
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Veröffentlichung
- (wo)
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Freiburg
- (wer)
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Universität
- (wann)
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2020
- Urheber
- DOI
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10.1002/nbm.4394
- URN
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urn:nbn:de:bsz:25-freidok-1669466
- Rechteinformation
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Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
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25.03.2025, 13:54 MEZ
Datenpartner
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Beteiligte
- Braig, Moritz
- Menza, Marius
- Leupold, Jochen
- LeVan, Pierre
- Li, Feng
- Ko, Cheng-Wen
- Zur Mühlen, Constantin von
- Krafft, Axel Joachim
- Hennig, Jürgen
- Elverfeldt, Dominik von
- Universität
Entstanden
- 2020