Respiratory gated PET derived from raw PET data

Abstract

Respiratory motion in PET degrades images and limits detectability of small or low- contrast lesions. Although image quality can be improved using respiratory-gating hardware, this adds to the complexity and expense of acquiring PET data. We aimed to develop a data-driven method, based on individual voxel signal fluctuations, for accomplishing electronic respiratory gating of PET data acquired in a clinically practical manner, requiring no additional hardware or end-user input. We tested our methods using both simulated PET scans, as well as actual human PET acquisitions. For the simulations, our methods correctly identified the start frame of each respiratory cycle defined for the phantom. Resultant gated images demonstrated improved effective resolution and increased SUV uptake for lesions scattered in the thorax. For the human PET data, we were able to recover respiratory phase information with a large signal-to-noise ratio. Fully automated voxel-based respiratory gating of PET images may be achieved without the need for gating hardware or additional user input, in a manner capable of improving effective resolution and increasing lesion detectability.