AI for BPH Surgical Decision-Making: Cost Effectiveness and Outcomes.

Area of Science:

• Urology
• Medical Imaging
• Artificial Intelligence

Background:

• Benign prostatic hyperplasia (BPH) affects nearly 70% of men over 60, presenting clinical challenges due to varied symptoms and treatment responses.
• Surgical intervention for BPH is considered after failed medical therapy, as per American Urological Association guidelines.

Purpose of the Study:

• To review the role of artificial intelligence (AI) in improving decision-making for benign prostatic hyperplasia (BPH) management.
• To explore AI applications in diagnosis, outcome prediction, and treatment optimization for BPH.

Main Methods:

• Analysis of non-invasive imaging modalities (multiparametric MRI, Ultrasound) using AI.
• Development of AI models integrating serum biomarkers and histopathology.
• Utilizing AI for predicting patient outcomes and optimizing therapeutic strategies.

Main Results:

• AI enhances diagnostic precision for BPH and distinguishes it from prostate cancer (PC) with high accuracy.
• AI models improve diagnostic accuracy, potentially reducing the need for invasive procedures.
• AI aids in personalized medicine by predicting post-treatment outcomes and optimizing therapies.

Conclusions:

• AI demonstrates significant potential in streamlining BPH management and improving patient outcomes.
• AI applications can help reduce healthcare costs associated with BPH.
• Further research and development are crucial for integrating AI into clinical workflows and establishing standardized evaluation metrics for BPH management.