Dynamic autocalibrated parallel imaging using temporal GRAPPA (TGRAPPA). Magn Reson Med 2005;53:981–985

Current parallel imaging techniques for accelerated imaging require a fully encoded reference data set to estimate the spa-tial coil sensitivity information needed for reconstruction. In dynamic parallel imaging a time-interleaved acquisition scheme can be used, which eliminates the need for separately acquiring additional reference data, since the signal from directly adja-cent time frames can be merged to build a set of fully encoded full-resolution reference data for coil calibration. In this work, we demonstrate that a time-interleaved sampling scheme, in combination with autocalibrated GRAPPA (referred to as TGRAPPA), allows one to easily update the coil weights for the GRAPPA algorithm dynamically, thereby improving the acquisi-tion efficiency. This method may update coil sensitivity esti-mates frame by frame, thereby tracking changes in relative coil sensitivities that may occur during the data acquisition. Mag