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Clinical Impact of Respiratory Motion Correction in Simultaneous PET/MR with a Joint PET/MR Predictive Motion Model

Manber, R; Thielemans, K; Hutton, BF; Wan, S; Fraioli, F; Barnes, A; Ourselin, S; ... Atkinson, D; + view all (2018) Clinical Impact of Respiratory Motion Correction in Simultaneous PET/MR with a Joint PET/MR Predictive Motion Model. The Journal of Nuclear Medicine , 59 (9) pp. 1467-1473. 10.2967/jnumed.117.191460. Green open access

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Abstract

In Positron Emission Tomography (PET) imaging, patient motion due to respiration can lead to artefacts and blurring, in addition to quantification errors. The integration of PET imaging with Magnetic Resonance (MR) imaging in PET/MR scanners provides spatially aligned complementary clinical information, and allows the use of high spatial resolution and high contrast MR images to monitor and correct motion-corrupted PET data. We validate our PET respiratory motion correction methodology based on a joint PET-MR motion model, on a patient cohort, showing it can improve lesion detectability and quantitation, and reduce image artefacts. METHODS: We apply our motion correction methodology on 42 clinical PET-MR patient datasets, using multiple tracers and multiple organ locations, containing 162 PET-avid lesions. Quantitative changes are calculated using Standardised Uptake Value (SUV) changes in avid lesions. Lesion detectability changes are explored with a study where two radiologists identify lesions or 'hot spots', providing confidence levels, in uncorrected and motion-corrected images. RESULTS: Mean increases of 12.4% for SUV_peak and 17.6% for SUV_max following motion correction were found. In the detectability study, an increase in confidence scores for detecting avid lesions is shown, with a mean score of 2.67 rising to 3.01 (out of 4) after motion correction, and a detection rate of 74% rising to 84%. Of 162 confirmed lesions, 49 lesions showed an increase in all three metrics SUV_peak, SUV_max and combined reader confidence scores, whilst only two lesions showed a decrease. We also present a number of clinical case studies, demonstrating the effect respiratory motion correction of PET data can have on patient management, with increased numbers of lesions detected, improved lesion sharpness and localisation, as well as reduced attenuation-based artefacts. CONCLUSION: We demonstrate significant improvements in quantification and detection of PET-avid lesions, with specific case study examples showing where motion correction has the potential to have an effect on patient diagnosis or care.

Type: Article
Title: Clinical Impact of Respiratory Motion Correction in Simultaneous PET/MR with a Joint PET/MR Predictive Motion Model
Location: United States
Open access status: An open access version is available from UCL Discovery
DOI: 10.2967/jnumed.117.191460
Publisher version: http://dx.doi.org/10.2967/jnumed.117.191460
Language: English
Additional information: Immediate Open Access: Creative Commons Attribution 4.0 International License (CC BY) allows users to share and adapt with attribution, excluding materials credited to previous publications. License: https://creativecommons.org/licenses/by/4.0/.
Keywords: Image Reconstruction, Lesion Quantification, Lesions detection, Motion Correction, PET/MR, PET/MRI, Respiratory
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine > Metabolism and Experi Therapeutics
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10045345
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