Peter Adany1, In-Young Choi1,2,3,4, Phil Lee1,3,4. 1. Hoglund Biomedical Imaging Center, University of Kansas Medical Center, Kansas City, Kansas, USA. 2. Department of Neurology, University of Kansas Medical Center, Kansas City, Kansas, USA. 3. Department of Radiology, University of Kansas Medical Center, Kansas City, Kansas, USA. 4. Department of Molecular & Integrative Physiology, University of Kansas Medical Center, Kansas City, Kansas, USA.
Abstract
PURPOSE: To develop a new rapid spatial filtering method for lipid removal, fast lipid reconstruction and removal processing (FLIP), which selectively isolates and removes interfering lipid signals from outside the brain in a full-FOV 2D MRSI and whole-brain 3D echo planar spectroscopic imaging (EPSI). THEORY AND METHODS: FLIP uses regularized least-squares regression based on spatial prior information from MRI to selectively remove lipid signals originating from the scalp and measure the brain metabolite signals with minimum cross contamination. FLIP is a noniterative approach, thus allowing a rapid processing speed, and uses only spatial information without any spectral priors. The performance of FLIP was compared with the Papoulis-Gerchberg algorithm (PGA), Hankel singular value decomposition (HSVD), and fast image reconstruction with L2 regularization (L2). RESULTS: FLIP in both 2D and 3D MRSI resulted in consistent metabolite quantification in a greater number of voxels with less concentration variation than other algorithms, demonstrating effective and robust lipid-removal performance. The percentage of voxels that met quality criteria with FLIP, PGA, HSVD, and L2 processing were 90%, 57%, 29%, and 42% in 2D MRSI, and 80%, 75%, 76%, and 74% in 3D EPSI, respectively. The quantification results of full-FOV MRSI using FLIP were comparable to those of volume-localized MRSI, while allowing significantly increased spatial coverage. FLIP performed the fastest in 2D MRSI. CONCLUSION: FLIP is a new lipid-removal algorithm that promises fast and effective lipid removal with improved volume coverage in MRSI.
PURPOSE: To develop a new rapid spatial filtering method for lipid removal, fast lipid reconstruction and removal processing (FLIP), which selectively isolates and removes interfering lipid signals from outside the brain in a full-FOV 2D MRSI and whole-brain 3D echo planar spectroscopic imaging (EPSI). THEORY AND METHODS: FLIP uses regularized least-squares regression based on spatial prior information from MRI to selectively remove lipid signals originating from the scalp and measure the brain metabolite signals with minimum cross contamination. FLIP is a noniterative approach, thus allowing a rapid processing speed, and uses only spatial information without any spectral priors. The performance of FLIP was compared with the Papoulis-Gerchberg algorithm (PGA), Hankel singular value decomposition (HSVD), and fast image reconstruction with L2 regularization (L2). RESULTS: FLIP in both 2D and 3D MRSI resulted in consistent metabolite quantification in a greater number of voxels with less concentration variation than other algorithms, demonstrating effective and robust lipid-removal performance. The percentage of voxels that met quality criteria with FLIP, PGA, HSVD, and L2 processing were 90%, 57%, 29%, and 42% in 2D MRSI, and 80%, 75%, 76%, and 74% in 3D EPSI, respectively. The quantification results of full-FOV MRSI using FLIP were comparable to those of volume-localized MRSI, while allowing significantly increased spatial coverage. FLIP performed the fastest in 2D MRSI. CONCLUSION: FLIP is a new lipid-removal algorithm that promises fast and effective lipid removal with improved volume coverage in MRSI.
Authors: M von Kienlin; M Beer; A Greiser; D Hahn; K Harre; H Köstler; W Landschütz; T Pabst; J Sandstede; S Neubauer Journal: J Magn Reson Imaging Date: 2001-04 Impact factor: 4.813
Authors: D Wiedermann; N Schuff; G B Matson; B J Soher; A T Du; A A Maudsley; M W Weiner Journal: Magn Reson Imaging Date: 2001-10 Impact factor: 2.546