Dual time point imaging of staging PSMA PET/CT quantification; spread and radiomic analyses.

Abstract

The aims were to evaluate the performance of models that predict Gleason Grade (GG) groups with radiomic data obtained from the prostate gland in dual time 68Ga-Prostate Specific Membrane Antigen (PSMA) Positron Emission Tomography/Computerized Tomography (PET/CT) images for prostate cancer (PCa) staging, and to analyze the contribution of late imaging to the radiomic model and to evaluate the relationship of the distance between tumor foci in the body (Dmax) obtained in early PET images with histopathology and prostate specific antigen (PSA) value. Between October 2020 and August 2021, 41 patients who underwent 68Ga-PSMA PET/CT for staging of PCa were retrospectively analyzed. Volumetric and radiomics data were obtained from early and late PSMA PET images. The differences between age, metastasis status, PSA, standard uptake value (SUV), volumetric and radiomics parameters between GG groups were analyzed. Early and late PET radiomic models were created, area under curve (AUC), sensitivity, specificity and accuracy values of the models were obtained. In addition, the correlation of Dmax values with total PSMA-tumor volume (TV), Total lesion (TL)-PSMA and PSA values was evaluated. In metastatic patients, the difference in Dmax between GG groups was analyzed. There was a significant difference between patients with GG ≤ 3 and > 3 in 35 of the early PET radiomic features. In the early PET model, multivariate analyses showed that GLRLM_RLNU and PSA were the most meaningful parameters. The AUC, sensitivity, specificity and accuracy values of the early model in detecting patients with GG > 3 were calculated as 0.902, 76.2%, 84% and 78.1%, respectively. In 36 late PET radiomic features, there was a significant difference between patients with GG ≤ 3 and > 3. In multivariate analyses; SHAPE_compacity and PSA were obtained as the most meaningful parameters. The AUC, sensitivity, specificity and accuracy values of the late model in detecting patients with GG > 3 were calculated as 0.924, 85.7%, 85% and 85.4%. There was a strong correlation between Dmax and PSA values (p < 0.001, rho: 0.793). Dmax showed strong correlation with PSMA-TVtotal and TL-PSMAtotal (p < 0.001, rho: 0.797; p < 0.001, rho: 0.763, respectively). In patients with metastasis, median Dmax values of the GG > 3 group were higher than GG ≤ 3 group; A statistically significant difference was obtained between these two groups (p=0.023). Model generated from the late PSMA PET radiomic data had better performance in the current study. Without the use of invasive methods, the heterogeneity and aggressiveness of the primary tumor and the prediction of GG groups may be possible with 68Ga-PSMA PET/CT images obtained for diagnostic purposes especially with late PSMA PET/CT imaging.