Development of a phantom-based methodology for the assessment of quantification performance in CT

Baiyu Chen; Ehsan Samei

doi:10.1117/12.2008481

19 March 2013 Development of a phantom-based methodology for the assessment of quantification performance in CT

Baiyu Chen, Ehsan Samei

Proceedings Volume 8668, Medical Imaging 2013: Physics of Medical Imaging; 86681E (2013) https://doi.org/10.1117/12.2008481
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States

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.

Citation Download Citation

Baiyu Chen and Ehsan Samei "Development of a phantom-based methodology for the assessment of quantification performance in CT", Proc. SPIE 8668, Medical Imaging 2013: Physics of Medical Imaging, 86681E (19 March 2013); https://doi.org/10.1117/12.2008481

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available