Evaluation of PET List Data-driven Gated Motion Correction Technique Applied in Lung Tumors

Abstract Purpose PET/CT is an important tool for tumor staging or evaluation of treatment response, especially for lung tumors. However, due to patients' free-breathing, the static PET image could be blurred, resulting in decreasing in image quality and incorrect quantitative values. The purpose of this study was to evaluate whether the Q.Static scan mode with the novel PET list data-driven gated (DDG) technique decreases the lesion blurring problems in lung cancer patients. Methods 194 patients with lung tumors were retrospectively reviewed. DDG Q.Static scan mode was set with 3 beds to cover the whole chest and the upper abdomen in their routine PET/CT scans. It was activated automatically when sensed significant respiratory motion. Routine reconstruction algorithm was applied to the data. Only those lesions located in the motioncorrected areas were measured and calculated for statistics. Results There were 124 out of 194 patients whose acquisition beds at least one bed activated the DDG Q.Static procedure. However, only 49 out of 124 patients showed lesions in their activated beds. Compared to noncorrection data, DDG Q.Static data showed improved accuracy by increasing SUVmax and SUVmean by 8.52% (9.20±5.42 to 9.74±5.42) and 8.65% (6.11±3.68 to 6.48±3.68). And, MTV was reduced from 6.54±8.58 to 5.55±7.33 (14.79% reduction). For subjective image quality, DDG Q.Static data was scored higher than noncorrection data. Conclusions This study demonstrated that both quantitative values and image quality were improved after correction. The DDG Q.Static technique provided an easier way to correct motion artifacts in PET/CT scans.