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Next-Generation Advances in Prostate Cancer Imaging and Artificial Intelligence Applications
Kathleen H Miao1, Julia H Miao2, Mark Finkelstein1
1Department of Diagnostic, Molecular, and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Journal of Imaging
|November 26, 2025
Summary
Artificial intelligence (AI) is revolutionizing prostate cancer imaging, enhancing detection and treatment planning across MRI, PET/CT, and ultrasound. While challenges remain, AI integration promises more accurate diagnostics and personalized care for prostate cancer patients.
Area of Science:
- Radiology and Oncology
- Medical Imaging Informatics
- Artificial Intelligence in Medicine
Background:
- Prostate cancer is a major global health concern, with imaging crucial for diagnosis and management.
- Artificial intelligence (AI) offers significant potential to improve accuracy, efficiency, and consistency in prostate imaging.
Purpose of the Study:
- To review the integration and impact of AI in prostate cancer diagnostics.
- To explore AI applications across various imaging modalities and their clinical utility.
Main Methods:
- Review of AI applications in multiparametric MRI (mpMRI), PSMA PET/CT, and transrectal ultrasound (TRUS).
- Analysis of AI techniques including machine learning, deep learning, and radiomics for lesion detection, segmentation, and treatment planning.
- Evaluation of AI's role in PI-RADS scoring, biopsy targeting, and radiation therapy optimization.
Main Results:
- AI demonstrates enhanced capabilities in lesion detection, risk stratification, and automated segmentation.
- AI-assisted tools improve PI-RADS scoring accuracy and guide targeted biopsies effectively.
- AI shows potential in optimizing radiation therapy planning and delivery for prostate cancer.
Conclusions:
- AI integration in prostate imaging shows transformative potential for diagnosis and treatment.
- Challenges in data heterogeneity, generalizability, and clinical implementation need to be addressed.
- Multimodal AI models and multidisciplinary collaboration are key to advancing precision medicine in prostate cancer care.
