Utility of high-definition FDG-PET image reconstruction for lung cancer staging

Abstract

Background High-definition (HD) positron emission tomography (PET) image reconstruction is a new image reconstruction method based on the point spread function system, which improves the spatial resolution of the images. Purpose To compare the utility of HD reconstruction of PET images for staging lung cancer with that of conventional 2D ordered subset expectation maximization + Fourier rebinning (2D) reconstruction. Material and Methods Thirty-five lung cancer patients (24 men, 11 women; median age, 66 years) who underwent surgery after 18F-2-deoxy-fluoro-D-glucose (FDG)-PET-CT were studied. Their PET data were reconstructed with 2D and HD PET reconstruction algorithms. Two radiologists individually TNM staged both sets of images. They also evaluated the quality of the images and the diagnostic confidence that the images afforded them using 5-point scales. Results T, N, and M stages were correctly diagnosed on both the 2D and HD reconstructed images in 23 (66%), 25 (71%), and 30 (86%) of 35 cases, respectively. Overall TNM stage was correctly diagnosed on both types of reconstructed images in 23 cases (66%), underestimated in three (9%), and overestimated in nine (26%). No significant difference in T, N, or M stage or overall TNM stage was observed between the two reconstruction methods. However, the HD reconstructed images afforded a significantly higher level of diagnostic confidence during TNM staging than the 2D reconstructed images and were also of higher quality than the 2D reconstructed images. Conclusion Although HD reconstruction of FDG-PET images did not improve the diagnostic accuracy of lung cancer staging compared with 2D reconstruction, the quality of the HD reconstructed images and the diagnostic confidence level they afforded the radiologists were higher than those of the conventional 2D reconstructed images.