Abstract :
Keywords: .sup.18F-DCFPyL; PET/CT; PSMA; prostate cancer; biochemical recurrence; histopathology Objectives To assess the correlation of pathological radical prostatectomy (RP) specimen features and prostate-specific antigen (PSA) characteristics to imaging findings on subsequent .sup.18F-DCFPyL positron emission tomography/computed tomography (PET/CT) in patients with biochemical failure (BF). Patients and Methods Retrospective analysis of combined .sup.18F-DCFPyL PET/CT database of patients from centres in Australia and New Zealand was performed. A total of 205 patients presenting with BF after RP were included in this study. Imaging findings on .sup.18F-DCFPyL PET/CT were recorded and correlated with the PSA characteristics at BF and pathological features of the original tumour. Results Of the 205 patients, 120 (58.5%) had evidence of abnormal prostate-specific membrane antigen (PSMA) expression compatible with recurrent prostate cancer. Increasing PSA velocity (P = 0.01), International Society of Urological Pathology (ISUP) Grade Group (P = 0.02), lymphovascular invasion (P = 0.05) and nodal positivity (P = 0.02) at the time of RP were more likely to demonstrate PSMA positivity. Multivariable logistic regression revealed a higher PSA level prior to PSMA PET/CT (P Conclusion .sup.18F-DCFPyL PET/CT positivity, both generally and site specific, correlates with PSA and RP pathological factors. Our results echo cohorts focussing on post-RP patients, those imaged with .sup.68Ga-PSMA and those concerning biochemical persistence. Nomograms that include risk factors for 'PSMA-positive recurrence' in the BF population may increase the catchment of patients with disease confined to the prostate bed or pelvis who have a greater probability of prolonged disease-free survival. CAPTION(S): Fig.S1. Model performance for predicting prostate cancer isolated to prostate bed (A and B), extraprostatic but intrapelvic prostate cancer (C and D) and prostate cancer limited to the pelvis (E and F). Byline: Elisa Perry, Arpit Talwar, Kim Taubman, Michael Ng, Lih-Ming Wong, Tom R. Sutherland