Generalized autocalibrating partially parallel acquisitions (GRAPPA)

TLDR

GRAPPA extends PILS and VD‑AUTO‑SMASH, does not require a prior RF field map, and reconstructs unaliased images from each coil before combination. The study introduces a novel GRAPPA method to accelerate MRI acquisition with an RF coil array and evaluates its practical implementation, reconstruction algorithm, and SNR performance. GRAPPA acquires additional calibration k‑space lines, reconstructs unaliased images per coil, and then combines them, separating reconstruction from combination. GRAPPA achieves higher SNR and improved image quality, as demonstrated by in‑vivo images.

Abstract

In this study, a novel partially parallel acquisition (PPA) method is presented which can be used to accelerate image acquisition using an RF coil array for spatial encoding. This technique, GeneRalized Autocalibrating Partially Parallel Acquisitions (GRAPPA) is an extension of both the PILS and VD-AUTO-SMASH reconstruction techniques. As in those previous methods, a detailed, highly accurate RF field map is not needed prior to reconstruction in GRAPPA. This information is obtained from several k-space lines which are acquired in addition to the normal image acquisition. As in PILS, the GRAPPA reconstruction algorithm provides unaliased images from each component coil prior to image combination. This results in even higher SNR and better image quality since the steps of image reconstruction and image combination are performed in separate steps. After introducing the GRAPPA technique, primary focus is given to issues related to the practical implementation of GRAPPA, including the reconstruction algorithm as well as analysis of SNR in the resulting images. Finally, in vivo GRAPPA images are shown which demonstrate the utility of the technique.