Preliminary investigation into sources of uncertainty in quantitative imaging features. (September 2015) - Fave, Xenia; Cook, Molly; Frederick, Amy; Zhang, Lifei; Yang, Jinzhong; Fried, David; Stingo, Francesco; Court, Laurence
Highlights: Features measured at end-of-exhale phase did not significantly differ from T20 to T90. Features are highly correlated between end-of-exhale phase and average images. The impact of tube voltage on features may not be statistically significant. The impact of tube current modeled as Gaussian noise was statistically significant. Abstract: Several recent studies have demonstrated the potential for quantitative imaging features to classify non-small cell lung cancer (NSCLC) patients as high or low risk. However applying the results from one institution to another has been difficult because of the variations in imaging techniques and feature measurement. Our study was designed to determine the effect of some of these sources of uncertainty on image features extracted from computed tomography (CT) images of non-small cell lung cancer (NSCLC) tumors. CT images from 20 NSCLC patients were obtained for investigating the impact of four sources of uncertainty: Two region of interest (ROI) selection conditions (breathing phase and single-slice vs. whole volume) and two imaging protocol parameters (peak tube voltage and current). Texture values did not vary substantially with the choice of breathing phase; however, almost half (12 out of 28) of the measured textures did change significantly when measured from the average images compared to the end-of-exhale phase. Of the 28 features, 8 showed a significant variation when measured from the largest cross sectional slice compared to the entire tumor, but 14 were correlated to the entire tumor value. While simulating a decrease in tube voltage had a negligible impact on texture features, simulating a decrease in mA resulted in significant changes for 13 of the 23 texture values. Our results suggest that substantial variation exists when textures are measured under different conditions, and thus the development of a texture analysis standard would be beneficial for comparing features between patients and institutions.