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Reducing respiratory motion artifacts in positron emission tomography through retrospective stacking
Author(s) -
Thorndyke Brian,
Schreibmann Eduard,
Koong Albert,
Xing Lei
Publication year - 2006
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.2207367
Subject(s) - positron emission tomography , nuclear medicine , medicine , positron emission , medical imaging , stacking , tomography , positron , radiology , computed tomography , medical physics , nuclear magnetic resonance , physics , nuclear physics , electron
Respiratory motion artifacts in positron emission tomography (PET) imaging can alter lesion intensity profiles, and result in substantially reduced activity and contrast‐to‐noise ratios (CNRs). We propose a corrective algorithm, coined “retrospective stacking” (RS), to restore image quality without requiring additional scan time. Retrospective stacking uses b‐spline deformable image registration to combine amplitude‐binned PET data along the entire respiratory cycle into a single respiratory end point. We applied the method to a phantom model consisting of a small, hot vial oscillating within a warm background, as well as toFDG18 - PET images of a pancreatic and a liver patient. Comparisons were made using cross‐section visualizations, activity profiles, and CNRs within the region of interest. Retrospective stacking was found to properly restore the lesion location and intensity profile in all cases. In addition, RS provided CNR improvements up to three‐fold over gated images, and up to five‐fold over ungated data. These phantom and patient studies demonstrate that RS can correct for lesion motion and deformation, while substantially improving tumor visibility and background noise.