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Proceedings Paper

Development of a phantom-based methodology for the assessment of quantification performance in CT
Author(s): Baiyu Chen; Ehsan Samei
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Paper Abstract

The quantification of lung nodule volume from CT images provides valuable information for cancer diagnosis and staging. However, the usefulness of quantification depends on its precision. Direct assessment of the volume quantification precision involves multiple steps and can become intractable for a multiplicity of protocols. To assess quantification precision efficiently, we developed a prediction model, named the estimability index (e’). e’ provides a prediction of precision based on the characteristics of image noise and resolution, the nodule being quantified, and the segmentation software. It was further calibrated against empirical precision for 45 protocols of various reconstruction algorithms, slice thickness, and dose level. Results showed a strong correlation established between e’ and the empirical precision across all 45 protocols, demonstrating e’ as an effective surrogate of quantification precision. This study provides a useful framework for the optimization of CT protocols in terms of quantification precision. It also enables fast assessment of protocol compliance in terms of precision for biomarker quantification.

Paper Details

Date Published: 19 March 2013
PDF: 7 pages
Proc. SPIE 8668, Medical Imaging 2013: Physics of Medical Imaging, 86681E (19 March 2013); doi: 10.1117/12.2008481
Show Author Affiliations
Baiyu Chen, Duke Univ. Medical Physics Graduate Program (United States)
Carl E. Ravin Advanced Imaging Labs. (United States)
Ehsan Samei, Duke Univ. Medical Physics Graduate Program (United States)
Carl E. Ravin Advanced Imaging Labs. (United States)
Duke Univ. (United States)


Published in SPIE Proceedings Vol. 8668:
Medical Imaging 2013: Physics of Medical Imaging
Robert M. Nishikawa; Bruce R. Whiting; Christoph Hoeschen, Editor(s)

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