BACKGROUND: A projection-based method of intrinsic cardiac gating in small-animal computed tomography imaging is presented. METHODS AND RESULTS: In this method, which operates without external ECG monitoring, the gating reference signal is derived from the raw data of the computed tomography projections. After filtering, the derived gating reference signal is used to rearrange the projection images retrospectively into data sets representing different time points in the cardiac cycle during expiration. These time-stamped projection images are then used for tomographic reconstruction of different phases of the cardiac cycle. Intrinsic gating was evaluated in mice and rats and compared with extrinsic retrospective gating. An excellent agreement was achieved between ECG-derived gating signal and self-gating signal (coverage probability for a difference between the 2 measurements to be less than 5 ms was 89.2% in mice and 85.9% in rats). Functional parameters (ventricular volumes and ejection fraction) obtained from the intrinsic and the extrinsic data sets were not significantly different. The ease of use and reliability of intrinsic gating were demonstrated via a chemical stress test on 2 mice, in which the system performed flawlessly despite an increased heart rate. Because of intrinsic gating, the image quality was improved to the extent that even the coronary arteries of mice could be visualized in vivo despite a heart rate approaching 430 bpm. Feasibility of intrinsic gating for functional imaging and assessment of cardiac wall motion abnormalities was successfully tested in a mouse model of myocardial infarction. CONCLUSIONS: Our results demonstrate that self-gating using advanced software postprocessing of projection data promises to be a valuable tool for rodent computed tomography imaging and renders ECG gating with external electrodes superfluous.
BACKGROUND: A projection-based method of intrinsic cardiac gating in small-animal computed tomography imaging is presented. METHODS AND RESULTS: In this method, which operates without external ECG monitoring, the gating reference signal is derived from the raw data of the computed tomography projections. After filtering, the derived gating reference signal is used to rearrange the projection images retrospectively into data sets representing different time points in the cardiac cycle during expiration. These time-stamped projection images are then used for tomographic reconstruction of different phases of the cardiac cycle. Intrinsic gating was evaluated in mice and rats and compared with extrinsic retrospective gating. An excellent agreement was achieved between ECG-derived gating signal and self-gating signal (coverage probability for a difference between the 2 measurements to be less than 5 ms was 89.2% in mice and 85.9% in rats). Functional parameters (ventricular volumes and ejection fraction) obtained from the intrinsic and the extrinsic data sets were not significantly different. The ease of use and reliability of intrinsic gating were demonstrated via a chemical stress test on 2 mice, in which the system performed flawlessly despite an increased heart rate. Because of intrinsic gating, the image quality was improved to the extent that even the coronary arteries of mice could be visualized in vivo despite a heart rate approaching 430 bpm. Feasibility of intrinsic gating for functional imaging and assessment of cardiac wall motion abnormalities was successfully tested in a mouse model of myocardial infarction. CONCLUSIONS: Our results demonstrate that self-gating using advanced software postprocessing of projection data promises to be a valuable tool for rodent computed tomography imaging and renders ECG gating with external electrodes superfluous.
Authors: Russell H Knutsen; Leah M Gober; Joseph R Sukinik; Danielle R Donahue; Elise K Kronquist; Mark D Levin; Sean E McLean; Beth A Kozel Journal: J Vis Exp Date: 2020-06-20 Impact factor: 1.355
Authors: Elise K Kronquist; Maninder Kaur; Leah M Gober; Russell H Knutsen; Yi-Ping Fu; Zu-Xi Yu; Danielle R Donahue; Marcus Y Chen; Sharon Osgood; Neelam Raja; Mark D Levin; Amisha Barochia; Beth A Kozel Journal: Diagnostics (Basel) Date: 2022-06-10
Authors: Sandeep Bhat; Irina V Larina; Kirill V Larin; Mary E Dickinson; Michael Liebling Journal: IEEE Trans Med Imaging Date: 2012-12-04 Impact factor: 10.048
Authors: Claudio Vinegoni; Sungon Lee; Paolo Fumene Feruglio; Ralph Weissleder Journal: IEEE J Sel Top Quantum Electron Date: 2014-03 Impact factor: 4.544
Authors: Gitsios Gitsioudis; Maximilian Nunninger; Anna Missiou; Peter Wolf; Hugo A Katus; Grigorios Korosoglou Journal: J Thorac Dis Date: 2019-11 Impact factor: 2.895