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Publication Detail
Clinical Impact of Respiratory Motion Correction in Simultaneous PET/MR with a Joint PET/MR Predictive Motion Model.
  • Publication Type:
    Journal article
  • Publication Sub Type:
  • Authors:
    Manber R, Thielemans K, Hutton BF, Wan S, Fraioli F, Barnes A, Ourselin S, Arridge S, Atkinson D
  • Publication date:
  • Journal:
    Journal of nuclear medicine : official publication, Society of Nuclear Medicine
  • Medium:
  • Status:
  • Print ISSN:
  • Language:
  • Addresses:
    University College London, United Kingdom.
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.
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