Improved Alignment of PET and CT Images in Whole-Body PET/CT in Cases of Respiratory Motion During CT

Abstract

Respiratory motion during the CT and PET parts of a PET/CT scan leads to imperfect alignment of anatomical features seen by the two modalities. In this work, we concentrate on the effects of motion during CT. We propose a novel approach for improving the alignment. Methods: Respiratory waveform data were gathered during the CT and PET parts of 28 PET/CT scans of cancer patients with 40 lesions up to 3 cm size in the lung or upper abdomen. PET list-mode data were reconstructed by three reconstruction methods: PET/static, PET/EX or end of expiration (OncoFreeze), and a novel PET/matched method that used both waveforms. The three methods were compared. The distance between tumor positions in PET and CT were characterized in visual interpretation by physicians as well as quantitatively. Tumor standardized uptake values (SUV_max and SUVpeak) were determined relative to SUV based on the static method. Image noise was evaluated in the liver and compared to PET/static. Results: In visual interpretation, the rate of good alignment was 13/21, 13/23 and 18/21 for PET/static, PET/EX and PET/matched methods, respectively, and the mean PET-CT distances were 3.5, 5.1 and 2.8 mm. In visual comparison with PET/EX, the rate of good alignment was increased in 1/10 and 7/10 cases for PET/static and PET/matched. SUV_max was on average 21% higher than PET/static when either PET/EX or PET/matched was used. SUVpeak was 12% higher. Image noise in the liver was 15% higher than static for the PET/EX method, and 40% higher for PET/matched; that is, noise was much lower than in gated PET. Conclusion: Acquiring respiratory waveforms both in PET (as in the current state of the art) and in CT (an unusual key step in this approach) has the potential to improve the alignment of PET and CT images. A proposed method for using this information was tested. Improved alignment was demonstrated.