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Quiescent period respiratory gating for PET/CT
Author(s) -
Liu Chi,
Alessio Adam,
Pierce Larry,
Thielemans Kris,
Wollenweber Scott,
Ganin Alexander,
Kinahan Paul
Publication year - 2010
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 - 10.1118/1.3480508
Subject(s) - gating , nuclear medicine , histogram , noise (video) , medicine , computer science , artificial intelligence , physiology , image (mathematics)
Purpose: 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 and evaluated. 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 lesionSUV maxand the fraction of counts included in each gate as a surrogate for image noise. Results: For all the gating methods, image noise artifactually increasesSUV maxwhen 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 lesionSUV max. Compared to five‐bin phase gating, the QPG methods yield significantly larger fraction of counts with similarSUV maximprovement. Both QPG methods result in increased lesionSUV maxfor 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 betweenSUV maxand fraction of counts. The QPG methods for respiratory motion compensation could effectively improve tumor quantification with minimal noise increase.