Comparison between two super-resolution implementations in PET imaging.

Super-resolution (SR) techniques are used in PET imaging to generate a high-resolution image by combining multiple low-resolution images that have been acquired from different points of view (POV). In this article, the authors propose a novel implementation of the SR technique whereby the required multiple low-resolution images are generated by shifting the reconstruction pixel grid during the image reconstruction process rather than being acquired from different POVs. The objective of this article is to compare the performances of the two SR implementations using theoretical and experimental studies. A mathematical framework is first provided to support the hypothesis that the two SR implementations have similar performance in current PET/CT scanners that use block detectors. Based on this framework, a simulation study, a point source study, and a NEMA/IEC phantom study were conducted to compare the performance of these two SR implementations with respect to contrast, resolution, noise, and SNR. For reference purposes, a comparison with a native reconstruction (NR) image using a high-resolution pixel grid was also performed. The mathematical framework showed that the two SR implementations are expected to achieve similar contrast and resolution but different noise contents. These results were confirmed by the simulation and experimental studies. The simulation study showed that the two SR implementations have an average contrast difference of 2.3%, while the point source study showed that their average differences in contrast and resolution were 0.5% and 1.2%, respectively. Comparisons between the SR and NR images for the point source study showed that the NR image exhibited averages of 30% and 8% lower contrast and resolution, respectively. The NEMA/IEC phantom study showed that the three images (two SR and NR) exhibited different noise structures. The SNR of the new SR implementation was, on average, 21.5% lower than the original implementation largely due to an increase in background noise, while the NR image had averages of 18.5% and 8% lower SNR and contrast, respectively, versus the two SR images. The new SR implementation can potentially replace the original SR approach in current PET scanners that use block detectors while maintaining similar contrast and resolution, but at a relatively lower SNR. A major advantage of the new SR implementation is its shorter overall scan duration which results in an increase in scanner throughput and a reduction in patient motion.

[1]  Magnus Dahlbom,et al.  Characterization of sampling schemes for whole body PET imaging , 1993 .

[2]  Michal Irani,et al.  Motion Analysis for Image Enhancement: Resolution, Occlusion, and Transparency , 1993, J. Vis. Commun. Image Represent..

[3]  Kunio Doi,et al.  Integrating PET and CT information to improve diagnostic accuracy for lung nodules: A semiautomatic computer-aided method. , 2006, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[4]  M C Gilardi,et al.  Using Deconvolution to Improve PET Spatial Resolution in OSEM Iterative Reconstruction , 2007, Methods of Information in Medicine.

[5]  Suleman Surti,et al.  Imaging characteristics of a 3-dimensional GSO whole-body PET camera. , 2004, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[6]  M. Casey,et al.  PET reconstruction with system matrix derived from point source measurements , 2004, IEEE Transactions on Nuclear Science.

[7]  M P Sandler,et al.  Evaluation of benign vs malignant hepatic lesions with positron emission tomography. , 1998, Archives of surgery.

[8]  Joel G. Rogers,et al.  A method for correcting the depth-of-interaction blurring in PET cameras , 1995, IEEE Trans. Medical Imaging.

[9]  Jonathan Goldin,et al.  Accuracy of PET/CT in characterization of solitary pulmonary lesions. , 2007, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[10]  S Grootoonk,et al.  Performance Evaluation of the Positron Scanner ECAT EXACT , 1992, Journal of computer assisted tomography.

[11]  George Starkschall,et al.  A novel platform simulating irregular motion to enhance assessment of respiration‐correlated radiation therapy procedures , 2005, Journal of applied clinical medical physics.

[12]  R Lecomte,et al.  Nonstationary scatter subtraction-restoration in high-resolution PET. , 1996, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[13]  G. Baselli,et al.  Improving PET image spatial resolution by experimental measurement of scanner blurring properties , 2003, Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439).

[14]  P.M. Bloomfield,et al.  Rigid-body transformation of list-mode projection data for respiratory motion correction in cardiac PET , 2005, 2003 IEEE Nuclear Science Symposium. Conference Record (IEEE Cat. No.03CH37515).

[15]  J. M. Ollinger,et al.  Positron Emission Tomography , 2018, Handbook of Small Animal Imaging.

[16]  Thomas K. Lewellen,et al.  Modeling and incorporation of system response functions in 3-D whole body PET , 2006, IEEE Transactions on Medical Imaging.

[17]  Michael D. Thomas,et al.  Quality assurance: Fundamental reproducibility tests for 3D treatment‐planning systems , 2005, Journal of applied clinical medical physics.

[18]  G Brix,et al.  Performance evaluation of a whole-body PET scanner using the NEMA protocol. National Electrical Manufacturers Association. , 1997, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[19]  Roberta Matheoud,et al.  Performance characteristics obtained for a new 3-dimensional lutetium oxyorthosilicate-based whole-body PET/CT scanner with the National Electrical Manufacturers Association NU 2-2001 standard. , 2005, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[20]  John A. Kennedy,et al.  Improved Image Fusion in PET/CT Using Hybrid Image Reconstruction and Super-Resolution , 2007, Int. J. Biomed. Imaging.

[21]  Haim Azhari,et al.  Super-resolution in PET imaging , 2006, IEEE Transactions on Medical Imaging.

[22]  D K Owens,et al.  Accuracy of positron emission tomography for diagnosis of pulmonary nodules and mass lesions: a meta-analysis. , 2001, JAMA.

[23]  Magnus Dahlbom,et al.  Implementation of true continuous bed motion in 2-D and 3-D whole-body PET scanning , 2001 .

[24]  B. Alfano,et al.  Imaging of adrenal tumors using FDG PET: comparison of benign and malignant lesions. , 1999, AJR. American journal of roentgenology.

[25]  Val J Lowe,et al.  NEMA NU 2-2001 performance measurements of an LYSO-based PET/CT system in 2D and 3D acquisition modes. , 2006, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[26]  Moon Gi Kang,et al.  Super-resolution image reconstruction: a technical overview , 2003, IEEE Signal Process. Mag..

[27]  J. H. Reed,et al.  Continuous bed motion acquisition on a whole body combined PET/CT system , 2002, 2002 IEEE Nuclear Science Symposium Conference Record.

[28]  Yoshiharu Yonekura,et al.  18F-FDG accumulation with PET for differentiation between benign and malignant lesions in the thorax. , 2003, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.