TY - GEN
T1 - PET-driven respiratory phase tracking and self-gating of PET data
T2 - 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017
AU - Karakatsanis, Nicolas A.
AU - Robson, Philip M.
AU - Dweck, Marc R.
AU - Trivieri, Maria G.
AU - Calcagno, Claudia
AU - Mani, Venkatesh
AU - Faul, David D.
AU - Tsoumpas, Charalampos
AU - Fayad, Zahi A.
N1 - Funding Information:
The authors would like to gratefully acknowledge support by National Institutes of Health NIH/NHLBI R01HL071021 grant.
Funding Information:
Manuscript received May 1st, 2017. This work was supported by NIH/NHLBI R01HL071021 grant. N. A. Karakatsanis is with the Division of Radiopharmaceutical Sciences, Department of Radiology, Weill Cornell Medical College, Cornell University, New York, NY, USA (e-mail: nak2032@med.cornell.edu) N. A. Karakatsanis, P M Robson, M. G. Trivieri, C. Calcagno, V. Mani and Z. A. Fayad are with the Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA. M. R. Dweck is with the University of Edinburgh, Edinburgh, UK D. D. Faul is with Siemens Healthineers, New York, NY, USA C. Tsoumpas is with the Division of Biomedical Imaging, School of Medicine, University of Leeds, Leeds, UK
Publisher Copyright:
© 2017 IEEE.
PY - 2018/11/12
Y1 - 2018/11/12
N2 - The advent of cardiovascular PET/MR in clinic may offer superior motion compensation capabilities by exploiting the non-ionizing nature of MR to sufficiently track and model respiratory and cardiac motion at high spatial resolution. However, the estimated motion models need to be continuously driven by the respiratory and cardiac motion phase for the accurate motion correction of the PET and MR data, thereby demonstrating the need for constant cardio-respiratory phase tracking throughout the entire scan period. Although MR-based continuous monitoring of cardio-respiratory phase is possible, it could reserve valuable time from other diagnostic MR sequences, thus diminishing PET/MR clinical potential. In this study, we validate a readily applicable in clinic PET list-mode (LM) datadriven respiratory phase extraction method to enable robust respiratory self-gating of PET data. The method relies on the hypothesis that for certain tracers the total LM PET counts can be sensitive to the periodic movement of hot or cold activity regions in and out of the PET field of view during breathing. The respiratory phase is tracked by continuously monitoring the total LM counts temporal profile, after smoothing with moving average filters (MAFs) to automatically correct for deep breath hold and drifting patterns. Subsequently the phase is used to drive the self-gating of the PET data into five respiratory gates and a special breath-hold gate. The period of the respiratory phase extracted with our proposed method matched well with the expected period of normal human breathing. Moreover, the automatically identified irregular LM PET count patterns corresponded in time to breath-hold MR acquisitions. The clinical application of the proposed method on our cardiovascular PET/MR studies demonstrated feasibility, while quantitative assessment of 18F-NaF coronary lesions detectability suggested a 10% improvement in lesion contrast and contrast-tonoise scores for the self-gated PET images.
AB - The advent of cardiovascular PET/MR in clinic may offer superior motion compensation capabilities by exploiting the non-ionizing nature of MR to sufficiently track and model respiratory and cardiac motion at high spatial resolution. However, the estimated motion models need to be continuously driven by the respiratory and cardiac motion phase for the accurate motion correction of the PET and MR data, thereby demonstrating the need for constant cardio-respiratory phase tracking throughout the entire scan period. Although MR-based continuous monitoring of cardio-respiratory phase is possible, it could reserve valuable time from other diagnostic MR sequences, thus diminishing PET/MR clinical potential. In this study, we validate a readily applicable in clinic PET list-mode (LM) datadriven respiratory phase extraction method to enable robust respiratory self-gating of PET data. The method relies on the hypothesis that for certain tracers the total LM PET counts can be sensitive to the periodic movement of hot or cold activity regions in and out of the PET field of view during breathing. The respiratory phase is tracked by continuously monitoring the total LM counts temporal profile, after smoothing with moving average filters (MAFs) to automatically correct for deep breath hold and drifting patterns. Subsequently the phase is used to drive the self-gating of the PET data into five respiratory gates and a special breath-hold gate. The period of the respiratory phase extracted with our proposed method matched well with the expected period of normal human breathing. Moreover, the automatically identified irregular LM PET count patterns corresponded in time to breath-hold MR acquisitions. The clinical application of the proposed method on our cardiovascular PET/MR studies demonstrated feasibility, while quantitative assessment of 18F-NaF coronary lesions detectability suggested a 10% improvement in lesion contrast and contrast-tonoise scores for the self-gated PET images.
UR - http://www.scopus.com/inward/record.url?scp=85058433573&partnerID=8YFLogxK
U2 - 10.1109/NSSMIC.2017.8532939
DO - 10.1109/NSSMIC.2017.8532939
M3 - Conference contribution
AN - SCOPUS:85058433573
T3 - 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017 - Conference Proceedings
BT - 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017 - Conference Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 21 October 2017 through 28 October 2017
ER -