ORIGINAL RESEARCH article
Front. Nucl. Med.
Sec. Physics and Data Analysis
This article is part of the Research TopicRapid Image ReconstructionView all 3 articles
MR-Guided Reconstruction of PET Data in Spinal Cord PET/MRI
Provisionally accepted
Eve Lennie1
Charalampos Tsoumpas2
Nigel Hoggard1
Tom Jenkins3
Matthew Spangler-Bickell4
Steven Sourbron1*- 1The University of Sheffield Academic Unit of Radiology, Sheffield, United Kingdom
- 2Universitair Medisch Centrum Groningen, Groningen, Netherlands
- 3Joondalup Health Campus, Joondalup, Australia
- 4GE Precision Healthcare LLC, Waukesha, United States
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Accurate PET reconstruction in spinal cord PET/MRI is challenging due to the small size of the structure and interference from background activity. The aim of this study was to establish whether MR-guided PET reconstruction can improve the accuracy of measured uptake in the spinal cord. Specifically we investigate the hybrid kernel expectation maximisation (HKEM) algorithm on a digital anthropomorphic phantom (XNAT), and an implementation of a modified asymmetric Bowsher's prior incorporating both PET and MR data on clinical test cases. These methods are evaluated by comparison against commonly used algorithms OSEM and Q.Clear. The results demonstrated that the two algorithms lead to an increase in measured 18F-FDG PET tracer uptake in the spinal cord. Comparison to ground truth indicates that the improvement is insufficient to remove the bias in this small structure. With care taken to optimise for the desired application, novel PET image reconstruction algorithms using PET and MR data to inform iterative image updates lead to improved quantification and improved image quality compared to OSEM. Further work is needed to investigate the optimal parameters and identify strategies to reduce residual bias.
Keywords: PET/MRI, positron emission tomography, Magnetic Resonance Imaging, Spinal Cord, Neurology, Neuro-imaging, quantification
Received: 15 Sep 2025; Accepted: 27 Nov 2025.
Copyright: © 2025 Lennie, Tsoumpas, Hoggard, Jenkins, Spangler-Bickell and Sourbron. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Steven Sourbron
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