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Related Experiment Video

Updated: Jun 23, 2025

Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
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Predicting prostate cancer grade reclassification on active surveillance using a deep learning-based grading

Chien-Kuang C Ding1,2, Zhuo Tony Su1, Erik Erak1

  • 1Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Journal of the National Cancer Institute
|June 18, 2024
PubMed
Summary

A deep learning algorithm, AIRAProstate, accurately identified higher-risk prostate cancer (PCa) in active surveillance cohorts. This tool aids in better risk stratification for PCa management.

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Area of Science:

  • Oncology
  • Artificial Intelligence
  • Pathology

Background:

  • Deep learning (DL) algorithms for prostate cancer (PCa) Grade Group (GG) determination on biopsy slides lack clinical outcome validation.
  • Accurate grading is crucial for managing PCa, especially in active surveillance (AS) protocols.

Purpose of the Study:

  • To validate the utility of a DL-based algorithm (AIRAProstate) for regrading prostate biopsies in independent PCa active surveillance cohorts.
  • To assess the association of DL-based regrading with clinical outcomes like grade reclassification during AS.

Main Methods:

  • Utilized the AIRAProstate DL algorithm to regrade initial prostate biopsies from two independent PCa AS cohorts.
  • Analyzed the association between AIRAProstate-based upgrading (to GG≥2) and subsequent grade reclassification on AS.
  • Compared DL-based upgrading with contemporary uropathologist reviews in one cohort.

Main Results:

  • In the first cohort (n=138, initial GG1), AIRAProstate upgrading was significantly associated with grade reclassification on AS (OR=3.3, P=0.04), unlike uropathologist reviews.
  • In the validation cohort (n=169, all initial GG1), AIRAProstate upgrading also predicted grade reclassification on AS (HR=1.7, P=0.03).

Conclusions:

  • The DL-based AIRAProstate algorithm demonstrates significant utility in predicting grade reclassification for prostate cancer patients on active surveillance.
  • This AI tool shows promise for improving risk stratification and clinical decision-making in PCa management.