Stanford University, Stanford, CA
Hong Song , Aseem Anand , Karl Sjöstrand , Valentina Ferri , Heying Duan , Jagruti Shah , Farshad Moradi , Carina Mari Aparici , Benjamin Lewis Franc , Guido Davidzon , Colin P Bergstrom , Alice C. Fan , Sumit Shah , Ali Raza Khaki , Sandy Srinivas , Andrei Iagaru
Background: PSMA PET has been shown to detect more metastasis and alter management at biochemical recurrence (BCR), but it remains to be determined that it changes oncologic outcome. We assessed the quantitative parameters on 18F-DCFPyL PET at BCR and evaluated their association with tumor volume, metastatic locations with the subsequent biochemical progression free survival (bPFS). Methods: This is a retrospective image analysis and longitudinal follow up of a prospective study evaluating 18F-DCFPyL PET in BCR. Patients were treated with androgen deprivation therapy (ADT) and/or metastatic directed therapy (MDT) based on imaging findings. The 18F-DCFPyL PET images were quantitatively analyzed by the aPROMISE application, a semi-automated software for comprehensive analysis and structured reporting of PSMA PET/CT. aPROMISE uses deep learning to segment detailed anatomical information from the CT images and uses this information in combination with the PET image to detect and quantify candidates for prostate cancer lesions. The reader works in tandem with the software to vet the final list of lesions, from which the quantitative assessments and final report is created automatically. Based on the Prostate Cancer Molecular Imaging Standardized Evaluation (PROMISE) criteria. SUV mean, PSMA positive total tumor volume (PSMAttv) and aPSMA scores, a quantitative score for tumor burden measuring the interaction of tumor volume and uptake stratified by local tumors (aPSMA-miT), regional lymph nodes (aPSMA-miN) and distant metastases (aPSMA-miMa for extrapelvic metastases, miMb for bone metastases and miMc for other organ metastases) were obtained based on the miTNM classification. The association of these quantitative parameters with the subsequent bPFS was evaluated. Results: 143 patients (age 70.5 ± 7.9, range 50 -93 years; median PSA 2.8, range 0.12 – 1125.9 ng/mL) were included in the quantitative image analysis. 80 of 143 patients (56%) had nodal metastases 51/143 patients (36%) had bone metastases, only 16 of 143 patients (11%) had visceral metastases. With median follow up of 40 months, 82 of 143 patients (57%) have progressed again biochemically after MDT. The median bPFS was 26.9 months. Quantitative analysis of 18F-DCFPyL PET found that the subsequent bPFS is significantly associated with aPSMA-miMb (P = 0.003), aPSMA-miN (P = 0.005), aPSMA-miT (P< 0.001), and PSMAttv (P = 0.006), but not with SUVmean, SUVmax or aPSMA-miMc. Conclusions: Quantitative image analysis of 18F-DCFPyL PET at BCR may be useful in predicting the subsequent bPFS. Given many patients were treated with MDT and/or ADT, clinical implication of the findings remains to be elucidated to guide treatment intensification based on findings on 18F-DCFPyL PET.
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