RT Journal Article SR Electronic T1 18F-FDG PET Uptake Characterization Through Texture Analysis: Investigating the Complementary Nature of Heterogeneity and Functional Tumor Volume in a Multi–Cancer Site Patient Cohort JF Journal of Nuclear Medicine JO J Nucl Med FD Society of Nuclear Medicine SP 38 OP 44 DO 10.2967/jnumed.114.144055 VO 56 IS 1 A1 Hatt, Mathieu A1 Majdoub, Mohamed A1 Vallières, Martin A1 Tixier, Florent A1 Le Rest, Catherine Cheze A1 Groheux, David A1 Hindié, Elif A1 Martineau, Antoine A1 Pradier, Olivier A1 Hustinx, Roland A1 Perdrisot, Remy A1 Guillevin, Remy A1 El Naqa, Issam A1 Visvikis, Dimitris YR 2015 UL http://jnm.snmjournals.org/content/56/1/38.abstract AB Intratumoral uptake heterogeneity in 18F-FDG PET has been associated with patient treatment outcomes in several cancer types. Textural feature analysis is a promising method for its quantification. An open issue associated with textural features for the quantification of intratumoral heterogeneity concerns its added contribution and dependence on the metabolically active tumor volume (MATV), which has already been shown to be a significant predictive and prognostic parameter. Our objective was to address this question using a larger cohort of patients covering different cancer types. Methods: A single database of 555 pretreatment 18F-FDG PET images (breast, cervix, esophageal, head and neck, and lung cancer tumors) was assembled. Four robust and reproducible textural feature–derived parameters were considered. The issues associated with the calculation of textural features using co-occurrence matrices (such as the quantization and spatial directionality relationships) were also investigated. The relationship between these features and MATV, as well as among the features themselves, was investigated using Spearman rank coefficients for different volume ranges. The complementary prognostic value of MATV and textural features was assessed through multivariate Cox analysis in the esophageal and non–small cell lung cancer (NSCLC) cohorts. Results: A large range of MATVs was included in the population considered (3–415 cm3; mean, 35; median, 19; SD, 50). The correlation between MATV and textural features varied greatly depending on the MATVs, with reduced correlation for increasing volumes. These findings were reproducible across the different cancer types. The quantization and calculation methods both had an impact on the correlation. Volume and heterogeneity were independent prognostic factors (P = 0.0053 and 0.0093, respectively) along with stage (P = 0.002) in non–small cell lung cancer, but in the esophageal tumors, volume and heterogeneity had less complementary value because of smaller overall volumes. Conclusion: Our results suggest that heterogeneity quantification and volume may provide valuable complementary information for volumes above 10 cm3, although the complementary information increases substantially with larger volumes.