Can Dynamic Whole-Body FDG PET Imaging Differentiate between Malignant and Inflammatory Lesions?

Abstract

Background: Investigation of the clinical feasibility of dynamic whole-body (WB) [18F]FDG PET, including standardized uptake value (SUV), rate of irreversible uptake (Ki), and apparent distribution volume (Vd) in physiologic tissues, and comparison between inflammatory/infectious and cancer lesions. Methods: Twenty-four patients were prospectively included to undergo dynamic WB [18F]FDG PET/CT for clinically indicated re-/staging of oncological diseases. Parametric maps of Ki and Vd were generated using Patlak analysis alongside SUV images. Maximum parameter values (SUVmax, Kimax, and Vdmax) were measured in liver parenchyma and in malignant or inflammatory/infectious lesions. Lesion-to-background ratios (LBRs) were calculated by dividing the measurements by their respective mean in the liver tissue. Results: Seventy-seven clinical target lesions were identified, 60 malignant and 17 inflammatory/infectious. Kimax was significantly higher in cancer than in inflammatory/infections lesions (3.0 vs. 2.0, p = 0.002) while LBRs of SUVmax, Kimax, and Vdmax did not differ significantly between the etiologies: LBR (SUVmax) 3.3 vs. 2.9, p = 0.06; LBR (Kimax) 5.0 vs. 4.4, p = 0.05, LBR (Vdmax) 1.1 vs. 1.0, p = 0.18). LBR of inflammatory/infectious and cancer lesions was higher in Kimax than in SUVmax (4.5 vs. 3.2, p < 0.001). LBRs of Kimax and SUVmax showed a strong correlation (Spearman’s rho = 0.83, p < 0.001). Conclusions: Dynamic WB [18F]FDG PET/CT is feasible in a clinical setting. LBRs of Kimax were higher than SUVmax. Kimax was higher in malignant than in inflammatory/infectious lesions but demonstrated a large overlap between the etiologies.

Keywords: FDG PET/CT; Patlak; dynamic whole-body positron emission tomography; fluorodeoxyglucose; infection; molecular imaging; oncologic imaging.

Figure 1

Examples of blood pool single bed dynamic (A) and head-to-thighs dynamic (B) reconstructed images (injected activity: 2 MBq/kg body weight—156 MBq in total) from representative dynamic frames, illustrating the original imaging data used for generating parametric maps.

Figure 2

Examples of the parametric images of standardized uptake value (SUV), metabolic rate (Ki) and apparent distribution volume (Vd) of [¹⁸F]FDG. (A) Images from a patient with lung cancer with histologically proven hilar lymph node metastasis, ipsilateral lung metastasis (confirmed by follow-up imaging), and postoperatively proven diverticulitis of the sigmoid colon. High signal is seen in the hilar lymph node (arrow) and ipsilateral lung metastasis (arrowhead) as well as the inflammatory sigmoid colon lesion (dashed arrow) both on SUV and Ki images with no corresponding signal in the Vd image, indicating almost entirely irreversible uptake and no unmetabolized [¹⁸F]FDG. (B) Images from a patient with histologically proven liver metastasis from rectal cancer in the left liver lobe (arrowhead) show high signal in both SUV and Ki images and absence of signal in the Vd image, indicating irreversible uptake of [¹⁸F]FDG. In the left shoulder, there is one medial lesion (arrow) with high signal on SUV, Ki, and Vd images and one additional lateral focus (dashed arrow) without correlation in the Vd image. Both foci are consistent with tendinitis (confirmed by follow-up imaging), with the medial focus containing partly unmetabolized [¹⁸F]FDG.

Figure 3

Combined dot and box plots comparing the quantitative parameters standardized uptake value (SUV_max, A), rate of irreversible uptake (Ki_max, B), and apparent distribution volume (Vd_max, C) normalized over their respective mean in liver tissue in cancer (n = 60) versus inflammatory lesions (n = 17).

Figure 4

Correlation plot of the rate of irreversible uptake (Ki_max) against standardized uptake value (SUV_max). Both parameters were normalized over their respective averages measured in the liver parenchyma.