Share Email Print

Proceedings Paper

Dose reduction and lesion delectability in abdominal CT
Author(s): Sameer Tipnis; Walter Huda; Andrew Hardie; Kent Ogden
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

The purpose of this study was to quantify how reducing x-ray beam intensity (i.e., mAs) affects lesion detection performance in abdominal CT examinations. A simulation package (Syngo Explorer) was used to reconstruct 4-mm thick CT images of a patient undergoing a standard abdominal exam. Simulations were performed at four x-ray beam intensities of 100%, 70%, 50%, and 25%. Four observers were used to perform a series of two Alternate Forced Choice (2-AFC) experiments that measure the lesion contrast (I92%) corresponding to a detection accuracy of 92%. Four lesion sizes were used ranging from 5 mm to 12 mm. Results were plotted as log(I92%) versus log(mAs) to quantify how changes in x-ray intensity affect lesion detection, as well as log(I92%) versus log(size) to generate contrast-detail curves. The fitted slope of noise in reconstructed images as a function of relative CT x-ray beam intensity was -0.25, which is about half the value of -0.5 expected for an ideal quantum noise limited imaging system. For lesion sizes between 5 mm and 10 mm, slopes of log(I92%) versus log(mAs) curves were very similar for all four observers, and ranged between -0.10 and -0.17. For 5 mm sized lesions, doubling the x-ray beam intensity improved detection performance by about 13%, whereas for 7 and 10 mm lesions, doubling the x-ray intensity improved detection performance by about 7%. For the 12 mm lesion there were no consistent patterns for all four readers, which may be related to the lack of a standardized viewing distance. The average slope for the four contrast detail curves was -0.41 ± 0.09, which is substantially less than the value of -1.0 predicted for an ideal observer operating with a quantum noise limited images. For our abdominal CT images, doubling of the lesion size resulted in improvements in lesion detection of ~ 30%.

Paper Details

Date Published: 22 March 2010
PDF: 9 pages
Proc. SPIE 7622, Medical Imaging 2010: Physics of Medical Imaging, 76222Q (22 March 2010); doi: 10.1117/12.843600
Show Author Affiliations
Sameer Tipnis, Medical Univ. of South Carolina (United States)
Walter Huda, Medical Univ. of South Carolina (United States)
Andrew Hardie, Medical Univ. of South Carolina (United States)
Kent Ogden, SUNY Upstate Medical Univ. (United States)

Published in SPIE Proceedings Vol. 7622:
Medical Imaging 2010: Physics of Medical Imaging
Ehsan Samei; Norbert J. Pelc, Editor(s)

© SPIE. Terms of Use
Back to Top