Quiescent period respiratory gating for PET/CT.
OBJECTIVE
To minimize respiratory motion artifacts, this work proposes quiescent period gating (QPG) methods that extract PET data from the end-expiration quiescent period and form a single PET frame with reduced motion and improved signal-to-noise properties.


METHODS
Two QPG methods are proposed andevaluated. Histogram-based quiescent period gating (H-QPG) extracts a fraction of PET data determined by a window of the respiratory displacement signal histogram. Cycle-based quiescent period gating (C-QPG) extracts data with a respiratory displacement signal below a specified threshold of the maximum amplitude of each individual respiratory cycle. Performances of both QPG methods were compared to ungated and five-bin phase-gated images across 21 FDG-PET/CT patient data sets containing 31 thorax and abdomen lesions as well as with computer simulations driven by 1295 different patient respiratory traces. Image quality was evaluated in terms of the lesion SUV(max) and the fraction of counts included in each gate as a surrogate for image noise.


RESULTS
For all the gating methods, image noise artifactually increases SUV(max) when the fraction of counts included in each gate is less than 50%. While simulation data show that H-QPG is superior to C-QPG, the H-QPG and C-QPG methods lead to similar quantification-noise tradeoffs in patient data. Compared to ungated images, both QPG methods yield significantly higher lesion SUV(max). Compared to five-bin phase gating, the QPG methods yield significantly larger fraction of counts with similar SUV(max) improvement. Both QPG methods result in increased lesion SUV(max) for patients whose lesions have longer quiescent periods.


CONCLUSIONS
Compared to ungated and phase-gated images, the QPG methods lead to images with less motion blurring and an improved compromise between SUV(max) and fraction of counts. The QPG methods for respiratory motion compensation could effectively improve tumor quantification with minimal noise increase.
Liu
Chi
C
Department of Radiology, University of Washington, Seattle, Washington 98195, USA. chi.liu@yale.edu
Alessio
Adam
A
Pierce
Larry
L
Thielemans
Kris
K
Wollenweber
Scott
S
Ganin
Alexander
A
Kinahan
Paul
P
D000368:Aged; D006801:Humans; D008875:Middle Aged; D049268:Positron-Emission Tomography / Q000379:methods*; D012119:Respiration; D055425:Respiratory-Gated Imaging Techniques / Q000379:methods*; D012146:Rest; D012189:Retrospective Studies; D014057:Tomography, X-Ray Computed / Q000379:methods*