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Proceedings Paper

Diagnostic accuracy at several reduced radiation dose levels for CT imaging in the diagnosis of appendicitis
Author(s): Di Zhang; Maryam Khatonabadi; Hyun Kim; Matilda Jude; Edward Zaragoza; Margaret Lee; Maitraya Patel; Cheryce Poon; Michael Douek; Denise Andrews-Tang; Laura Doepke; Shawn McNitt-Gray; Chris Cagnon; John DeMarco; Michael McNitt-Gray
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Paper Abstract

Purpose: While several studies have investigated the tradeoffs between radiation dose and image quality (noise) in CT imaging, the purpose of this study was to take this analysis a step further by investigating the tradeoffs between patient radiation dose (including organ dose) and diagnostic accuracy in diagnosis of appendicitis using CT. Methods: This study was IRB approved and utilized data from 20 patients who underwent clinical CT exams for indications of appendicitis. Medical record review established true diagnosis of appendicitis, with 10 positives and 10 negatives. A validated software tool used raw projection data from each scan to create simulated images at lower dose levels (70%, 50%, 30%, 20% of original). An observer study was performed with 6 radiologists reviewing each case at each dose level in random order over several sessions. Readers assessed image quality and provided confidence in their diagnosis of appendicitis, each on a 5 point scale. Liver doses at each case and each dose level were estimated using Monte Carlo simulation based methods. Results: Overall diagnostic accuracy varies across dose levels: 92%, 93%, 91%, 90% and 90% across the 100%, 70%, 50%, 30% and 20% dose levels respectively. And it is 93%, 95%, 88%, 90% and 90% across the 13.5-22mGy, 9.6-13.5mGy, 6.4-9.6mGy, 4-6.4mGy, and 2-4mGy liver dose ranges respectively. Only 4 out of 600 observations were rated "unacceptable" for image quality. Conclusion: The results from this pilot study indicate that the diagnostic accuracy does not change dramatically even at significantly reduced radiation dose.

Paper Details

Date Published: 22 March 2012
PDF: 7 pages
Proc. SPIE 8313, Medical Imaging 2012: Physics of Medical Imaging, 831347 (22 March 2012); doi: 10.1117/12.911428
Show Author Affiliations
Di Zhang, David Geffen School of Medicine at UCLA (United States)
Maryam Khatonabadi, David Geffen School of Medicine at UCLA (United States)
Hyun Kim, David Geffen School of Medicine at UCLA (United States)
Matilda Jude, Olive View-Univ. of California, Los Angeles Medical Ctr. (United States)
Edward Zaragoza, David Geffen School of Medicine at UCLA (United States)
Margaret Lee, Olive View-Univ. of California, Los Angeles Medical Ctr. (United States)
Maitraya Patel, Olive View-Univ. of California, Los Angeles Medical Ctr. (United States)
Cheryce Poon, David Geffen School of Medicine at UCLA (United States)
Michael Douek, David Geffen School of Medicine at UCLA (United States)
Denise Andrews-Tang, Olive View-Univ. of California, Los Angeles Medical Ctr. (United States)
Laura Doepke, David Geffen School of Medicine at UCLA (United States)
Shawn McNitt-Gray, David Geffen School of Medicine at UCLA (United States)
Chris Cagnon, David Geffen School of Medicine at UCLA (United States)
John DeMarco, David Geffen School of Medicine at UCLA (United States)
Michael McNitt-Gray, David Geffen School of Medicine at UCLA (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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