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J Med Imaging (Bellingham). 2016 Apr;3(2):024001. doi: 10.1117/1.JMI.3.2.024001. Epub 2016 May 2.

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

Author information

1
University of Washington , Department of Radiology, Seattle, Washington 98195, United States.
2
The University of Chicago , Department of Radiology, Chicago, Illinois 60637, United States.

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 [Formula: see text]) compared to linearly interpreted static assessment (0.45 to [Formula: see text]), 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 ([Formula: see text]) in stratifying patients, especially for larger patients and lower contrast doses [area under the curve [Formula: see text] 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.

KEYWORDS:

cardiac computed tomography; computed tomography perfusion; dynamic computed tomography; kinetic modeling; perfusion imaging

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