Evaluation of a respiratory motion-corrected image reconstruction algorithm in 2-[18F]FDG and [68Ga]Ga-DOTA-NOC PET/CT: impacts on image quality and tumor quantification

Qing-Le Meng; Rui Yang; Run-Ze Wu; Lei Xu; Hao Liu; Gang Yang; Yun Dong; Feng Wang; Zhengguo Chen; Hongbing Jiang

doi:10.21037/qims-22-557

Evaluation of a respiratory motion-corrected image reconstruction algorithm in 2-[¹⁸F]FDG and [⁶⁸Ga]Ga-DOTA-NOC PET/CT: impacts on image quality and tumor quantification

Quant Imaging Med Surg. 2023 Jan 1;13(1):370-383. doi: 10.21037/qims-22-557. Epub 2022 Nov 21.

Authors

Qing-Le Meng^#¹, Rui Yang^#¹, Run-Ze Wu², Lei Xu¹, Hao Liu², Gang Yang², Yun Dong², Feng Wang¹, Zhengguo Chen³, Hongbing Jiang^{4

5}

Affiliations

¹ Department of Nuclear Medicine, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.
² United Imaging Healthcare, Shanghai, China.
³ National Health Commission Key Laboratory of Nuclear Technology Medical Transformation, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, China.
⁴ Department of Medical Equipment, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.
⁵ Nanjing Emergency Medical Center, Nanjing, China.

^# Contributed equally.

Abstract

Background: Respiratory motions may cause artifacts on positron emission tomography (PET) images that degrade image quality and quantification accuracy. This study aimed to evaluate the effect of a respiratory motion-corrected image reconstruction (MCIR) algorithm on image quality and tumor quantification compared with nongated/nonmotion-corrected reconstruction.

Methods: We used a phantom consisting of 5 motion spheres immersed in a chamber driven by a motor. The spheres and the background chamber were filled with 18F solution at a sphere-to-background ratio of 5:1. We enrolled 42 and 16 patients undergoing 2-deoxy-2-[¹⁸F]fluoro-D-glucose {2-[¹⁸F]FDG} and ⁶⁸Ga-labeled [1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid]-1-Nal3-octreotide {[⁶⁸Ga]Ga-DOTA-NOC} PET/computed tomography (CT) from whom 74 and 30 lesions were segmented, respectively. Three reconstructions were performed: data-driven gating-based motion correction (DDGMC), external vital signal module-based motion correction (VSMMC), and noncorrection reconstruction. The standardized uptake values (SUVs) and the volume of the spheres and the lesions were measured and compared among the 3 reconstruction groups. The image noise in the liver was measured, and the visual image quality of motion artifacts was scored by radiologists in the patient study.

Results: In the phantom study, the spheres' SUVs increased by 26-36%, and the volumes decreased by 35-38% in DDGMC and VSMMC compared with the noncorrection group. In the 2-[¹⁸F]FDG PET patient study, the lesions' SUVs had a median increase of 10.87-12.65% while the volumes had a median decrease of 14.88-15.18% in DDGMC and VSMMC compared with those of noncorrection. In the [⁶⁸Ga]Ga-DOTA-NOC PET patient study, the lesions' SUVs increased by 14.23-15.45%, and the volumes decreased by 19.11-20.94% in DDGMC and VSMMC. The image noise in the liver was equal between the DDGMC, VSMMC, and noncorrection groups. Radiologists found improved image quality in more than 45% of the cases in DDGMC and VSMMC compared with the noncorrection group. There was no statistically significant difference in SUVs, volumes, or visual image quality scores between DDGMC and VSMMC.

Conclusions: MCIR improves tumor quantification accuracy and visual image quality by reducing respiratory motion artifacts without compromised image noise performance or elongated acquisition time in 2-[¹⁸F]FDG and [⁶⁸Ga]Ga-DOTA-NOC PET/CT tumor imaging. The performance of DDG-driven MCIR is as good as that of the external device-driven solution.

Keywords: Positron emission tomography/computed tomography (PET/CT); elastic respiratory motion correction; image quality; motion-corrected image reconstruction (MCIR); tumor quantification.