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27 February 2009 Identification of asymmetric pulmonary nodule growth using a moment-based algorithm
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Proceedings Volume 7260, Medical Imaging 2009: Computer-Aided Diagnosis; 72602W (2009)
Event: SPIE Medical Imaging, 2009, Lake Buena Vista (Orlando Area), Florida, United States
The growth rate of pulmonary nodules has been shown to be an indicator of malignancy, and previous work on pulmonary nodule characterization has suggested that the asymmetry of a nodule's shape may be correlated with malignancy. We have also observed that measurements in the axial direction on CT scans are less repeatable than measurements in-plane and this should be considered when making lesion size-change measurements. To address this, we present a method to measure the asymmetry of a pulmonary nodule's growth by the use of second-order central moments that are insensitive to z-direction variation. The difference in the moment ratios on each scan is used as a measure of the asymmetry of growth. To establish what level of difference is significant, the 95% confidence interval of the differences was determined on a zero-change dataset of 22 solid pulmonary nodules with repeat scans in the same session. This method was applied to a set of 47 solid, stable pulmonary nodules and a set of 49 solid, malignant nodules. The confidence interval established from the zero-change dataset was (-0.45, 0.38); nodules with differences outside this confidence interval are considered to have asymmetric growth. Of the 47 stable nodules, 12.8% (6/47) were found to have asymmetric growth compared to 24.5% (12/49) of malignant nodules. These preliminary results suggest that nodules with asymmetric growth can be identified.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Artit C. Jirapatnakul, Anthony P. Reeves, Alberto M. Biancardi, David F. Yankelevitz, and Claudia I. Henschke "Identification of asymmetric pulmonary nodule growth using a moment-based algorithm", Proc. SPIE 7260, Medical Imaging 2009: Computer-Aided Diagnosis, 72602W (27 February 2009);

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