Adding the temporal domain to PET radiomic features

Abstract

Background Radiomic features, extracted from positron emission tomography, aim to characterize tumour biology based on tracer intensity, tumour geometry and/or tracer uptake heterogeneity. Currently, radiomic features are derived from static images. However, temporal changes in tracer uptake might reveal new aspects of tumour biology. This study aims to explore additional information of these novel dynamic radiomic features compared to those derived from static or metabolic rate images. Methods Thirty-five patients with non-small cell lung carcinoma underwent dynamic [F-18]FDG PET/CT scans. Spatial intensity, shape and texture radiomic features were derived from volumes of interest delineated on static PET and parametric metabolic rate PET. Dynamic grey level cooccurrence matrix (GLCM) and grey level run length matrix (GLRLM) features, assessing the temporal domain unidirectionally, were calculated on eight and sixteen time frames of equal length. Spearman's rank correlations ofparametricanddynamicfeatures withstaticfeatures were calculated to identify features with potential additional information. Survival analysis was performed for the non-redundant temporal features and a selection ofstaticfeatures using Kaplan-Meier analysis. Results Three out of 90parametricfeatures showed moderate correlations with correspondingstaticfeatures (rho >= 0.61), all other features showed high correlations (rho>0.7).Dynamicfeatures are robust independent of frame duration. Five out of 22dynamicGLCM features showed a negligible to moderate correlation with anystaticfeature, suggesting additional information. All sixteendynamicGLRLM features showed high correlations with static features, implying redundancy. Log-rank analyses of Kaplan-Meier survival curves for all features dichotomised at the median were insignificant. Conclusion This study suggests that, compared tostaticfeatures, somedynamicGLCM radiomic features show different information, whereasparametricfeatures provide minimal additional information. Future studies should be conducted in larger populations to assess whether there is a clinical benefit of radiomics using the temporal domain over traditional radiomics.