[18F]FDG PET/CT for treatment monitoring and prediction of progression in retroperitoneal fibrosis
Year: 2025
Type: article
Study design: Observational Study
Abstract: Purpose Retroperitoneal fibrosis (RPF) is a rare inflammatory disease, that, if left untreated, can lead to ureteral obstruction and subsequent renal impairment. First-line treatment is prednisolone, with rituximab, often used for refractory cases. This study evaluates treatment response in both [ 18 F]FDG PET and CT, and potential baseline parameters for early prediction of progression. Methods 50 patients with RPF underwent at least two [ 18 F]FDG PET/CT scans (baseline, BL, and first follow-up, FU1), 36 patients a second (FU2), 18 patients a third follow-up (FU3). PET parameters SUV max , SUV mean , SUV peak , metabolic active volume (MAV), thickness (CT rim ) and cranio-caudal extension (CT cc ) of the retroperitoneal mass were measured. Therapy groups were divided into prednisolone, rituximab and the combination of both. Results All PET parameters showed significant correlations with CT rim at all four timepoints. After therapy all PET parameters and CT rim decreased significantly ( p ≤ 0.021). Highly significant metabolic and morphologic response was seen in the prednisolone ( p ≤ 0.003) and the combination therapy group ( p ≤ 0.001). At FU2, eight patients showed progression, with MAV as a good predictor of progression in BL ( p = 0.041; 217.33 versus 100.86 ml). At FU2, SUV max , SUV peak and MAV differed significantly between progression and non-progression group ( p ≤ 0.009), while CT showed no significant differences. Conclusion Our findings underscore the superiority of PET against CT in therapy monitoring of RPF, especially in the detection of progression at FU2. Higher BL MAV correlated with progression at FU2, indicating its potential as a predictive marker. Still, especially when PET is not available, CT can be considered for initial therapy monitoring.
Language: English
Subfield: Rheumatology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,490
OpenAlex ID: W4413140914
