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Related Experiment Video

Updated: Feb 14, 2026

Use of MRI-ultrasound Fusion to Achieve Targeted Prostate Biopsy
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Is Systematic Biopsy Mandatory in All MRI-Guided Fusion Prostate Biopsies? A Machine Learning Prediction Model.

Omer Longo1,2, Gil Raviv1,3, Miki Haifler1,2

  • 1Faculty of Medical and Health Sciences, Tel Aviv University, Tel Aviv 6997801, Israel.

Cancers
|February 13, 2026
PubMed
Summary

This study developed a prediction model to identify patients needing systematic biopsy alongside targeted biopsy for higher-risk prostate cancer detection. The model aids in deciding biopsy strategies, potentially reducing adverse events while maintaining high detection rates.

Keywords:
biopsycancerfusionmachine learningprostatesystematic

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Area of Science:

  • Urology
  • Oncology
  • Medical Imaging

Background:

  • MRI/US fusion biopsy is crucial for prostate cancer diagnosis.
  • Distinguishing higher-risk prostate cancer in systematic biopsies versus targeted biopsies is clinically significant.
  • Predictive models can optimize biopsy strategies and patient outcomes.

Purpose of the Study:

  • To develop and validate a prediction model for identifying patients with higher-risk prostate cancer in systematic biopsies during MRI/US fusion biopsy.
  • To assess the clinical utility and variable importance of the developed prediction model.

Main Methods:

  • An extreme gradient boosting model was trained and tested using clinical and radiographic data from 529 patients.
  • Key predictors including prostate volume, PSA density (PSAD), patient age, and PSA were identified.
  • Model performance was evaluated using ROC curve analysis and decision curve analysis.

Main Results:

  • The model achieved an area under the ROC curve of 0.82 and a negative predictive value of 0.92.
  • 15.5% of patients had higher-risk prostate cancer detected in systematic biopsies.
  • The model demonstrated clinical benefit at threshold probabilities between 0 and 0.5.

Conclusions:

  • A validated prediction model can accurately identify patients who require systematic biopsy in addition to targeted biopsy.
  • This model can assist in clinical decision-making regarding the extent of prostate biopsy.
  • Implementing this model may reduce adverse events and maintain high cancer detection rates.