Abstract
PurposeThis study aims to predict hematological toxicity induced by 223Ra therapy. We investigated the value of metabolically active bone tumor volume (MBTV) and total bone lesion activity (TLA) calculated on pretreatment fluorine-18-fluorocholine (18F-FCH) PET/CT in castrate-resistant prostate cancer (CRPC) patients with bone metastases treated with 223Ra radionuclide therapy.Patients and methods18F-FCH PET/CT imaging was performed in 15 patients with CRPC before treatment with 223Ra. Bone metastatic disease was quantified on the basis of the maximum standardized uptake value (SUV), total lesion activity (TLA=MBTV×SUVmean), or MBTV/height (MBTV/H) and TLA/H. 18F-FCH PET/CT bone tumor burden and activity were analyzed to identify which parameters could predict hematological toxicity [on hemoglobin (Hb), platelets (PLTs), and lymphocytes] while on 223Ra therapy. Pearson’s correlation was used to identify the correlations between age, prostate-specific antigen, and 18F-FCH PET parameters.ResultsMBTV ranged from 75 to 1259 cm3 (median: 392 cm3). TLA ranged from 342 to 7198 cm3 (median: 1853 cm3). Patients benefited from two to six cycles of 223Ra (n=56 cycles in total). At the end of 223Ra therapy, five of the 15 (33%) patients presented grade 2/3 toxicity on Hb and lymphocytes, whereas three of the 15 (20%) patients presented grade 2/3 PLT toxicity.Age was correlated negatively with both MBTV (r=−0.612, P=0.015) and TLA (r=−0.596, P=0.018). TLA, TLA/H, and MBTV/H predicted hematological toxicity on Hb, whereas TLA/H and MBTV/H predicted toxicity on PLTs at the end of 223Ra cycles. Receiver operating characteristic curve analysis allowed to define the cutoffs for MBTV (915 cm3) and TLA (4198 cm3) predictive for PLT toxicity, with an accuracy of 0.92 and 0.99.ConclusionTumor bone burden calculation is feasible with 18F-FCH PET/CT with freely available open-source software. In this pilot study, baseline 18F-FCH PET/CT markers (TLA, MBTV) have shown abilities to predict Hb and PLT toxicity after 223Ra therapy and could be explored for patient selection and treatment optimization.
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