These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
Pubmed for Handhelds
PUBMED FOR HANDHELDS
Search MEDLINE/PubMed
Title: Functional MRI using sensitivity-encoded echo planar imaging (SENSE-EPI). Author: Preibisch C, Pilatus U, Bunke J, Hoogenraad F, Zanella F, Lanfermann H. Journal: Neuroimage; 2003 Jun; 19(2 Pt 1):412-21. PubMed ID: 12814590. Abstract: Parallel imaging methods become increasingly available on clinical MR scanners. To investigate the potential of sensitivity-encoded single-shot EPI (SENSE-EPI) for functional MRI, five imaging protocols at different SENSE reduction factors (R) and matrix sizes were compared with respect to their noise characteristics and their sensitivity toward functional activation in a motor task examination. At constant echo times, SENSE-EPI was either used to shorten the single volume acquisition times (TR(min)) at matrix size 128 x 100 (22 slices) from 3.9 s (no SENSE) to 2.0 s at R = 3, or to increase the matrix size to 192 x 153 (22 slices), resulting in TR(min) = 5.3 s for R = 2 or TR(min) = 3.4 s for R = 3. At the lower resolution, the bisection of echo train length (R = 2) substantially reduced distortions and blurring, while signal-to-noise and statistical power (measured by cluster size and maximum t value per unit time) were hardly reduced. At R = 3 the additional gain in speed and distortion reduction was quite small, while signal-to-noise and statistical power dropped significantly. With enhanced spatial resolution the time course signal-to-noise was better than expected from theory for purely thermal noise because of a reduced contribution of physiological noise, and statistical power almost reached that of the regular, low-resolution single-shot EPI, with a slight drop off toward R = 3. Thus, SENSE-EPI allows to substantially increase speed and spatial resolution in fMRI. At SENSE reduction factors up to R = 2, the potential drawbacks regarding signal-to-noise and statistical power are almost negligible.[Abstract] [Full Text] [Related] [New Search]