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Diagnostic Performance of Dynamic Whole-Body Patlak [(18)F]FDG-PET/CT in Patients with Indeterminate Lung Lesions and Lymph Nodes

Background: Static [(18)F]FDG-PET/CT is the imaging method of choice for the evaluation of indeterminate lung lesions and NSCLC staging; however, histological confirmation of PET-positive lesions is needed in most cases due to its limited specificity. Therefore, we aimed to evaluate the diagnostic p...

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Detalles Bibliográficos
Autores principales: Weissinger, Matthias, Atmanspacher, Max, Spengler, Werner, Seith, Ferdinand, Von Beschwitz, Sebastian, Dittmann, Helmut, Zender, Lars, Smith, Anne M., Casey, Michael E., Nikolaou, Konstantin, Castaneda-Vega, Salvador, la Fougère, Christian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10299392/
https://www.ncbi.nlm.nih.gov/pubmed/37373636
http://dx.doi.org/10.3390/jcm12123942
Descripción
Sumario:Background: Static [(18)F]FDG-PET/CT is the imaging method of choice for the evaluation of indeterminate lung lesions and NSCLC staging; however, histological confirmation of PET-positive lesions is needed in most cases due to its limited specificity. Therefore, we aimed to evaluate the diagnostic performance of additional dynamic whole-body PET. Methods: A total of 34 consecutive patients with indeterminate pulmonary lesions were enrolled in this prospective trial. All patients underwent static (60 min p.i.) and dynamic (0–60 min p.i.) whole-body [(18)F]FDG-PET/CT (300 MBq) using the multi-bed-multi-timepoint technique (Siemens mCT FlowMotion). Histology and follow-up served as ground truth. Kinetic modeling factors were calculated using a two-compartment linear Patlak model (FDG influx rate constant = Ki, metabolic rate = MR-FDG, distribution volume = DV-FDG) and compared to SUV using ROC analysis. Results: MR-FDG(mean) provided the best discriminatory power between benign and malignant lung lesions with an AUC of 0.887. The AUC of DV-FDG(mean) (0.818) and SUV(mean) (0.827) was non-significantly lower. For LNM, the AUCs for MR-FDG(mean) (0.987) and SUV(mean) (0.993) were comparable. Moreover, the DV-FDG(mean) in liver metastases was three times higher than in bone or lung metastases. Conclusions: Metabolic rate quantification was shown to be a reliable method to detect malignant lung tumors, LNM, and distant metastases at least as accurately as the established SUV or dual-time-point PET scans.