title: In vivo brain rosette spectroscopic imaging (RSI) with LASER excitation, constant gradient strength readout, and automated LCModel quantification for all voxels.
abstract: To optimize the Rosette trajectories for high-sensitivity in vivo brain spectroscopic imaging and reduced gradient demands.
  
  
  
  Using LASER localization, a rosette based sampling scheme for in vivo brain spectroscopic imaging data on a 3 Tesla (T) system is described. The two-dimensional (2D) and 3D rosette spectroscopic imaging (RSI) data were acquired using 20 × 20 in-plane resolution (8 × 8 mm(2) ), and 1 (2D) -18 mm (1.1 cc) or 12 (3D) -8 mm partitions (0.5 cc voxels). The performance of the RSI acquisition was compared with a conventional spectroscopic imaging (SI) sequence using LASER localization and 2D or 3D elliptical phase encoding (ePE). Quantification of the entire RSI data set was performed using an LCModel based pipeline.
  
  
  
  The RSI acquisitions took 32 s for the 2D scan, and as short as 5 min for the 3D 20 × 20 × 12 scan, using a maximum gradient strength Gmax=5.8 mT/m and slew-rate Smax=45 mT/m/ms. The Bland-Altman agreement between RSI and ePE CSI, characterized by the 95% confidence interval for their difference (RSI-ePE), is within 13% of the mean (RSI+ePE)/2. Compared with the 3D ePE at the same nominal resolution, the effective RSI voxel size was three times smaller while the measured signal-to-noise ratio sensitivity, after normalization for differences in effective size, was 43% greater.
  
  
  
  3D LASER-RSI is a fast, high-sensitivity spectroscopic imaging sequence, which can acquire medium-to-high resolution SI data in clinically acceptable scan times (5-10 min), with reduced stress on the gradient system. Magn Reson Med 76:380-390, 2016. © 2015 Wiley Periodicals, Inc.
authors: University of Pittsburgh School of Medicine, Department of Radiology, Pittsburgh, Pennsylvania, USA.
authors: Claudiu V
authors: CV
authors: Schirda
authors: Siemens Healthcare, Siemens Medical Solutions USA, Inc., Pittsburgh, Pennsylvania, USA.
authors: Tiejun
authors: T
authors: Zhao
authors: Massachusetts General Hospital, Department of Radiology, Boston, Massachusetts, USA.
authors: Ovidiu C
authors: OC
authors: Andronesi
authors: University of Pittsburgh School of Medicine, Department of Radiology, Pittsburgh, Pennsylvania, USA.
authors: Yoojin
authors: Y
authors: Lee
authors: University of Pittsburgh School of Medicine, Department of Radiology, Pittsburgh, Pennsylvania, USA.|University of Pittsburgh School of Medicine, Department of Neurology, Pittsburgh, Pennsylvania, USA.
authors: Jullie W
authors: JW
authors: Pan
authors: University of Pittsburgh School of Medicine, Department of Radiology, Pittsburgh, Pennsylvania, USA.
authors: James M
authors: JM
authors: Mountz
authors: University of Pittsburgh School of Medicine, Department of Radiology, Pittsburgh, Pennsylvania, USA.
authors: Hoby P
authors: HP
authors: Hetherington
authors: New York University, Department of Radiology, New York, New York, USA.
authors: Fernando E
authors: FE
authors: Boada
mesh_terms: D000328:Adult; D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology*; D001923:Brain Chemistry; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods; D007834:Lasers; D013058:Mass Spectrometry / Q000379:methods*; D057054:Molecular Imaging / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
keywords: LASER; RSI, sensitivity; Rosette trajectories; brain; fast spectroscopic imaging; normalized SNR efficiency