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Abstract #4220

bin-SENSE: Accelerated MRI Near Metal With No Additional Hardware

Philip K. Lee1,2, Xinwei Shi1,2, Daehyun Yoon1, Evan G. Levine1,2, and Brian A. Hargreaves1,2

1Radiology, Stanford University, Stanford, CA, United States, 2Electrical Engineering, Stanford University, Stanford, CA, United States

MAVRIC-SL suppresses artifacts induced by field inhomogeneities induced by metal, but requires increased scan time due to the acquisition of a fourth spectral dimension. We accelerate MAVRIC-SL acquisitions limited to the body coil by exploiting fieldmap information implicitly provided by the MAVRIC-SL acquisition. SENSE is applied to undo the coherent aliasing, using the spectral profiles as the spatial weights required for matrix inversion. A region growing method is applied to estimate the fieldmap and spectral profiles from uniformly undersampled data. We demonstrate 1.3x retrospective acceleration at a minimal g-factor penalty with no additional hardware requirement.

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