Abstract
Introduction: The differentiation of pseudoprogression (PsP) from tumor progression (TP) in glioblastoma patients is difficult on the basis of standard MRI alone. Textural feature analysis as part of the concept of radiomics offers a quantitative method to describe tumor heterogeneity and gains increasing interest in the field of neuro-oncology. In our study, we investigated the potential of textural features of O-(2-[(18)F]fluoroethyl)-L-tyrosine (FET) PET to discriminate between PsP and TP in glioblastoma patients. Materials and Methods: Twenty-three newly diagnosed glioblastoma patients with MRI findings suspicious for TP within 12 weeks after completion of chemoradiation with temozolomide underwent an additional dynamic FET PET scan. Volumes-of-interest were defined on summed images from 20-40 min post-injection (p.i.) by a 3-dimensional auto-contouring process using a tumor-to-brain ratio (TBR) of 1.6 or more. For each lesion, TBRs and the time-activity curves (TACs) of the FET uptake were determined. The TACs were used to evaluate the dynamic FET PET parameters time-to-peak (TTP), slope (slope of linear regression line 20-50 min p.i.) and intercept (intercept of linear regression line with y-axis). Additionally, 39 textural parameters were calculated using the software LifeX (lifexsoft.org). The diagnostic accuracy of TBRs, TTP, slope, intercept, and textural parameters to discriminate between PsP and TP was evaluated using ROC analyses. In order to further increase the diagnostic accuracy, parameters were combined using linear logistic regression for classification of PsP and TP. Results: Fourteen patients had a clinico-radiological diagnosis of TP and nine patients had PsP. The FET PET parameters TBRmean, TBRmax, TTP and intercept yielded a diagnostic accuracy to discriminate between PsP and TP of 79%, 79%, 58%, 63%, respectively. The dynamic FET PET parameter slope yielded the highest diagnostic accuracy of 83% to discriminate between PsP and TP. Two textural features showed a comparable accuracy of 79%. The diagnostic accuracy could not be increased by combination of parameters. Conclusions: Textural features yielded a comparable diagnostic accuracy for diagnosis of pseudoprogression in glioblastoma patients in comparison with static and dynamic FET PET parameters. Textural features might yield additional valuable information for this highly relevant clinical problem and should be further evaluated in larger cohort prospective studies.