Rethinking dynamics: static amino acid PET parameters vs. dynamic amino acid PET parameters for the detection of...

It remains unclear whether dynamic amino-acid (AA) positron-emission tomography (PET) has additional diagnostic value over static AA-PET to distinguish tumor progression (TP) from treatment-related abnormalities (TRA) in patients with post-treatment glioma.

This was a retrospective study of patients with glioma with suspected TP who underwent dynamic AA-PET imaging. The final diagnoses were based on histopathology and/or clinical-radiological follow-up. The static PET parameters included the mean and maximum tumor-to-brain ratio (TBR_max and TBR_mean, respectively) and the dynamic PET parameters included time to peak (TTP) and area under the time activity curve (AUTAC). Diagnostic accuracy was assessed using the area under the receiver operating characteristic curve (AUROC).

In total, 33 patients with adult diffuse glioma (17 females: mean age: 55.7 ± 12.2 years) were included [13 [S-methyl-¹¹C]methionine ([¹¹C]MET) and 20 O-(2-[¹⁸F]fluoroethyl)-L-tyrosine (¹⁸F]FET) PET examinations]. The static parameters (TBR_mean and TBR_max) were significantly different between the TP and TRA groups when using [¹¹C]MET (p = 0.019 and p = 0.013, respectively), resulting in very-good-to-excellent diagnostic accuracy (AUROC values of 0.85 and 0.93, respectively). The TBR_mean values derived from [¹⁸F]FET PET data were not significantly different between the TP and TRA groups (p = 0.066). However, the [¹⁸F]FET PET data-derived TBR_max values were significantly higher in the individuals with TP (p = 0.005), indicating very good diagnostic accuracy (AUROC = 0.84). The dynamic PET parameters (time to peak and area under the time activity curve) were not significantly different between the TP and TRA groups.

This study suggests that dynamic and static AA-PET parameters have similar diagnostic capacities to distinguish TP from TRA. While static AA-PET parameters may suffice for clinical decision-making, this study did not formally assess the incremental value of using dynamic metrics in addition to static measures.