SU‐E‐J‐242: Volume‐Dependence of Quantitative Imaging Features From CT and CE‐CT Images of NSCLC

Abstract

Purpose:To determine whether tumor volume plays a significant role in the values obtained for texture features when they are extracted from computed tomography (CT) images of non‐small cell lung cancer (NSCLC). We also sought to identify whether features can be reliably measured at all volumes or if a minimum volume threshold should be recommended.Methods:Eleven features were measured on 40 CT and 32 contrast‐enhanced CT (CECT) patient images for this study. Features were selected for their prognostic/diagnostic value in previous publications. Direct correlations between these textures and volume were evaluated using the Spearman correlation coefficient. Any texture that the Wilcoxon rank‐sum test was used to compare the variation above and below a volume cutoff. Four different volume thresholds (5, 10, 15, and 20 cm3) were tested.Results:Four textures were found to be significantly correlated with volume in both the CT and CE‐CT images. These were busyness, coarseness, gray‐level nonuniformity, and run‐length nonuniformity with correlation coefficients of 0.92, −0.96, 0.94, and 0.98 for the CT images and 0.95, −0.97, 0.98, and 0.98 for the CE‐CT images. After volume normalization, the correlation coefficients decreased substantially. For the data obtained from the CT images, the results of the Wilcoxon rank‐sum test were significant when volume thresholds of 5–15 cm3 were used. No volume threshold was shown to be significant for the CE‐CT data.Conclusion:Equations for four features that have been used in several published studies were found to be volume‐dependent. Future studies should consider implementing normalization factors or removing these features entirely to prevent this potential source of redundancy or bias.This work was supported in part by National Cancer Institute grant R03CA178495‐01. Xenia Fave is a recipient of the American Association of Physicists in Medicine Graduate Fellowship.