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Abstract #2229

Artificial Correlations Induced by SENSE and GRAPPA Corrupt fcMRI Conclusions

Iain P. Bruce1, Daniel B. Rowe1, 2

1Department of Mathematics, Statistics, and Computer Science, Marquette University, Milwaukee, WI, United States; 2Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States

In fcMRI, parallel MR image reconstruction models such as SENSE and GRAPPA can be used to reduce data acquisition time in an effort to both increase spatiotemporal resolution and more rapidly measure changes in the BOLD contrast. However, the correlations induced by these models can change the correlation coefficients between previously aliased voxels in sub-sampled data by contrast to data that was fully sampled. Depending on the sign of the induced correlation relative to the correlation inherent in the acquired data, this can result in either Type I or II errors in fcMRI when the hypothesis assumes no correlation exists.

Keywords

accelerated accounted acquisition added aims aliased aliasing aligned arise around array artifacts artificial assumes attention attractive audience avoid background band bandpass biological biophysics brain calibration circle coefficient coefficients coils college combined commonly computer concurrent connectivity contrast convolved correlation correlations corrupt covariance decay decreasing default density depending either employed encoding equation errors essential expected experimentally fact fields filter filtering fitting frequencies frequency full fully functional green hamming human hypothesis imperative implications increasing increments induce induced inherent interpolation invasive involve kernel little magnitude maintain mathematics medical misleading missing mode model models moreover negligible network noise notable notably observing omitted origin outlined outside paid parallel phantom polynomial popularity previously process processes processing pulse random receiver reconstruct reconstructed reconstruction reconstructions reduced reducing reduction removal reside resting revolve sampled science seed sense sensitivities series short sign simulate simulated sources space spatial spin squared statistical statistics structure studies subject target threshold type unfolding upper variety white window