Clinical feasibility and impact of data-driven respiratory motion compensation studied in 200 whole-body 18 F-FDG PET/CT scans.

André Henrique DiasPaul SchleyerMikkel H VendelboKarin HjorthaugLars C GormsenOle L Munk

Published in: EJNMMI research (2022)

Respiratory motion compensation using DDG is readily integrated into clinical routine and produce images with more accurate and significantly greater SUV values and smaller metabolic volumes. In our broad cohort of patients, the physicians overwhelmingly preferred gated over ungated images, with a slight preference for DDG images. However, even in patients with malignant disease in the torso, no additional diagnostic information was obtained by the gated images that could not be derived from the ungated images.

Keyphrases

deep learning
convolutional neural network
optical coherence tomography
end stage renal disease
primary care
computed tomography
ejection fraction
chronic kidney disease
healthcare
magnetic resonance imaging
prognostic factors
patient reported outcomes