Purpose: To evaluate the performance of radiomic features (RF) derived from PSMA PET for intraprostatic tumor discrimination and non-invasive characterization of Gleason score (GS) and pelvic lymph node status. Patients and methods: Patients with prostate cancer (PCa) who underwent [ 68 Ga]-PSMA-11 PET/CT followed by radical prostatectomy and pelvic lymph node dissection were prospectively enrolled (n=20). Coregistered histopathological gross tumor volume (GTV-Histo) in the prostate served as reference. 133 RF were derived from GTV-Histo and from manually created segmentations of the intraprostatic tumor volume (GTV-Exp). Spearman´s correlation coefficients (ρ) were assessed between RF derived from the different GTVs. We additionally analyzed the differences in RF values for PCa and non-PCa tissues. Furthermore, areas under receiver-operating characteristics curves (AUC) were calculated and uni- and multivariate analyses were performed to evaluate the RF based discrimination of GS 7 and ≥8 disease and of patients with nodal spread (pN1) and non-nodal spread (pN0) in surgical specimen. The results found in the latter analyses were validated by a retrospective cohort of 40 patients. Results: Most RF from GTV-Exp showed strong correlations with RF from GTV-Histo (86% with ρ>0.7). 81% and 76% of RF from GTV-Exp and GTV-Histo significantly discriminated between PCa and non-PCa tissue. The texture feature QSZHGE discriminated between GS 7 and ≥8 considering GTV-Histo (AUC=0.93) and GTV-Exp (prospective cohort: AUC=0.91 / validation cohort: AUC=0.84). QSZHGE also discriminated between pN1 and pN0 disease considering GTV-Histo (AUC=0.85) and GTV-Exp (prospective cohort: AUC=0.87 / validation cohort: AUC=0.85). In uni- and multivariate analyses including patients of both cohorts QSZHGE was a statistically significant (p<0.01) predictor for PCa patients with GS ≥8 tumors and pN1 status. Conclusion: RF derived from PSMA PET discriminated between PCa and non-PCa tissue within the prostate. Additionally, the texture feature QSZHGE discriminated between GS 7 and GS ≥8 tumors and between patients with pN1 and pN0 disease. Our results support the role of RF in PSMA PET as a new tool for non-invasive PCa discrimination and characterization of its biological properties.

Purpose: We performed a voxel-wise comparison of 68Ga-HBED-CC-PSMA PET/CT with prostate histopathology to evaluate the performance of 68Ga-HBED-CC-PSMA for the detection and delineation of primary prostate cancer (PCa).Methodology: Nine patients with histopathological proven primary PCa underwent 68Ga-HBED-CC-PSMA PET/CT followed by radical prostatectomy. Resected prostates were scanned by ex-vivo CT in a special localizer and histopathologically prepared. Histopathological information was matched to ex-vivo CT. PCa volume (PCa-histo) and non-PCa tissue in the prostate (NPCa-histo) were processed to obtain a PCa-model, which was adjusted to PET-resolution (histo-PET). Each histo-PET was coregistered to in-vivo PSMA-PET/CT data.Results: Analysis of spatial overlap between histo-PET and PSMA PET revealed highly significant correlations (p < 10-5) in nine patients and moderate to high coefficients of determination (R²) from 42 to 82 % with an average of 60 ± 14 % in eight patients (in one patient R2 = 7 %). Mean SUVmean in PCa-histo and NPCa-histo was 5.6 ± 6.1 and 3.3 ± 2.5 (p = 0.012). Voxel-wise receiver-operating characteristic (ROC) analyses comparing the prediction by PSMA-PET with the non-smoothed tumor distribution from histopathology yielded an average area under the curve of 0.83 ± 0.12. Absolute and relative SUV (normalized to SUVmax) thresholds for achieving at least 90 % sensitivity were 3.19 ± 3.35 and 0.28 ± 0.09, respectively.Conclusions: Voxel-wise analyses revealed good correlations of 68Ga-HBED-CC-PSMA PET/CT and histopathology in eight out of nine patients. Thus, PSMA-PET allows a reliable detection and delineation of PCa as basis for PET-guided focal therapies.

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