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Related Experiment Video

Updated: Jul 8, 2025

Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence
08:08

Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence

Published on: June 10, 2025

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Stimulated Raman Histology Interpretation by Artificial Intelligence Provides Near-Real-Time Pathologic Feedback for

M P Mannas1,2,3, F M Deng4, A Ion-Margineanu5

  • 1Department of Urologic Sciences, University of British Columbia, Vancouver, British Columbia, Canada.

The Journal of Urology
|December 15, 2023
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) can interpret stimulated Raman histology (SRH) images of prostate biopsies in real-time. This AI system achieved 96.5% accuracy in detecting prostate cancer, significantly speeding up diagnosis.

Keywords:
Raman spectroscopyartificial intelligenceprostate cancer

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Area of Science:

  • Digital pathology
  • Artificial intelligence in medicine
  • Optical imaging techniques

Background:

  • Stimulated Raman histology (SRH) offers real-time, high-resolution imaging of unprocessed tissue.
  • SRH significantly reduces the time required for prostate biopsy interpretation.
  • AI has the potential to further streamline pathological analysis.

Purpose of the Study:

  • To evaluate an AI convolutional neural network's ability to interpret SRH images of prostate biopsies.
  • To assess the diagnostic performance of AI in detecting prostate cancer using SRH.

Main Methods:

  • Prospective imaging of unprocessed prostate biopsies using SRH.
  • Ground truth established by genitourinary pathologists on conventionally processed cores.
  • AI network trained on 303 biopsies and validated on an independent set of 113 biopsies.

Main Results:

  • SRH image generation time: 2-2.75 minutes.
  • AI classification time: approximately 1 minute.
  • AI demonstrated 96.5% accuracy, 96.3% sensitivity, and 96.6% specificity for prostate cancer detection.

Conclusions:

  • SRH enables real-time, accurate identification of prostate cancer without tissue processing.
  • AI interpretation of SRH images provides near-real-time pathological feedback.
  • This technology can aid physicians in prostate cancer diagnosis and treatment.