Priapism is defined as abnormal prolonged penile erection occurring beyond or unrelated to sexual interest. The disorder is enigmatic yet devastating because of its elusive etiology, irreversible erectile tissue damage, and resultant erectile dysfunction (ED). Current management strategies suffer from a poor understanding of the pathophysiology, especially at the molecular level. The traditional treatments are based more on empirical rather than evidence-based knowledge. The outcomes for restoration of normal erectile function are poor, especially for stuttering priapism. Therefore, it is critical to understand priapism from a molecular level, to formulate treatment strategies and to establish rational prevention strategies for high-risk populations, such as sickle cell disease (SCD) patients and cases of the stuttering variant. This review focuses on the recent advances at the molecular level in priapism and penile erection, and applies the recent knowledge to the treatment of stuttering priapism.
Hormones ; therapeutic use ; Humans ; Ischemia ; complications ; Male ; Penile Prosthesis ; Penis ; blood supply ; Priapism ; drug therapy ; etiology ; surgery ; Recurrence

Recently, artificial intelligence (AI) has been widely applied in the diagnosis and treatment of urinary diseases with the development of data storage, image processing, pattern recognition and machine learning technologies. Based on the massive biomedical big data of imaging and histopathology, many urinary system diseases (such as urinary tumor, urological calculi, urinary infection, voiding dysfunction and erectile dysfunction) will be diagnosed more accurately and will be treated more individualizedly. However, most of the current AI diagnosis and treatment are in the pre-clinical research stage, and there are still some difficulties in the wide application of AI. This review mainly summarizes the recent advances of AI in the diagnosis of prostate cancer, bladder cancer, kidney cancer, urological calculi, frequent micturition and erectile dysfunction, and discusses the future potential and existing problems.
Artificial Intelligence ; trends ; Diagnosis, Computer-Assisted ; trends ; Humans ; Image Processing, Computer-Assisted ; Urologic Diseases ; diagnosis