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

Abstract

Intratumoral uptake heterogeneity in 18 F-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 18 F-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 cm 3 ; 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 5 0.0053 and 0.0093, respectively) along with stage (P 5 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 cm 3 , although the complementary information increases substantially with larger volumes. Fordi agnosis and staging in oncology, 18 F-FDG PET/CT is a powerful tool (1). Its use in therapy assessment (2,3) is increasing. Within this context, more emphasis is being given to image-derived indices (4). On the one hand, features extracted from PET images, including metabolically active tumor volume (MATV), mean standardized uptake value (SUV), and total lesion glycolysis, have provided potentially higher prognostic value than standard maximum SUV in various cancer types (5). On the other hand, more recently the heterogeneity of 18 F-FDG uptake within tumors has been associated with treatment failure (4,6-8). Proposed approaches to assessing the heterogeneity of intratumoral activity distribution include visual evaluation (9), SUV coefficient of variation (10), area under...

Hybrid Imaging: Instrumentation and Data Processing

“…As a result of this initiative, first reports have appeared that point at promising results of a quantitative assessment of tumor heterogeneity in light of therapy response prediction [270,271], disease-specific survival [272] as well as prognostic stratification [273]. Meanwhile, challenges using textural features remain, since such calculations are highly sensitive to acquisition, reconstruction and sample size variations [274][275][276]. Overall, the need of reproducibility evaluation as well as standardization of textural features is being acknowledged in the field [274].…”

Predicting Pathologic Response of Esophageal Cancer to Neoadjuvant Chemotherapy: The Implications of Metabolic Nodal Response for Personalized Therapy

“…We believe this to be the largest study performed for esophageal cancer and believe that our results are robust-whether they can be extrapolated to NACR is not clear, but we believe these results warrant urgent assessment. In addition, assessment of several textural response parameters, including entropy and run-length matrices, which although not routinely used in clinical practice have recently been shown to be associated with pTR after NACR (44), and their inclusion in conjunction with volume have been suggested to improve prognostication (45). Such metrics may therefore provide complementary predictive data.…”

Advanced Hodgkin’s lymphoma: End-of-treatment FDG-PET should be maintained

“…One team showed that textural analysis of baseline CT images are correlated to progression-free survival and can be combined with information from interim-PET [30]. There also is potential for textural analysis of baseline PET images to yield useful information [31,32]. Numerous biomarkers within the Reed-Sternberg cell and its microenvironment can also be exploited [33].…”