Zugriffsnummer 44633
Dokumenttyp Zeitschriftenartikel Open Access Hybrid
Peer Review mit Peer Review
Sprache Englisch
Titel Flexible numerical simulation framework for dynamic PET-MR data
Autor(in); Institution
Mayer, Johannes; 8.1, Biomedizinische Magnetresonanz, PTB-Berlin
Brown, R.; Institute of Nuclear Medicine, University College London, London, UK
Thielemans, K.; Institute of Nuclear Medicine, University College London, London, UK
Ovtchinnikov, E.; Scientific Computing Department, Science and Technology Facilities Council, RAL, Didcot, UK
Pasca, E.; Scientific Computing Department, Science and Technology Facilities Council, RAL, Didcot, UK
Atkinson, D.; Centre for Medical Imaging, University College London, London, UK
Gillman, A.; Australian e-Health Research Centre, CSIRO, Brisbane, AUSTRALIA
Marsden, P.; School of Biomedical Imaging Sciences, King’s College London, London, UK
Ippoliti, M.; Radiology, Charite Universitätsmedizin Berlin, Berlin, GERMANY
Makowski, M.; Radiology, Charite Universitätsmedizin Berlin, Berlin, GERMANY
Schäffter, Tobias; 8, Medizinphysik und metrologische Informationstechnik, PTB-Berlin
Kolbitsch, Christoph; 8.1, Biomedizinische Magnetresonanz, PTB-Berlin
Quelle/Jahr Physics in Medicine and Biology: 65 (2020), 14, 17 S.
Artikelnummer 145003
ISSN 0031-9155 (PRINT) ; 1361-6560 (ONLINE)
DOI
Verlag Bristol: IOP
Zusammenfassung This paper presents a simulation framework for dynamic PET-MR. The main focus of this framework is to provide motion-resolved MR and PET data and ground truth motion information. This can be used in the optimisation and quantitative evaluation of image registration and in assessing the error propagation due to inaccuracies in motion estimation in complex motion-compensated reconstruction algorithms. Contrast and tracer kinetics can also be simulated and are available as ground truth information. To closely emulate medical examination, input and output of the simulation are files in standardised open-source raw data formats. This enables the use of existing raw data as a template input and ensures seamless integration of the output into existing reconstruction pipelines. The proposed framework was validated in PET-MR and image registration applications. It was used to simulate a FDG-PET-MR scan with cardiac and respiratory motion. Ground truth motion information could be utilised to optimise parameters for PET and synergistic PET-MR image registration. In addition, a free-breathing dynamic contrast enhancement (DCE) abdominal scan of a patient with hepatic lesions was simulated. In order to correct for breathing motion, a motion-corrected image reconstruction scheme was used and a Toft's model was fit to the DCE data to obtain quantitative DCE-MRI parameters. Utilising the ground truth motion information, the dependency of quantitative DCE-MR images on the accuracy of the motion estimation was evaluated. We demonstrated that respiratory motion had to be available with an average accuracy of at least the spatial resolution of the DCE-MR images in order to ensure an improvement in lesions visualisation and quantification compared to no motion correction. The proposed framework provides a valuable tool with a wide range of scientific PET and MR applications and will be available as part of the open-source project Synergistic Image Reconstruction Framework (SIRF).
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Rechteinformation CC BY 3.0 ; Creative Commons Attribution 3.0 License
Themenbereich der Metrologie Metrologie in der Medizin

Zitierung

Mayer, J., Brown, R., Thielemans, K., Ovtchinnikov, E., Pasca, E., Atkinson, D., Gillman, A., Marsden, P., Ippoliti, M., Makowski, M., Schäffter, T., & Kolbitsch, C. (2020). Flexible numerical simulation framework for dynamic PET-MR data. Physics in Medicine and Biology, 65(14), 17 S. https://doi.org/10.1088/1361-6560/ab7eee

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