What’s behind 68 Ga-PSMA-11 uptake in primary prostate cancer PET? Investigation of histopathological parameters and immunohistochemical PSMA expression patterns

Purpose Prostate-specific membrane antigen (PSMA-) PET has become a promising tool in staging and restaging of prostate carcinoma (PCa). However, specific primary tumour features might impact accuracy of PSMA-PET for PCa detection. We investigated histopathological parameters and immunohistochemical PSMA expression patterns on radical prostatectomy (RPE) specimens and correlated them to the corresponding 68 Ga-PSMA-11-PET examinations. Methods RPE specimens of 62 patients with preoperative 68 Ga-PSMA-11-PET between 2016 and 2018 were analysed. WHO/ISUP grade groups, growth pattern (expansive vs. infiltrative), tumour area and diameter as well as immunohistochemical PSMA heterogeneity, intensity and negative tumour area (PSMA %neg ) were correlated with spatially corresponding SUV max on 68 Ga-PSMA-11-PET in a multidisciplinary analysis. Results All tumours showed medium to strong membranous (2–3 +) and weak to strong cytoplasmic (1–3 +) PSMA expression. Heterogeneously expressed PSMA was found in 38 cases (61%). Twenty-five cases (40%) showed at least 5% and up to 80% PSMA %neg . PSMA %neg , infiltrative growth pattern, smaller tumour area and diameter and WHO/ISUP grade group 2 significantly correlated with lower SUV max values. A ROC curve analysis revealed 20% PSMA %neg as an optimal cutoff with the highest sensitivity and specificity (89% and 86%, AUC 0.923) for a negative PSMA-PET scan. A multiple logistic regression model revealed tumoural PSMA %neg ( p < 0.01, OR = 9.629) and growth pattern ( p = 0.0497, OR = 306.537) as significant predictors for a negative PSMA-PET scan. Conclusions We describe PSMA %neg , infiltrative growth pattern, smaller tumour size and WHO/ISUP grade group 2 as parameters associated with a lower 68 Ga-PSMA-11 uptake in prostate cancer. These findings can serve as fundament for future biopsy-based biomarker development to enable an individualized, tumour-adapted imaging approach.