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Related Concept Videos

Positron Emission Tomography01:29

Positron Emission Tomography

Positron emission tomography (PET) is a medical imaging technique involving radiopharmaceuticals — substances that emit short-lived radiation. Although the first PET scanner was introduced in 1961, it took 15 more years before radiopharmaceuticals were combined with the technique and revolutionized its potential.
One of the main requirements of a PET scan is a positron-emitting radioisotope, which is produced in a cyclotron and then attached to a substance used by the part of the body being...

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A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound
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A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound

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An interpretable 1⁸F-PSMA PET/CT-MRI model for optimizing prostate biopsy decisions.

Shuaitao Xiong1,2, Jiangyu Ma3, Han Li1

  • 1Department of Urology, Beijing Hospital, National Center of Gerontology; National Clinical Research Center for Gerontology; The Key Laboratory of Geriatrics of NHC; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.

European Journal of Nuclear Medicine and Molecular Imaging
|May 23, 2026
PubMed
Summary
This summary is machine-generated.

A new multimodal model integrating 18F-PSMA PET/CT and MRI accurately predicts clinically significant prostate cancer (csPCa) in biopsy-naïve men. This tool can significantly reduce unnecessary biopsies while maintaining oncological safety.

Keywords:
Biopsy-naïvePSMA PET/CTProstate cancerRadiomicsRisk stratification

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Use of MRI-ultrasound Fusion to Achieve Targeted Prostate Biopsy
09:11

Use of MRI-ultrasound Fusion to Achieve Targeted Prostate Biopsy

Published on: April 9, 2019

Area of Science:

  • Oncology
  • Radiology
  • Medical Imaging
  • Machine Learning

Background:

  • Distinguishing indolent from clinically significant prostate cancer (csPCa) in biopsy-naïve men is challenging.
  • Current diagnostic methods can lead to unnecessary prostate biopsies.

Purpose of the Study:

  • Develop and validate an interpretable multimodal model to predict csPCa.
  • Integrate 18F-PSMA PET/CT, mpMRI, and clinical variables for improved biopsy decision-making.

Main Methods:

  • Retrospective analysis of 302 biopsy-naïve patients.
  • Extracted radiomic features from 18F-PSMA PET and mpMRI using a dual-level ROI strategy.
  • Developed a Fusion model combining radiomics and clinical data, validated using AUC, DCA, and CIC; SHAP values used for feature interpretation.

Main Results:

  • The Fusion model achieved AUCs of 0.92 (internal) and 0.92 (external validation).
  • In PI-RADS 3 cases, the model yielded an AUC of 0.97, outperforming standard assessments.
  • Risk stratification with the Fusion model could avoid 72-83% of unnecessary biopsies with low missed diagnosis rates (4-9.5%).
  • PET-derived intensity and textural features were identified as dominant predictors by SHAP analysis.

Conclusions:

  • The interpretable Fusion model integrating 18F-PSMA PET/CT and mpMRI shows superior diagnostic performance for csPCa.
  • This approach can serve as an effective non-invasive triage tool, reducing unnecessary biopsies and enhancing oncological safety.