Theoretical optimization of multi-echo fMRI data acquisition.
Simulations are used to optimize multi-echo fMRI data acquisition for detection of BOLD signal changes in this study. Optimal sequence design (echo times and sampling period (receiver bandwidth)) and the variation in sensitivity between tissues with different baseline T*(2) are investigated, taking into account the effects of physiological noise and non-exponential signal decay. In the case of a single echo, for normally distributed, uncorrelated noise, the results indicate that the sampling period should be made as long as possible (so as to produce an acceptable level of image distortion), up to a maximum sampling period of 3T*(2), (i.e. optimum TE = 1.5T*(2)). Combining the signal from multiple echoes using weighted summation improves the contrast-to-noise ratio (CNR), at a reduced optimum echo interval. If the BOLD effect causes a constant change in relaxation rate, DeltaR*(2), independent of the tissue R*(2), then a multi-echo acquisition causes considerable variation in sensitivity to BOLD signal changes with tissue T*(2), so that if the sequence is optimized for a target tissue T*(2) it will be more sensitive to BOLD signal changes in tissues with shorter T*(2) values. Fitting for DeltaR*(2) reduces the CNR, and when using this approach, the shortest echo time interval should be used, down to a limit of about 0.3T*(2), and as many echoes as possible within the constraints of TR or hardware limitations should be collected. It is also shown that the optimal sequence will remain optimum or close to optimum irrespective of whether there are physiological noise contributions.
Gowland
P A
PA
Sir Peter Mansfield Magnetic Resonance Centre, School of Physics and Astronomy, University of Nottingham, UK. penny.gowland@nottingham.ac.uk
Bowtell
R
R
D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D017352:Echo-Planar Imaging / Q000295:instrumentation / Q000379:methods*; D004867:Equipment Design; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000295:instrumentation / Q000379:methods*; D015233:Models, Statistical; D010100:Oxygen / Q000378:metabolism; D012680:Sensitivity and Specificity; D012984:Software; D013997:Time Factors
D010100:Oxygen