Work

Cross‐Sectional Analysis of Metabolic Tumor Burden Detected by F‐18 FDG PET/CT and Circulating Tumor DNA in Advanced Breast Cancer

Year: 2025

Type: article

Abstract: BACKGROUND: This study investigated the relationship between circulating tumor DNA (ctDNA) parameters and metabolic parameters from FDG PET/CT in advanced breast cancer (ABC) patients. METHODS: In this retrospective single-center study, 47 ABC patients who underwent both liquid biopsy and FDG PET/CT were analyzed. RESULTS: Results showed that 27 patients (57.4%) had detectable ctDNA. Patients with detectable ctDNA demonstrated significantly higher whole-body metabolic tumor volume (WB-MTV) (p = 0.002) and whole-body total lesion glycolysis (WB-TLG) (p = 0.006) compared to those without ctDNA, while no significant difference was found in SUVmax or SUVmean. A moderate correlation was observed between variant allele frequency (VAF) values and metabolic parameters: maximum VAF correlated with SUVmax, WB-MTV, and WB-TLG (r = 0.407, p = 0.005; r = 0.457, p = 0.001; r = 0.415, p = 0.004, respectively). Mean VAF correlated with SUVmax, WB-MTV, and WB-TLG (r = 0.406, p = 0.005; r = 0.446, p = 0.002; r = 0.404, p = 0.005, respectively). The total VAF correlated with SUVmax, WB-MTV, and WB-TLG (r = 0.394, p = 0.006; r = 0.465, p = 0.001; r = 0.430, p = 0.003, respectively). When excluding patients without detectable ctDNA, the correlation between VAF values and WB-MTV, WB-TLG disappeared, while the correlation with SUVmax persisted. Total alteration number in ctDNA showed a moderate correlation with WB-MTV and WB-TLG (r = 0.563, p < 0.001; r = 0.459, p = 0.001, respectively). Correlation with WB-MTV remained significant when excluding patients without detectable ctDNA (r = 0.500, p = 0.008). CONCLUSIONS: These findings suggest that metabolic tumor burden correlates with ctDNA detection and characteristics, potentially offering complementary information for disease monitoring, treatment selection, and response assessment in ABC. The combined use of these parameters may improve prognostic evaluation and guide personalized treatment strategies.

Source: Cancer Medicine

DOI: 10.1002/cam4.71049