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

Michael D. Bindschadler; Dimple Modgil; Kelley R. Branch M.D.; Patrick J. La Rivière; Adam M. Alessio

doi:10.1117/1.JMI.3.2.024001

2 May 2016 Evaluation of static and dynamic perfusion cardiac computed tomography for quantitation and classification tasks

Michael D. Bindschadler, Dimple Modgil, Kelley R. Branch M.D., Patrick J. La Rivière, Adam M. Alessio

Author Affiliations +

Journal of Medical Imaging, Vol. 3, Issue 2, 024001 (May 2016). https://doi.org/10.1117/1.JMI.3.2.024001

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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Michael D. Bindschadler, Dimple Modgil, Kelley R. Branch M.D., Patrick J. La Rivière, and Adam M. Alessio "Evaluation of static and dynamic perfusion cardiac computed tomography for quantitation and classification tasks," Journal of Medical Imaging 3(2), 024001 (2 May 2016). https://doi.org/10.1117/1.JMI.3.2.024001

Published: 2 May 2016

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