Prostate Cancer Stage

99mTc-QULIC-5-P1 is a new radiotracer targeting PSMA, which is promising as an excellent imaging agent applicable to PSMA positive prostate cancer. This study will investigate the safety, biodistribution and potential usefulness of 99mTc-QULIC-5-P1 SPECT imaging for the diagnosis of lesions in PSMA positive prostate cancer.

The aim of this clinical trial is whether artificial intelligence models can be used for accurate clinical preoperative diagnosis and postoperative diagnosis of pathological findings, and will also measure the accuracy of the predictions made by the artificial intelligence models.The main target questions addressed by the model building are: 1. whether the AI model can learn from preoperative MRI and postoperative Whole Slide Images so as to accurately predict information such as benignness or malignancy, aggressiveness, grading, subtypes, genes, etc. for participants suspected of having prostate cancer preoperatively/puncturally. 2. whether the AI model is capable of learning postoperative macropathology slides to enable outcome diagnosis of surgical pathology slides in new participants. Participants will: 1. complete an MRI examination and have their MRI images analysed by the established AI model to make an accurate diagnosis of them. 2. Based on the diagnosis, if prostate cancer is predicted, they will undergo radical prostate cancer surgery and refine their surgical pathology.

It is important to decrease the remifentanil dose for general anesthesia maintenance when using remimazolam. We will evaluate the effect of binaural sound on general anesthesia maintenance with remimazolam infusion.