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Positron Emission Tomography (PET) is a medical imaging technique that provides crucial insights into the body's physiological functions at a molecular level. It is an indispensable resource for diagnosing, staging, and monitoring various illnesses, notably cancer, neurological disorders, and cardiovascular conditions.
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Related Experiment Video

Updated: Jan 18, 2026

A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound
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Radiomics Features from Different Prostatic Zones on 18F-PSMA-1007 PET/CT for Predicting Persistent PSA in Prostate

Licong Li1, Jian Xu1, Shuying Bian1

  • 1The Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou 325000, China.

Cancers
|September 13, 2025
PubMed
Summary
This summary is machine-generated.

Radiomics features from specific prostate subregions on 18F-PSMA-1007 PET/CT can predict persistent prostate cancer. Combining a radiomics model with the PSA model significantly improves prediction accuracy.

Keywords:
PET/CTpersistent PSAprostate cancerradiomicstumor microenvironment

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Area of Science:

  • Radiology
  • Oncology
  • Medical Imaging

Background:

  • Persistent prostate cancer after treatment poses a clinical challenge.
  • Accurate prediction of persistent prostate cancer is crucial for guiding treatment decisions.

Purpose of the Study:

  • To investigate the predictive value of radiomics features (RFs) from different prostate subregions on 18F-PSMA-1007 PET/CT for persistent prostate-specific antigen (PSA).
  • To develop and validate radiomics models, individually and combined with PSA levels, for predicting persistent PSA.

Main Methods:

  • Retrospective analysis of 354 patients with localized prostate cancer.
  • Prostate segmentation into three zones (intra, peri, norm) based on SUVmax on 18F-PSMA-1007 PET/CT.
  • Development of five radiomics models and combined models with PSA, evaluated using ROC curves and AUC.

Main Results:

  • Radiomics models (model-ip, model-ipn, model-intra) showed varying predictive performance across cohorts.
  • The combined model integrating model-ip and PSA achieved the highest AUCs (0.78 training, 0.78 internal validation, 0.89 external validation).

Conclusions:

  • Radiomics features from distinct prostate subregions on 18F-PSMA-1007 PET/CT offer differential predictive capabilities for persistent PSA.
  • A combined radiomics-PSA model, particularly incorporating the 20-45% and 45-100% SUVmax zones, demonstrates enhanced accuracy in predicting persistent PSA.