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Abstract #3995

Improving Sensitivity in Low SNR Diffusion Imaging Using Optimal SNR Coil Combinations

Jennifer A. McNab1,2, Jonathan A. Polimeni1,2, Julien A. Cohen-Adad1,2, Lawrence L. Wald1,3

1A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; 2Harvard Medical School, Boston, MA, United States; 3Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, United States

Sum-of-squares (SoS) is the standard method for combining multi-channel coil images. SoS implicitly assumes that the pixel intensity is a reasonable estimate of the coil sensitivity profile. While this may hold true for acquisitions with high SNR and ideal arrays, diffusion-weighted images often have low SNR. We demonstrate improved sensitivity to diffusion measures using coil sensitivity estimates from high SNR b = 0 images as well as a quick determination of the noise covariance between coil channels to improve the channel combination. This approach adds 20 s of scan time but can increase fractional anisotropy estimates, for example, by 30%.