MR-guided data framing for PET motion correction in simultaneous MR–PET: A preliminary evaluation

Abstract

Head motion can significantly degrade image quality of static and dynamic Positron Emission Tomography (PET) of the human brain. One method to regain acceptable image quality in the presence of motion is to include the correction for motion in the reconstruction process. When applying motion correction, the PET data can be segmented into discrete parts of similar head position, referred to as frames. This framing of the data can reduce the computational overhead necessary for motion correction during the reconstruction process by reducing the number of discrete head positions which have to be accounted for. Here a framing algorithm is presented which minimises residual motion in the framed data, while taking full advantage of the additional information provided by Magnetic Resonance Imaging (MRI) in a simultaneous MR–PET acquisition. In the work presented here information on motion is derived from EPI sequences acquired simultaneously with the PET data. A comparison to images reconstructed with regular framing show a more clearly delineated cortex due to increased contrast between grey matter and white matter. This improvement in image quality is achieved as well as a reduction in the number of frames, thereby reducing the reconstruction time. Preliminary data indicates an efficient reduction of residual intra-frame motion compared to regular framing.