Evaluation of an artificial intelligence model based on multiparametric transrectal ultrasound for localizing clinically significant prostate cancer by simulation of targeted biopsies - Takeaways - MDSpire

Evaluation of an artificial intelligence model based on multiparametric transrectal ultrasound for localizing clinically significant prostate cancer by simulation of targeted biopsies

  • By

  • Daniel L. van den Kroonenberg

  • Florian Delberghe

  • Auke Jager

  • Arnoud W. Postema

  • Katelijne C. C. de Bie

  • Johannes B. Reitsma

  • Marije Zwart

  • Hessel Wijkstra

  • Anna Garrido-Utrilla

  • Joost de Baaij

  • Jean-Paul A. van Basten

  • Henk G. van der Poel

  • Harrie P. Beerlage

  • Massimo Mischi

  • Jorg R. Oddens

  • November 6, 2025

  • 0 min

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  • 1

    The study evaluates an AI model based on multiparametric transrectal ultrasound for detecting clinically significant prostate cancer.

  • 2

    Internal evaluation showed the AI model achieved a sensitivity of 0.82 and specificity of 0.43 for ISUP ≥ 2.

  • 3

    External evaluation indicated a sensitivity of 0.81 and specificity of 0.42 for the same ISUP criteria.

  • 4

    The AI model demonstrated a positive predictive value of 0.76 and a negative predictive value of 0.52 in internal evaluation.

  • 5

    Simulated targeted biopsies were used to assess the AI model's clinical performance and its potential for real-world application.

Original Source(s)

Evaluation of an artificial intelligence model based on multiparametric transrectal ultrasound for localizing clinically significant prostate cancer by simulation of targeted biopsies

  • by Daniel L. van den Kroonenberg, Florian Delberghe, Auke Jager, Arnoud W. Postema, Katelijne C. C. de Bie, Johannes B. Reitsma, Marije Zwart, Hessel Wijkstra, Anna Garrido-Utrilla, Joost de Baaij, Jean-Paul A. van Basten, Henk G. van der Poel, Harrie P. Beerlage, Massimo Mischi, Jorg R. Oddens

  • November 6, 2025

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