The increasing use of PSMA-PET/CT for restaging prostate cancer (PCa) leads to a patient shift from a non-metastatic situation based on conventional imaging (CI) to a metastatic situation. Since established therapeutic pathways have been designed according to CI, it is unclear how this should be translated to the PSMA-PET/CT results. This study aimed to investigate whether PSMA-PET/CT and clinical parameters could predict the visibility of PSMA-positive lesions on a bone scan (BS).
In four different centers, all PCa patients with BS and PSMA-PET/CT within 6 months without any change in therapy or significant disease progression were retrospectively selected. Up to 10 non-confluent clear bone metastases were selected per PSMA-PET/CT and SUVmax, SUVmean, PSMAtot, PSMAvol, density, diameter on CT, and presence of cortical erosion were collected. Clinical variables (age, PSA, Gleason Score) were also considered. Two experienced double-board physicians decided whether a bone metastasis was visible on the BS, with a consensus readout for discordant findings. For predictive performance, a random forest was fit on all available predictors, and its accuracy was assessed using 10-fold cross-validation performed 10 times.
A total of 43 patients were identified with 222 bone lesions on PSMA-PET/CT. A total of 129 (58.1%) lesions were visible on the BS. In the univariate analysis, all PSMA-PET/CT parameters were significantly associated with the visibility on the BS (p < 0.001). The random forest reached a mean accuracy of 77.6% in a 10-fold cross-validation.
These preliminary results indicate that there might be a way to predict the BS results based on PSMA-PET/CT, potentially improving the comparability between both examinations and supporting decisions for therapy selection.
Cancers. 2023 Nov 19*** epublish ***
Riccardo Laudicella, Matteo Bauckneht, Alexander Maurer, Jakob Heimer, Antonio G Gennari, Tania Di Raimondo, Gaetano Paone, Marco Cuzzocrea, Michael Messerli, Daniel Eberli, Irene A Burger
Department of Nuclear Medicine, Cantonal Hospital Baden, 5404 Baden, Switzerland., Nuclear Medicine, IRCCS Ospedale Policlinico San Martino, 16132 Genova, Italy., Department of Nuclear Medicine, University Hospital Zurich, University of Zurich, 8006 Zurich, Switzerland., Department of Mathematics, Seminar for Statistics, ETH Zurich, 8092 Zurich, Switzerland., Department of Health Sciences (DISSAL), University of Genova, 16126 Genova, Italy., Clinic for Nuclear Medicine and Molecular Imaging, Imaging Institute of Southern Switzerland, Ente Ospedaliero Cantonale, 6500 Bellinzona, Switzerland., Department of Urology, University Hospital of Zurich, 8006 Zurich, Switzerland.