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Proceedings Paper

Relevance of MTF and NPS in quantitative CT: towards developing a predictable model of quantitative performance
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Paper Abstract

The quantification of lung nodule volume based on CT images provides valuable information for disease diagnosis and staging. However, the precision of the quantification is protocol, system, and technique dependent and needs to be evaluated for each specific case. To efficiently investigate the quantitative precision and find an optimal operating point, it is important to develop a predictive model based on basic system parameters. In this study, a Fourier-based metric, the estimability index (e') was proposed as such a predictor, and validated across a variety of imaging conditions. To first obtain the ground truth of quantitative precision, an anthropomorphic chest phantom with synthetic spherical nodules were imaged on a 64 slice CT scanner across a range of protocols (five exposure levels and two reconstruction algorithms). The volumes of nodules were quantified from the images using clinical software, with the precision of the quantification calculated for each protocol. To predict the precision, e' was calculated for each protocol based on several Fourier-based figures of merit, which modeled the characteristic of the quantitation task and the imaging condition (resolution, noise, etc.) of a particular protocol. Results showed a strong correlation (R2=0.92) between the measured and predicted precision across all protocols, indicating e' as an effective predictor of the quantitative precision. This study provides a useful framework for quantification-oriented optimization of CT protocols.

Paper Details

Date Published: 9 March 2012
PDF: 7 pages
Proc. SPIE 8313, Medical Imaging 2012: Physics of Medical Imaging, 83132O (9 March 2012); doi: 10.1117/12.913219
Show Author Affiliations
Baiyu Chen, Duke Univ. (United States)
Duke Univ. Medical Ctr. (United States)
Samuel Richard, Duke Univ. (United States)
Duke Univ. Medical Ctr. (United States)
Ehsan Samei, Duke Univ. (United States)
Duke Univ. Medical Ctr. (United States)

Published in SPIE Proceedings Vol. 8313:
Medical Imaging 2012: Physics of Medical Imaging
Norbert J. Pelc; Robert M. Nishikawa; Bruce R. Whiting, Editor(s)

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