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Keywords
- 11C-Methionine PET/CT (1)
- 18F-FDG PET/CT (1)
- 68Ga-Pentixafor PET/CT (1)
- agreement (1)
- biomarker (1)
- comparability (1)
- metabolic tumour volume (MTV) (1)
- prostate-specific membrane antigen (PSMA) (1)
- smoldering myeloma (1)
- software (1)
- total lesion PSMA (1)
This study aimed to explore the correlation between imaging patterns and clinical features in patients with smoldering multiple myeloma (SMM) who simultaneously underwent 18F-FDG, 11C-Methionine, and 68Ga-Pentixafor positron emission tomography/computed tomography (PET/CT). We retrieved and analyzed clinical characteristics and PET imaging data of 10 patients with SMM. We found a significant correlation between bone marrow (BM) plasma cell (PC) infiltration and mean standardized uptake values (SUV\(_{mean}\)) of lumbar vertebrae L2-L4 on 11C-Methionine PET/CT scans (r = 0.676, p = 0.031) and 68Ga-Pentixafor PET/CT scans (r = 0.839, p = 0.002). However, there was no significant correlation between BM involvement and SUV\(_{mean}\) of lumbar vertebrae L2-L4 on 18F-FDG PET/CT scans (r = 0.558, p = 0.093). Similarly, mean target-to-background ratios (TBR\(_{mean}\)) of lumbar vertebrae L2-L4 also correlated with bone marrow plasma cell (BMPC) infiltration in 11C-Methionine PET/CT (r = 0.789, p = 0.007) and 68Ga-Pentixafor PET/CT (r = 0.724, p = 0.018) PET/CT. In contrast, we did not observe a significant correlation between BMPC infiltration rate and TBR\(_{mean}\) in 18F-FDG PET/CT (r = 0.355, p = 0.313). Additionally, on 11C-Methionine PET/CT scans, we found a significant correlation between BMPC infiltration and TBR\(_{max}\) of lumbar vertebrae L2-L4 (r = 0.642, p = 0.045). In conclusion, 11C-Methionine and 68Ga-Pentixafor PET/CT demonstrate higher sensitivity than 18F-FDG PET/CT in detecting BM involvement in SMM.
(1) Background: Prostate-specific membrane antigen (PSMA)-derived tumour volume (PSMA-TV) and total lesion PSMA (TL-PSMA) from PSMA PET/CT scans are promising biomarkers for assessing treatment response in prostate cancer (PCa). Currently, it is unclear whether different software tools for assessing PSMA-TV and TL-PSMA produce comparable results. (2) Methods: \(^{68}\)Ga-PSMA PET/CT scans from n = 21 patients with castration-resistant PCa (CRPC) receiving chemotherapy were identified from our single-centre database. PSMA-TV and TL-PSMA were calculated with Syngo.via (Siemens) as well as the freely available Beth Israel plugin for FIJI (Fiji Is Just ImageJ) before and after chemotherapy. While statistical comparability was illustrated and quantified via Bland-Altman diagrams, the clinical agreement was estimated by matching PSMA-TV, TL-PSMA and relative changes of both variables during chemotherapy with changes in serum PSA (ΔPSA) and PERCIST (Positron Emission Response Criteria in Solid Tumors). (3) Results: Comparing absolute PSMA-TV and TL-PSMA as well as Bland–Altman plotting revealed a good statistical comparability of both software algorithms. For clinical agreement, classifying therapy response did not differ between PSMA-TV and TL-PSMA for both software solutions and showed highly positive correlations with BR. (4) Conclusions: due to the high levels of statistical and clinical agreement in our CRPC patient cohort undergoing taxane chemotherapy, comparing PSMA-TV and TL-PSMA determined by Syngo.via and FIJI appears feasible.