Quantitative analysis of spatial averaging effect on chemical shift imaging SNR and noise coherence with k-space sampling schemes

Spatial averaging of multiple voxels from high-resolution chemical shift imaging (hrCSI) is a common strategy for in vivo metabolic studies to achieve a better signal-to-noise ratio (SNR) for a region-of-interest. However, the mechanism about how the spatial averaging approach influences the respective spectral signal and noise and its relevance to the k-space sampling schemes remains unclear. Using three-dimension ¹⁷O CSI technique with the weighted k-space sampling method of Fourier series window, we performed quantitative SNR comparisons between a single low-resolution CSI (lrCSI) voxel (being 27 times larger than the hrCSI voxel size) and the spatially averaged hrCSI voxels with matched sampling volume and location. We demonstrated that the averaged hrCSI voxel spectrum had a large SNR loss (> 4 times) compared to the lrCSI voxel, which was resulted from unmatched increases in signal (~1.9 fold) and noise (~9.3 fold). The signal increase was caused by the spatial overlapping between the adjacent hrCSI voxels. The substantial noise increase was mainly attributed to the strong noise coherence among hrCSI voxels acquired with the weighted k-space sampling. This study presents a quantitative relation between the k-space sampling schemes to an apparent SNR penalty of the spatial averaging approach. The information could be useful for designing CSI acquisition method and determination of optimal spatial resolution for in vivo metabolic imaging studies.