Benign prostatic hyperplasia (BPH) is a prevalent condition among older men that is characterized by the enlargement of the prostate gland and compression of the urethra, which often results in lower urinary tract symptoms, such as frequent urination, difficulty in starting urination, and incomplete bladder emptying. The development of BPH is thought to be primarily due to an imbalance between cell proliferation and apoptosis, underlying inflammation, epithelial-to-mesenchymal transition, and local paracrine and autocrine growth factors, although the exact molecular mechanisms are not yet fully understood. Anatomical structures considered natural and benign observations can occasionally present multi-parametric magnetic resonance imaging appearances that resemble prostate cancer (PCa), posing a risk of misinterpretation and generating false-positive outcomes and subsequently, unnecessary interventions. To aid in the diagnosis of BPH, distinguish it from PCa, and assist with treatment and outcome prediction, various Artificial Intelligence (AI)-based algorithms have been proposed to assist clinicians in the medical practice. Here, we explore the results of these new technological advances and discuss their potential to enhance clinicians' cognitive abilities and expertise. There is no doubt that AI holds extensive medical potential, but the cornerstone for secure, efficient, and ethical integration into diverse medical fields still remains well-structured clinical trials.
Keywords: Artificial Intelligence; benign prostatic hyperplasia; diagnosis; management; prostate.
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