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.
Patients with suspected PCa (elevated PSA or suspicious positive lesions on ultrasound or MRI results);
Previous treatment of the prostate in any form, including surgery, radiotherapy/chemotherapy, endocrine therapy, targeted therapy and immunotherapy;
Patients with any item missing from the baseline clinical and pathological information;
Patients with a history of other malignancies, serious comorbidities or other health problems;
Unable to provide/sign an informed consent form;
Shao Pengfei
Lead sponsor
The First Affiliated Hospital with Nanjing Medical University
Sponsor institution
Institute of Automation, Chinese Academy of Sciences
Collaborator