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68Ga-PSMA PET/CT-Based Model Predicts Perineural Invasion of Prostate Cancer with Whole-Mount Sections

  • Jie Gao,
  • Yao Fu,
  • Kuiqiang He,
  • Qinfeng Xu,
  • Feng Wang,
  • Hongqian Guo

摘要

Purpose

To develop a novel risk model incorporating 68Ga-PSMA PET/CT parameters for prediction of perineural invasion (PNI) of prostate cancer (PCa).

Methods

The study retrospectively enrolled 192 PCa patients with preoperative multiparametric MRI, 68Ga-PSMA PET/CT and radical specimen. Imaging parameters were derived from both mpMRI and PET/CT images. S100 immunohistochemistry staining was conducted to evaluate PNI of PCa. Significant predictors were derived with univariate and multivariate logistic regression analyses, and the PNI-risk nomogram was constructed with significant predictors. Internal discrimination validation was performed with receiver operating characteristic analysis. Calibration curves were plotted, decision curve and clinical impact curve analysis were performed for clinical benefit exploration.

Results

With the median peritumoral nerve density of 6, patients were stratified as low-PNI group (nerve density < 6, n = 78, 40.6%) and high-PNI group (nerve density ≥ 6, n = 114, 59.4%). Compared with low-PNI PCa, high-PNI PCa harbored significantly larger imaging lesion diameter (P < 0.001), higher PI-RADS score (P = 0.009), higher SUVmax (P < 0.001), larger tumor diameter (P = 0.024) and higher Gleason grade group (P < 0.001). Further, with univariate and multivariate analyses, imaging lesion diameter (OR 2.98, 95% CI 1.73–5.16, P = 0.004) and SUVmax (OR 3.59, 95%CI 2.32–5.55, P < 0.001) and were identified as independent predictors for PNI in PCa, and a PNI-risk nomogram incorporating these two predictors was constructed. The PNI-risk nomogram demonstrated considerable calibration (mean absolute error 0.026) and discrimination (area under the curve = 0.889, sensitivity 73.1%, specificity 97.4%) abilities, harboring net benefits with threshold probabilities range from 0 to 0.80.

Conclusion

68Ga-PSMA PET/CT-based model could effectively predict the perineural invasion of PCa. These results may help with the decision-making on active surveillance, focal therapy and surgery approach. Additionally, patients suspicious of high-density PNI PCa should receive more radical treatment than low-PNI PCa.