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Detection and Isolation of Cancer in Prostate Biopsies Using Stimulated Raman Histology and Artificial Intelligence
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Bridging the Gap from "Paper" to "Patient": An Overview and Quality Assessment of PET/CT-Based Radiomics for Prostate

Shuying Bian1, Yunjun Yang1, Zhiqiang Wang2

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

Academic Radiology
|June 18, 2026
PubMed
Summary

PET-based radiomics in prostate cancer show moderate quality but lack clinical readiness. Future studies need improved validation and open science for translation.

Keywords:
Positron emission tomographyProstate cancerQuality assessmentRQS 2.0Radiomics

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Area of Science:

  • Radiomics
  • Medical Imaging
  • Prostate Cancer Research

Background:

  • Positron-emission tomography (PET)-based radiomics is emerging for prostate cancer (PCa) analysis.
  • Assessing methodological quality and clinical translation maturity is crucial.
  • The Radiomics Quality Score (RQS 2.0) and Radiomics Readiness Level (RRL) framework offer standardized evaluation tools.

Purpose of the Study:

  • To systematically evaluate PET-based PCa radiomics studies using RQS 2.0 and RRL.
  • To identify current methodological strengths and weaknesses.
  • To determine the readiness of these studies for clinical implementation.

Main Methods:

  • Systematic literature search for PET-based PCa radiomics studies (2015-2025).
  • Evaluation using RQS 2.0, calculating total RQS and RQS percentage (RQS%).
  • Assessment of Radiomics Readiness Level (RRL) and inter-rater agreement (ICC, weighted Kappa).

Main Results:

  • 39 studies were analyzed, with a mean RQS of 40.4%.
  • Inter-rater agreement was excellent for RQS (ICC=0.89) and moderate for RRL (κ=0.41).
  • Studies showed deficiencies in automated segmentation, multicenter validation, and prospective validation, with no significant quality improvement over time.

Conclusions:

  • PET-based radiomics in PCa exhibit moderate methodological quality but are not yet mature for clinical translation.
  • Key areas for improvement include validation rigor and open science practices.
  • Fairness assessments are recommended to facilitate clinical adoption.