  Purpose: The purpose of this study is to demonstrate a method for Specific
Absorption Rate (SAR) reduction for T2-FLAIR MRI sequences at 7T by predicting
the required adiabatic pulse power and scaling the amplitude in a slice-wise
fashion. Methods: We used a TR-FOCI adiabatic pulse for spin inversion in a
T2-FLAIR sequence to improve B1+ homogeneity and calculate the pulse power
required for adiabaticity slice-by-slice to minimize the SAR. Drawing on the
implicit B1+ inhomogeneity present in a standard localizer scan, 3D AutoAlign
localizers and SA2RAGE B1+ maps were acquired in eight volunteers. A
convolutional neural network (CNN) was then trained to predict the B1+ profile
from the localizers and scale factors for the pulse power for each slice were
calculated. The ability to predict the B1+ profile as well as how the derived
pulse scale factors affected the FLAIR inversion efficiency were assessed in
transverse, sagittal, and coronal orientations. Results: The predicted B1+ maps
matched the measured B1+ maps with a mean difference of 4.45% across all
slices. The acquisition in the transverse orientation was shown to be most
effective for this method and delivered a 40% reduction in SAR along with 1min
and 30-sec reduction in scan time (28%) without degradation of image quality.
Conclusion: We propose a SAR reduction technique based on the prediction of B1+
profiles from standard localizer scans using a CNN and show that scaling the
inversion pulse power slice-by-slice for FLAIR sequences at 7T reduces SAR and
scan time without compromising image quality.
