Share Email Print

Proceedings Paper

Performance comparison between static and dynamic cardiac CT on perfusion quantitation and patient classification tasks
Author(s): Michael Bindschadler; Dimple Modgil; Kelley R. Branch; Patrick J. La Riviere; Adam M. Alessio
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Cardiac CT acquisitions for perfusion assessment can be performed in a dynamic or static mode. In this simulation study, we evaluate the relative classification and quantification performance of these modes for assessing myocardial blood flow (MBF). In the dynamic method, a series of low dose cardiac CT acquisitions yields data on contrast bolus dynamics over time; these data are fit with a model to give a quantitative MBF estimate. In the static method, a single CT acquisition is obtained, and the relative CT numbers in the myocardium are used to infer perfusion states. The static method does not directly yield a quantitative estimate of MBF, but these estimates can be roughly approximated by introducing assumed linear relationships between CT number and MBF, consistent with the ways such images are typically visually interpreted. Data obtained by either method may be used for a variety of clinical tasks, including 1) stratifying patients into differing categories of ischemia and 2) using the quantitative MBF estimate directly to evaluate ischemic disease severity. Through simulations, we evaluate the performance on each of these tasks. The dynamic method has very low bias in MBF estimates, making it particularly suitable for quantitative estimation. At matched radiation dose levels, ROC analysis demonstrated that the static method, with its high bias but generally lower variance, has superior performance in stratifying patients, especially for larger patients.

Paper Details

Date Published: 18 March 2015
PDF: 6 pages
Proc. SPIE 9412, Medical Imaging 2015: Physics of Medical Imaging, 941224 (18 March 2015); doi: 10.1117/12.2082098
Show Author Affiliations
Michael Bindschadler, Univ. of Washington (United States)
Dimple Modgil, Univ. of Chicago (United States)
Kelley R. Branch, Univ. of Washington (United States)
Patrick J. La Riviere, Univ. of Chicago (United States)
Adam M. Alessio, Univ. of Washington (United States)

Published in SPIE Proceedings Vol. 9412:
Medical Imaging 2015: Physics of Medical Imaging
Christoph Hoeschen; Despina Kontos, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?