Abstract
AimTo study the influence of dual time point 18F-FDG PET/CT in textural features and SUV-based variables and their relation among them.MethodsFifty-six patients with locally advanced breast cancer (LABC) were prospectively included. All of them underwent a standard 18F-FDG PET/CT (PET-1) and a delayed acquisition (PET-2). After segmentation, SUV variables (SUVmax, SUVmean, and SUVpeak), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were obtained. Eighteen three-dimensional (3D) textural measures were computed including: run-length matrices (RLM) features, co-occurrence matrices (CM) features, and energies. Differences between all PET-derived variables obtained in PET-1 and PET-2 were studied.ResultsSignificant differences were found between the SUV-based parameters and MTV obtained in the dual time point PET/CT, with higher values of SUV-based variables and lower MTV in the PET-2 with respect to the PET-1. In relation with the textural parameters obtained in dual time point acquisition, significant differences were found for the short run emphasis, low gray-level run emphasis, short run high gray-level emphasis, run percentage, long run emphasis, gray-level non-uniformity, homogeneity, and dissimilarity. Textural variables showed relations with MTV and TLG.ConclusionSignificant differences of textural features were found in dual time point 18F-FDG PET/CT. Thus, a dynamic behavior of metabolic characteristics should be expected, with higher heterogeneity in delayed PET acquisition compared with the standard PET. A greater heterogeneity was found in bigger tumors.
Highlights
Tumors are heterogeneous mixtures of cells, which differ in their morphology, genetics, and biological behavior
Significant differences were found between the standard uptake value (SUV)-based parameters and metabolic tumor volume (MTV) obtained in the dual time point PET/CT, with higher values of SUV-based variables and lower MTV in the PET-2 with respect to the PET-1
In relation with the textural parameters obtained in dual time point acquisition, significant differences were found for the short run emphasis, low gray-level run emphasis, short run high gray-level emphasis, run percentage, long run & Ana Marıa Garcia-Vicente angarvice@yahoo.es
Summary
Tumors are heterogeneous mixtures of cells, which differ in their morphology, genetics, and biological behavior. This complexity may underlie the inability of current therapies to significantly impact patient outcome [1]. The term ‘textural analysis’ refers to a variety of mathematical methods for quantifying the spatial distribution of voxel intensities in images [3, 4]. Those methods allow for an objective evaluation of the visible tumor properties, including heterogeneity. Many different textural analysis methods have been developed over the recent
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