UNIVERSI
TÄ
TS-
BIBLIOTHEK
P
ADERBORN
Anmelden
Menü
Menü
Start
Hilfe
Blog
Weitere Dienste
Neuerwerbungslisten
Fachsystematik Bücher
Erwerbungsvorschlag
Bestellung aus dem Magazin
Fernleihe
Einstellungen
Sprache
Deutsch
Deutsch
Englisch
Farbschema
Hell
Dunkel
Automatisch
Sie befinden Sich nicht im Netzwerk der Universität Paderborn. Der Zugriff auf elektronische Ressourcen ist
gegebenenfalls
nur via VPN oder Shibboleth (DFN-AAI) möglich.
mehr Informationen...
Universitätsbibliothek
Katalog
Details
Datensatz exportieren als...
BibTeX
Density‐weighted concentric circle trajectories for high resolution brain magnetic resonance spectroscopic imaging at 7T
Magnetic resonance in medicine, 2018-06, Vol.79 (6), p.2874-2885
Hingerl, Lukas
Bogner, Wolfgang
Moser, Philipp
Považan, Michal
Hangel, Gilbert
Heckova, Eva
Gruber, Stephan
Trattnig, Siegfried
Strasser, Bernhard
2018
Volltextzugriff (PDF)
Details
Autor(en) / Beteiligte
Hingerl, Lukas
Bogner, Wolfgang
Moser, Philipp
Považan, Michal
Hangel, Gilbert
Heckova, Eva
Gruber, Stephan
Trattnig, Siegfried
Strasser, Bernhard
Titel
Density‐weighted concentric circle trajectories for high resolution brain magnetic resonance spectroscopic imaging at 7T
Ist Teil von
Magnetic resonance in medicine, 2018-06, Vol.79 (6), p.2874-2885
Ort / Verlag
United States: Wiley Subscription Services, Inc
Erscheinungsjahr
2018
Quelle
Wiley-Blackwell Journals
Beschreibungen/Notizen
Purpose Full‐slice magnetic resonance spectroscopic imaging at ≥7 T is especially vulnerable to lipid contaminations arising from regions close to the skull. This contamination can be mitigated by improving the point spread function via higher spatial resolution sampling and k‐space filtering, but this prolongs scan times and reduces the signal‐to‐noise ratio (SNR) efficiency. Currently applied parallel imaging methods accelerate magnetic resonance spectroscopic imaging scans at 7T, but increase lipid artifacts and lower SNR‐efficiency further. In this study, we propose an SNR‐efficient spatial‐spectral sampling scheme using concentric circle echo planar trajectories (CONCEPT), which was adapted to intrinsically acquire a Hamming‐weighted k‐space, thus termed density‐weighted‐CONCEPT. This minimizes voxel bleeding, while preserving an optimal SNR. Theory and Methods Trajectories were theoretically derived and verified in phantoms as well as in the human brain via measurements of five volunteers (single‐slice, field‐of‐view 220 × 220 mm2, matrix 64 × 64, scan time 6 min) with free induction decay magnetic resonance spectroscopic imaging. Density‐weighted‐CONCEPT was compared to (a) the originally proposed CONCEPT with equidistant circles (here termed e‐CONCEPT), (b) elliptical phase‐encoding, and (c) 5‐fold Controlled Aliasing In Parallel Imaging Results IN Higher Acceleration accelerated elliptical phase‐encoding. Results By intrinsically sampling a Hamming‐weighted k‐space, density‐weighted‐CONCEPT removed Gibbs‐ringing artifacts and had in vivo +9.5%, +24.4%, and +39.7% higher SNR than e‐CONCEPT, elliptical phase‐encoding, and the Controlled Aliasing In Parallel Imaging Results IN Higher Acceleration accelerated elliptical phase‐encoding (all P < 0.05), respectively, which lead to improved metabolic maps. Conclusion Density‐weighted‐CONCEPT provides clinically attractive full‐slice high‐resolution magnetic resonance spectroscopic imaging with optimal SNR at 7T. Magn Reson Med 79:2874–2885, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
Sprache
Englisch
Identifikatoren
ISSN: 0740-3194
eISSN: 1522-2594
DOI: 10.1002/mrm.26987
Titel-ID: cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_5873433
Format
–
Schlagworte
Acceleration
,
Algorithms
,
Aliasing
,
Bleeding
,
Brain
,
Brain - diagnostic imaging
,
Brain Mapping
,
Brain slice preparation
,
Coding
,
concentric circles
,
Contamination
,
Density
,
density‐weighted acquisition
,
Filtration
,
Full Papers—Spectroscopic Methodology
,
Healthy Volunteers
,
Humans
,
Image Enhancement - methods
,
Image Interpretation, Computer-Assisted - methods
,
Image Processing, Computer-Assisted
,
Imaging
,
Lipids - chemistry
,
Magnetic induction
,
Magnetic resonance imaging
,
magnetic resonance spectroscopic imaging
,
Magnetic Resonance Spectroscopy
,
Medicine
,
Models, Statistical
,
Neuroimaging
,
Noise reduction
,
non‐cartesian trajectory
,
Phantoms, Imaging
,
Point spread functions
,
Resonance
,
Sampling
,
Signal-To-Noise Ratio
,
Spatial discrimination
,
Spatial resolution
,
spatial‐spectral encoding
,
Trajectories
Weiterführende Literatur
Empfehlungen zum selben Thema automatisch vorgeschlagen von
bX