Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

The resolution in conventional BOLD FMRI is considerably lower than can be achieved with other MRI methods, and is insufficient for many important applications. One major difficulty in robustly improving spatial resolution is the poor image quality in BOLD FMRI, which suffers from distortions, blurring, and signal dropout. This work considers the potential for increased resolution with a new FMRI method based on balanced SSFP. This method establishes a blood oxygenation sensitive steady-state (BOSS) signal, in which the frequency sensitivity of balanced SSFP is used to detect the frequency shift of deoxyhemoglobin. BOSS FMRI is highly SNR efficient and does not suffer from image distortions or signal dropout, making this method an excellent candidate for high-resolution FMRI. This study presents the first demonstration of high-resolution BOSS FMRI, using an efficient 3D stack-of-segmented EPI readout and combined acquisition at multiple center frequencies. BOSS FMRI is shown to enable high-resolution FMRI data (1 x 1 x 2 mm(3)) in both visual and motor systems using standard hardware at 1.5 T. Currently, the major limitation of BOSS FMRI is its sensitivity to temporal and spatial field drift.

Original publication

DOI

10.1002/mrm.20753

Type

Journal article

Journal

Magnetic resonance in medicine

Publication Date

01/2006

Volume

55

Pages

161 - 170

Addresses

Oxford Centre for Functional MRI of the Brain, FMRIB, Oxford University, UK. karla@fmrib.ox.ac.uk

Keywords

Motor Cortex, Visual Cortex, Humans, Imaging, Three-Dimensional, Magnetic Resonance Imaging, Brain Mapping, Reproducibility of Results, Image Processing, Computer-Assisted