A multivariable prediction model combining 18F-PSMA PET/CT and mpMRI for clinically significant prostate cancer: development and validation - Takeaways - MDSpire

A multivariable prediction model combining 18F-PSMA PET/CT and mpMRI for clinically significant prostate cancer: development and validation

  • By

  • Chaojian Yu

  • Zihou Zhao

  • Peidong Tian

  • Jingcheng Zhou

  • Lin Cai

  • Jianhui Qiu

  • Kan Gong

  • May 18, 2026

  • 0 min

Share

  • 1

    A multivariable model was developed to predict clinically significant prostate cancer (csPCa) using clinical and imaging parameters.

  • 2

    The study included 1305 patients who underwent both mpMRI and 18F-PSMA PET/CT with biopsy at Peking University First Hospital.

  • 3

    The final model retained three predictors: PRIMARY score, PI-RADS score, and PSA density (PSAD), achieving an AUC of 0.916 in the training cohort.

  • 4

    The model demonstrated good calibration and clinical utility, outperforming individual imaging parameters in predicting csPCa.

  • 5

    Integrating 18F-PSMA PET/CT and mpMRI enhances risk stratification for csPCa, aiding in optimizing biopsy decisions.

Original Source(s)

A multivariable prediction model combining 18F-PSMA PET/CT and mpMRI for clinically significant prostate cancer: development and validation

  • by Chaojian Yu, Zihou Zhao, Peidong Tian, Jingcheng Zhou, Lin Cai, Jianhui Qiu, Kan Gong

  • May 18, 2026

Related Content

Longitudinal investigation of psychological adaptation and its determinants in primary caregivers following thyroid cancer surgery

Effect of aesthetic nursing interventions on the health-related quality of life of cervical cancer patients after treatment

Machine learning-based identification of an oxidative phosphorylation signature for prognosis, immune infiltration, and drug sensitivity in ovarian cancer