Abstract
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Objectives Respiratory and other types of motion in positron emission tomography leads to blurring of reconstructed images and attenuation-related errors in quantitative PET data. The aim of this study is to develop a motion correction technique using list-mode data and advanced image registration techniques without the use of external or tracking device and preserving all of the acquisition data without discarding any subset of that data as is done with other gating techniques. This abstract has been accepted for poster presentation at RSNA 2010. It is being resubmitted again after further work has been performed to show increased SUVmax and average SUV values for motion corrected lung lesions with increased number of patient's data.
Methods Data were acquired in “list mode” during a three minute one bed position(thorax)acquisition of patients with solitary lung lesions. The acquisition of list-mode data was performed utilizing a Philips Gemini TF PET/CT Scanner equipped with time of flight hardware and software. The scanner utilized is a full ring LYSO-based scanner operating in 3-dimensional mode with an axial field of view of 18 cm and a diameter of 90 cm. The list mode data were reconstructed into 180 one second “frames” from the original three minute acquisition. Each individual frame was then registered utilizing both non-rigid and rigid approaches utilizing a registration technique optimized for these images.
Results The methods we used successfully minimized the deleterious impact of respiratory motion and resulted in improved image quality, registration and increased SUVmax and average SUV values for the lung lesions.
Conclusions Our pilot study will demonstrated that by simply categorizing the PET list mode stream on a frame-by frame basis and then registering the resulting image with the CT examination in the near future, it is feasible to correct for respiratory motion without the use of tracking devic