کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6026522 | 1580903 | 2015 | 8 صفحه PDF | دانلود رایگان |
- We compare the tSNR, BOLD CNR, and BOLD information content of multiplexed-EPI.
- Total acceleration NÂ =Â SÂ ÃÂ M with SIR accelerations (S) and MB accelerations (M).
- With N >Â 8, SÂ =Â 2 yields the maximum tSNR, BOLD CNR and information content.
- Greatest BOLD information content is obtained using TRs ranging from 300Â ms to 600Â ms.
- Highly accelerated EPI may enable new task/paradigms and improve statistical power.
Echo planar imaging (EPI) is the MRI technique that is most widely used for blood oxygen level-dependent (BOLD) functional MRI (fMRI). Recent advances in EPI speed have been made possible with simultaneous multi-slice (SMS) methods which combine acceleration factors M from multiband (MB) radiofrequency pulses and S from simultaneous image refocusing (SIR) to acquire a total of N = S Ã M images in one echo train, providing up to N times speed-up in total acquisition time over conventional EPI. We evaluated accelerations as high as N = 48 using different combinations of S and M which allow for whole brain imaging in as little as 100 ms at 3 T with a 32 channel head coil. The various combinations of acceleration parameters were evaluated by tSNR as well as BOLD contrast-to-noise ratio (CNR) and information content from checkerboard and movie clips in fMRI experiments. We found that at low acceleration factors (N â¤Â 6), setting S = 1 and varying M alone yielded the best results in all evaluation metrics, while at acceleration N = 8 the results were mixed using both S = 1 and S = 2 sequences. At higher acceleration factors (N > 8), using S = 2 yielded maximal BOLD CNR and information content as measured by classification of movie clip frames. Importantly, we found significantly greater BOLD information content using relatively fast TRs in the range of 300 ms-600 ms compared to a TR of 2 s, suggesting that faster TRs capture more information per unit time in task based fMRI.
Journal: NeuroImage - Volume 104, 1 January 2015, Pages 452-459