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Modern integrative prostate cancer diagnostics.

Rainer Grobholz1,2, Felice Burn3,4, Lukas Prause5

  • 1Medical Faculty, University of Zurich, Zurich.

Current Opinion in Urology
|December 11, 2025
PubMed
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Artificial intelligence (AI) enhances prostate cancer diagnosis in radiology and pathology, improving accuracy and efficiency. Multimodal AI biomarkers are emerging for personalized treatment selection, though validation and monitoring are crucial for widespread adoption.

Area of Science:

  • Oncology
  • Radiology
  • Pathology
  • Medical Imaging
  • Artificial Intelligence

Background:

  • Prostate cancer diagnosis relies heavily on radiological and pathological assessments.
  • Artificial intelligence (AI) is increasingly being explored to augment these diagnostic processes.
  • Challenges in standardization and efficiency exist in current diagnostic workflows.

Purpose of the Study:

  • To review current AI applications in prostate cancer diagnosis via radiology and pathology.
  • To assess the performance and implementation hurdles of these AI tools.
  • To highlight novel multimodal AI biomarkers for prognosis and treatment selection.

Main Methods:

  • Review of contemporary studies on AI in prostate cancer radiological and pathological diagnosis.
Keywords:
artificial intelligenceartificial intelligence biomarkerdigital pathologymagnetic resonance imagingprostate cancer

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  • Analysis of AI performance metrics, including accuracy, reproducibility, and workflow efficiency.
  • Evaluation of emerging multimodal AI biomarker development and validation.

    • Main Results:

    • AI in radiology (MRI-based) demonstrates accuracy comparable to or exceeding expert radiologists for detecting significant prostate cancer.
    • AI in pathology shows high concordance with pathologists for cancer detection and Gleason grading, aiding standardization.
    • Multimodal AI integrating histopathology with clinical/molecular data shows promise for prognostic and predictive biomarkers, currently undergoing validation.

    Conclusions:

    • AI serves as a powerful assistive technology, boosting diagnostic accuracy, reproducibility, and efficiency in MRI and pathology for prostate cancer.
    • Integrated multimodal data is driving validated biomarkers for risk stratification and personalized treatment decisions.
    • Widespread AI adoption necessitates rigorous external validation, quality assurance, and post-deployment monitoring.