The objective of this work is to improve the diagnostic quality and reduce the radiation dose of computed tomography coronary angiography (CTCA) imaging by developing gating techniques based on signals derived from cardiac motion, rather than the currently used electrocardiogram (ECG), to more reliably trigger data acquisition during periods of cardiac quiescence. Because the ECG is an indication of electrical activity, it is a surrogate marker of the mechanical state of the heart. Therefore, gating based on a signal derived directly from cardiac motion using either echocardiography or seismocardiography (SCG) should prove better at detecting and predicting periods of cardiac quiescence. Improved gating would permit the use of CTCA in more instances to either replace or determine the necessity of invasive and expensive CCAs.
This work presents novel methods for detecting and predicting cardiac quiescence. Quiescence is detected as periods of minimal velocity from echocardiography, computed tomography (CT), and SCG. Identified quiescent periods are used to develop and evaluate techniques for predicting cardiac quiescence using echocardiography and SCG. Both echocardiography and SCG are shown to be more accurate for predicting quiescent periods than ECG. Additionally, the average motion during quiescent periods predicted by echocardiography and SCG is shown to be lower than those predicted using only ECG. Lastly, cardiac CT reconstructions from quiescent phases predicted by a commercial CT scanner were compared to the optimal quiescent phases calculated using the CT quiescence detection methods presented in this work. The diagnostic quality of the reconstructions from the optimal phases was found to be higher than that of the phases predicted by the CT scanner, suggesting that there is the potential for marked improvement in CTCA performance through more accurate cardiac gating.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/52242 |
| Date | 27 August 2014 |
| Creators | Wick, Carson A. |
| Contributors | McClellan, James H. |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
| Format | application/pdf |
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