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Distinguishing benign from malignant lesions with high [68 Ga]Ga-FAPI-04 uptake in oncology patients: Insights from dynamic total-body [68 Ga]Ga-FAPI-04 PET/CT

  • Ruohua Chen,
  • Xinlan Yang,
  • Lianghua Li,
  • Haitao Zhao,
  • Gang Huang,
  • Jianjun Liu

摘要

Background and Purpose

While [68 Ga]Ga-FAPI-04 PET/CT is widely used in various malignant tumors diagnosis, its specificity is challenged by high uptake in benign lesions such as inflammatory lymphadenopathy, bone fractures, and degenerative changes. This study aimed to quantitatively assess and characterize the metabolic heterogeneity of [68 Ga]Ga-FAPI-04 uptake in benign and malignant lesions using dynamic total-body PET/CT.

Methods

Dynamic total-body [68 Ga]Ga-FAPI-04 PET/CT scans (0–60 min post-injection) were performed on 17 oncology patients. Time-activity curves (TACs) were generated for benign and malignant lesions with high [68 Ga]Ga-FAPI-04 uptake. The reversible two-tissue compartment model (2T4k) was used to derive kinetic metrics, including K1, k2, k3, k4, vB and VT. Receiver operating characteristic (ROC) curve analysis was used to determine the cut-off values for differentiating benign and malignant lesions.

Results

The study included 58 malignant and 55 inflammatory lesions with high [68 Ga]Ga-FAPI-04 uptake. Malignant lesions exhibited higher K1 (0.277 ± 0.217 ml/ccm/min vs. 0.221 ± 0.216 ml/ccm/min, P = 0.011), vB (0.042 ± 0.007 vs. 0.013 ± 0.004, P < 0.001), and lower k3 (0.267 ± 0.041 1/min vs. 0.481 ± 0.085 1/min, P = 0.008) compared to benign lesions. Lesions were classified into low, medium, and high-probability groups for being malignant based on K1, k3 and vB values, with probabilities of 0%, 50.7%, and 92.0%, respectively (P < 0.001).

Conclusions

Kinetic metrics, particularly K1, k3 and vB values, show promise as imaging biomarkers for distinguishing between benign and malignant lesions with high [68 Ga]Ga-FAPI-04 uptake in oncology patients. These metrics reflect the metabolic heterogeneity of the lesions and may improve diagnostic accuracy in oncological imaging.