Diagnostics (Basel, Switzerland) · 2025
Variability of Metabolic Rate and Distribution Volume Quantification in Whole-Body Parametric PATLAK [18F]-FDG PET/CT-A Prospective Trial in Patients with Lung Cancer.
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Ursprung Stephan, Zender Lars, Ghibes Patrick, Hagen Florian, Nikolaou Konstantin, la Fougère Christian, Weissinger Matthias
Аннотация
Background: The recent introduction of whole-body positron emission tomography/ computed tomography (PET/CT) scanners and multi-bed, multi-time point acquisition technique enable calculating fluorodeoxyglucose (FDG) kinetics in the whole body. However, validating parametric, Patlak-derived data is difficult on phantoms. Methods: This prospective study investigated the effect of quantification methods mean, max, and peak on the metabolic rate (MR-FDG) and distribution volume (DV-FDG) quantification, as well as the diagnostic accuracy of parametric Patlak FDG-PET scans in diagnosing lung lesions and lymph node metastases, using histopathology and follow-up as reference standards. Dynamic whole-body FDG PET was acquired for 80 minutes in 34 patients with indeterminate lung lesions and kinetic parameters extracted from lung lesions and representative mediastinal and hilar lymph nodes. Results: All quantification methods-mean, max, and peak-demonstrated high diagnostic accuracy (AUC: MR-FDG: 0.987-0.991 and 0.893-0.905; DV-FDG: 0.948-0.975 and 0.812-0.825) for differentiating benign from malignant lymph nodes and lung lesions. Differences in the magnitude of MR-FDG (-4.76-14.09) and DV-FDG (-10.64-46.10%) were substantial across methods. Variability was more pronounced in lymph nodes (MR-FDG: 1.37-3.48) than in lung lesions (MR-FDG: 3.31-5.04). The variability was lowest between mean and max quantification, with percentage differences of 40.87 ± 5.69% for MR-FDG and 39.26 ± 7.68% for DV-FDG. Conclusions: The choice of method to measure MR-FDG and DV-FDG greatly influences the results, especially in smaller lesions with large and systematic differences. For lung lesions, a conversion factor between mean and max methods of 40% provides acceptable agreement, facilitating retrospective comparisons of measurements, e.g., in meta-analyses.