Image Processing

Sinogram smoothing techniques for myocardial blood flow estimation from dose-reduced dynamic computed tomography

[+] Author Affiliations
Dimple Modgil

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

Adam M. Alessio

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

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

Michael D. Bindschadler

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

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

Patrick J. La Rivière

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

J. Med. Imag. 1(3), 034004 (Nov 03, 2014). doi:10.1117/1.JMI.1.3.034004
History: Received May 29, 2014; Revised September 12, 2014; Accepted September 19, 2014
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Abstract.  Dynamic contrast-enhanced computed tomography (CT) could provide an accurate and widely available technique for myocardial blood flow (MBF) estimation to aid in the diagnosis and treatment of coronary artery disease. However, one of its primary limitations is the radiation dose imparted to the patient. We are exploring techniques to reduce the patient dose by either reducing the tube current or by reducing the number of temporal frames in the dynamic CT sequence. Both of these dose reduction techniques result in noisy data. In order to extract the MBF information from the noisy acquisitions, we have explored several data-domain smoothing techniques. In this work, we investigate two specific smoothing techniques: the sinogram restoration technique in both the spatial and temporal domains and the use of the Karhunen–Loeve (KL) transform to provide temporal smoothing in the sinogram domain. The KL transform smoothing technique has been previously applied to dynamic image sequences in positron emission tomography. We apply a quantitative two-compartment blood flow model to estimate MBF from the time-attenuation curves and determine which smoothing method provides the most accurate MBF estimates in a series of simulations of different dose levels, dynamic contrast-enhanced cardiac CT acquisitions. As measured by root mean square percentage error (% RMSE) in MBF estimates, sinogram smoothing generally provides the best MBF estimates except for the cases of the lowest simulated dose levels (tube current=25mAs, 2 or 3 s temporal spacing), where the KL transform method provides the best MBF estimates. The KL transform technique provides improved MBF estimates compared to conventional processing only at very low doses (<7mSv). Results suggest that the proposed smoothing techniques could provide high fidelity MBF information and allow for substantial radiation dose savings.

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© 2014 Society of Photo-Optical Instrumentation Engineers

Citation

Dimple Modgil ; Adam M. Alessio ; Michael D. Bindschadler and Patrick J. La Rivière
"Sinogram smoothing techniques for myocardial blood flow estimation from dose-reduced dynamic computed tomography", J. Med. Imag. 1(3), 034004 (Nov 03, 2014). ; http://dx.doi.org/10.1117/1.JMI.1.3.034004


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