Integrating Artificial Intelligence into Prostate MR Imaging: Technical Foundations, Clinical Applications, and...

Area of Science:

• Radiology
• Medical Imaging
• Artificial Intelligence

Background:

• Prostate MRI is crucial for cancer diagnosis but is technically demanding and prone to variability.
• Abbreviated MRI protocols, like non-contrast (biparametric) MRI, increase the need for efficiency and consistency.

Purpose of the Study:

• To provide a comprehensive overview of AI integration in prostate MRI.
• To review AI's technical foundations, clinical applications, and workflow implications.
• To discuss challenges and future directions for AI in prostate MRI.

Main Methods:

• Non-systematic narrative review of AI in prostate MRI.
• Summarized machine learning and deep learning concepts relevant to prostate imaging.
• Reviewed evidence for AI in image quality, segmentation, detection, and risk stratification.

Main Results:

• AI shows promise in enhancing image quality, segmentation, lesion detection, and risk stratification in prostate MRI.
• Human-AI collaboration models and AI's role in supporting equivocal findings are discussed.
• Commercial AI tools and their impact on reporting, training, and standardization are examined.

Conclusions:

• AI is a valuable decision-support tool for prostate MRI, complementing radiologists' expertise.
• Challenges include validation, generalizability, and ethical/regulatory considerations.
• Successful AI implementation requires thoughtful integration, robust validation, and user training for improved prostate cancer care.