Prognostic significance of 68Ga-Pentixafor PET/CT in multiple myeloma recurrence: a comparison to 18F-FDG PET/CT and laboratory results

Purpose This study investigates the prognostic value of Ga-68-Pentixafor PET/CT using PET-derived quantitative in multiple myeloma (MM) patients with suspected recurrence in comparison to F-18-FDG PET/CT and clinical data. Methods Twenty-four MM patients with suspicion for relapse who underwent Ga-68-Pentixafor and F-18-FDG PET/CT were retrospectively evaluated. Total bone marrow glycolysis for F-18-FDG (TBMFDG) and total bone marrow uptake for Ga-68-Pentixafor PET/CT (TBMCXCR4) were calculated using whole-body metabolic tumor burden obtained by dedicated software (MIM 7.0.6). The patients were followed for 19-24 months, and the association of PET-derived quantitative data with overall survival (OS) was analyzed. Results Ga-68-Pentixafor PET/CT was positive in 17 patients, of which 13 were also positive on F-18-FDG PET/CT, whereas 7 patients were negative on both scans. The positive rate of Ga-68-Pentixafor and F-18-FDG PET/CT on a patient-based approach was 70.8% and 54.1%, respectively. Ga-68-Pentixafor positivity was significantly associated with OS (p = 0.009), and F-18-FDG positivity was at the margin of statistical significance (p = 0.056). TBMCXCR4 and TBMFDG were negatively correlated with OS (r = -0.457, p = 0.025 and r = -0.617, p = 0.001, respectively). The OS was negatively correlated with beta-2-microglobulin levels (r = -0.511, p = 0.01) and CRAB score (r = -0.592, p = 0.002) as an indicator of the end-organ disease, which confirmed these results. Serum beta-2-microglobulin levels and CRAB score were also correlated with TBMCXCR4 (r = 0.442, p = 0.039 and r = 0.573, p = 0.003, respectively) and TBMFDG (r = 0.543, p = 0.009 and r = -0.424, p = 0.003, respectively). Conclusion Ga-68-Pentixafor PET/CT positivity is a negative prognostic factor in the survival outcome of MM patients. Complementary Ga-68-Pentixafor PET/CT has the potential to overcome F-18-FDG PET/CT limitations and helps a more precise risk stratification.