Influence of GRAPPA pre-scan methods on temporal SNR of rapid GE-EPI measurements at 9.4 Tesla (2020)

Introduction: In functional MRI (fMRI) echo planar imaging (EPI) is often combined with parallel imaging, e.g. GRAPPA (1), to increase temporal resolution. The auto-calibration scans (ACS) required for the calculation of the coil sensitivities in the parallel imaging reconstruction are conventionally acquired in a segmented fashion (number of segments = parallel imaging factor), with the individual segments of each slice separated by the repetition time (TR). However, in case of TRs in the range of several seconds, ACS segments may be acquired at different B0-field offsets e.g. due to respiration or motion. These fluctuations can result in variations in temporal SNR (tSNR) across different slices particularly at high-field (3). The sensitivity of tSNR on physiological effects can be reduced by acquiring all segments of a slice successively with minimum delay in the so called FLEET technique (3). Alternatively, a FLASH readout, which is more robust against B0-field changes, can be used to obtain the ACS data (2). Although physiological influences are usually considered to be the main cause of tSNR variations at long TRs, as far as we know, the performance of various GRAPPA pre-scan methods (conventional, FLEET and FLASH) has not previously been investigated for a TR in the sub-second range. Methods: Four healthy subjects were measured at 9.4 Tesla (Siemens Healthineers, Germany) using an in-house-built 16Tx-31Rx head-coil (4). Gradient-echo EPIs were acquired for two regions covering a major part of the thalamus (ROI 1) and the motor cortex (ROI 2). Imaging parameters: TE/TR = 23/600ms, FA = 40°, 12 slices, 150 volumes. Two different spatial resolutions were used: • 1 x 1 x 2 mm³: mtx = 192x192, 6/8 partial Fourier, GRAPPA = 4 (60 ACS lines), echo spacing = 1.01 ms. • 2 x 2 x 2 mm³: mtx = 96x96, GRAPPA = 3 (45 ACS lines), echo spacing = 0.8 ms. The two protocols were repeated for both ROIs for all three ACS sampling methods: conventional, FLEET, and FLASH. The excitation flip angle for the FLEET and FLASH ACS scans was 10° and 15°, respectively. Temporal SNR maps were calculated as the mean signal value across time divided by its temporal standard deviation. To quantify the tSNR for the different GRAPPA pre-scan methods, mean tSNR values were assessed for each ROI after performing manual brain masking. Results: Figure 1 shows the calculated tSNR for the different GRAPPA pre-scan methods and brain regions in an example volunteer. The lowest tSNR is visible for the data measured with conventional ACS and low spatial resolution in particular. This observation is consistent for both ROIs. Averaged over all slices, the tSNR values in images acquired with FLEET or FLASH ACS sampling are higher than with conventional ordering, too (Figure 2). This is especially the case at low image resolution. At high spatial resolution, the tSNR of data reconstructed using FLEET and FLASH sampled data is almost identical and the improvement compared to the conventional method is rather small (∼12% in ROI 1 and ∼25% in ROI 2). Conclusions: Although physiological influences and respiration effects in particular are expected to be reduced for sub-second TR, the FLEET and FLASH pre-scan methods yielded clearly higher tSNR compared to the conventional approach. One explanation is, that despite the short TR, the acquisition of all ACS lines still took about 1.8 s (2x2x2 mm³) and 2.4 s (1x1x2 mm³), respectively, due to the slice-segment acquisition scheme, whereas the FLEET method only required about 200 ms (1x1x2 mm³). This study also confirmed that the impact of physiological fluctuations on tSNR heavily scales with the spatial resolution, as it is the case for un-accelerated imaging (5). Thus, even though less tSNR improvement can be expected for alternative ACS acquisition techniques at high spatial resolutions, it still has to be considered as a potential source for effect size differences even in sub-second TR fMRI studies.