4D-PET reconstruction using a spline-residue model with spatial and temporal roughness penalties



Ralli, George P, Chappell, Michael A, McGowan, Daniel R, Sharma, Ricky A, Higgins, Geoff S and Fenwick, John D
(2018) 4D-PET reconstruction using a spline-residue model with spatial and temporal roughness penalties. Physics in Medicine and Biology, 63 (9).

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Abstract

Institute of Physics and Engineering in Medicine PAPER • THE FOLLOWING ARTICLE ISOPEN ACCESS 4D-PET reconstruction using a spline-residue model with spatial and temporal roughness penalties George P Ralli1,6, Michael A Chappell2, Daniel R McGowan1,3, Ricky A Sharma4, Geoff S Higgins1 and John D Fenwick5 Published 4 May 2018 • © 2018 Institute of Physics and Engineering in Medicine Physics in Medicine & Biology, Volume 63, Number 9 DownloadArticle PDF Figures References Download PDF 1095 Total downloads 11 citation on Dimensions. Turn on MathJax Share this article Share this content via email Share on Facebook Share on Twitter Share on Google+ Share on Mendeley Hide article information Author e-mails george.ralli@oncology.ox.ac.uk Author affiliations 1 Department of Oncology, University of Oxford, Old Road Campus Research Building, Roosevelt Drive, Oxford OX3 7DQ, United Kingdom 2 Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Old Road Campus Research Building, Roosevelt Drive, Oxford OX3 7DQ, United Kingdom 3 Radiation Physics and Protection, Oxford University Hospitals NHS Foundation Trust, Churchill Hospital, Oxford OX3 7LE, United Kingdom 4 NIHR University College London Hospitals Biomedical Research Centre, UCL Cancer Institute, University College London, 72 Huntley Street, London WC1E 6DD, United Kingdom 5 Institute of Translational Medicine, University of Liverpool, UCD Block, Royal Liverpool University Hospital, Daulby Street, Liverpool L69 3GA, United Kingdom 6 Author to whom any correspondence should be addressed. ORCID iDs George P Ralli https://orcid.org/0000-0002-0119-050X Michael A Chappell https://orcid.org/0000-0003-1802-4214 Daniel R McGowan https://orcid.org/0000-0002-6880-5687 Ricky A Sharma https://orcid.org/0000-0002-4873-9918 Geoff S Higgins https://orcid.org/0000-0003-3072-909X Dates Received 18 December 2017 Accepted 4 April 2018 Accepted Manuscript online 4 April 2018 Published 4 May 2018 Check for updates using Crossmark Citation George P Ralli et al 2018 Phys. Med. Biol. 63 095013 Create citation alert DOI https://doi.org/10.1088/1361-6560/aabb62 Buy this article in print Journal RSS feed Sign up for new issue notifications Abstract 4D reconstruction of dynamic positron emission tomography (dPET) data can improve the signal-to-noise ratio in reconstructed image sequences by fitting smooth temporal functions to the voxel time-activity-curves (TACs) during the reconstruction, though the optimal choice of function remains an open question. We propose a spline-residue model, which describes TACs as weighted sums of convolutions of the arterial input function with cubic B-spline basis functions. Convolution with the input function constrains the spline-residue model at early time-points, potentially enhancing noise suppression in early time-frames, while still allowing a wide range of TAC descriptions over the entire imaged time-course, thus limiting bias. Spline-residue based 4D-reconstruction is compared to that of a conventional (non-4D) maximum a posteriori (MAP) algorithm, and to 4D-reconstructions based on adaptive-knot cubic B-splines, the spectral model and an irreversible two-tissue compartment ('2C3K') model. 4D reconstructions were carried out using a nested-MAP algorithm including spatial and temporal roughness penalties. The algorithms were tested using Monte-Carlo simulated scanner data, generated for a digital thoracic phantom with uptake kinetics based on a dynamic [18F]-Fluromisonidazole scan of a non-small cell lung cancer patient. For every algorithm, parametric maps were calculated by fitting each voxel TAC within a sub-region of the reconstructed images with the 2C3K model. Compared to conventional MAP reconstruction, spline-residue-based 4D reconstruction achieved  >50% improvements for five of the eight combinations of the four kinetics parameters for which parametric maps were created with the bias and noise measures used to analyse them, and produced better results for 5/8 combinations than any of the other reconstruction algorithms studied, while spectral model-based 4D reconstruction produced the best results for 2/8. 2C3K model-based 4D reconstruction generated the most biased parametric maps. Inclusion of a temporal roughness penalty function improved the performance of 4D reconstruction based on the cubic B-spline, spectral and spline-residue models.

Item Type: Article
Uncontrolled Keywords: dynamic PET, image reconstruction, kinetic modelling, regularization
Depositing User: Symplectic Admin
Date Deposited: 09 May 2018 09:49
Last Modified: 02 Dec 2021 08:20
DOI: 10.1088/1361-6560/aabb62
Open Access URL: http://iopscience.iop.org/article/10.1088/1361-656...
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URI: https://livrepository.liverpool.ac.uk/id/eprint/3021107