PET-driven respiratory phase tracking and self-gating of PET data: clinical demonstration of enhanced lesion detectability in cardiovascular PET/MRI

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.