Image Processing

Evaluation of static and dynamic perfusion cardiac computed tomography for quantitation and classification tasks

[+] Author Affiliations
Michael Bindschadler, Kelley R. Branch, Adam M. Alessio

University of Washington, Department of Radiology, Seattle, Washington 98195, United States

Dimple Modgil, Patrick J. La Riviere

The University of Chicago, Department of Radiology, Chicago, Illinois 60637, United States

J. Med. Imag. 3(2), 024001 (May 02, 2016). doi:10.1117/1.JMI.3.2.024001
History: Received September 8, 2015; Accepted March 24, 2016
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Abstract.  Cardiac computed tomography (CT) acquisitions for perfusion assessment can be performed in a dynamic or static mode. Either method may be used for a variety of clinical tasks, including (1) stratifying patients into categories of ischemia and (2) using a quantitative myocardial blood flow (MBF) estimate to evaluate disease severity. In this simulation study, we compare method performance on these classification and quantification tasks for matched radiation dose levels and for different flow states, patient sizes, and injected contrast levels. Under conditions simulated, the dynamic method has low bias in MBF estimates (0 to 0.1  ml/min/g) compared to linearly interpreted static assessment (0.45 to 0.48  ml/min/g), making it more suitable for quantitative estimation. At matched radiation dose levels, receiver operating characteristic analysis demonstrated that the static method, with its high bias but generally lower variance, had superior performance (p<0.05) in stratifying patients, especially for larger patients and lower contrast doses [area under the curve (AUC)=0.95 to 96 versus 0.86]. We also demonstrate that static assessment with a correctly tuned exponential relationship between the apparent CT number and MBF has superior quantification performance to static assessment with a linear relationship and to dynamic assessment. However, tuning the exponential relationship to the patient and scan characteristics will likely prove challenging. This study demonstrates that the selection and optimization of static or dynamic acquisition modes should depend on the specific clinical task.

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© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Michael Bindschadler ; Dimple Modgil ; Kelley R. Branch ; Patrick J. La Riviere and Adam M. Alessio
"Evaluation of static and dynamic perfusion cardiac computed tomography for quantitation and classification tasks", J. Med. Imag. 3(2), 024001 (May 02, 2016). ; http://dx.doi.org/10.1117/1.JMI.3.2.024001


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