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Artificial intelligence (AI) enhances positron emission tomography (PET) imaging beyond [18F]F-FDG. AI-powered radiomics analysis of tracers like [18F]F-FET, [18F]F-FLT, and [11C]C-MET improves tumor characterization and diagnostic performance.

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Area of Science:

  • Nuclear Medicine
  • Radiology
  • Artificial Intelligence

Background:

  • Previous review focused on AI in [18F]F-FDG PET.
  • This review examines AI's impact on radiomics from other PET tracers.

Purpose of the Study:

  • To review the impact of PET-derived radiomics data on diagnostic performance of other PET radiotracers.
  • To highlight AI's role in improving PET imaging beyond [18F]F-FDG.

Main Methods:

  • Review of literature on AI applications in PET imaging using tracers like [18F]F-FET, [18F]F-FLT, and [11C]C-MET.
  • Analysis of PET-derived radiomics features and their diagnostic utility.

Main Results:

  • [18F]F-FET PET-derived radiomics show potential in glioma detection, characterization, heterogeneity assessment, and survival stratification.
  • [18F]F-FLT PET shows promise in evaluating glioma, correlating with Ki-67, and guiding radiation therapy.
  • [11C]C-MET PET radiomics aid in predicting tumor grade, distinguishing recurrence, and monitoring treatment.
  • Radiomics from various other tracers ([18F]F-DOPA, [18F]F-FACBC, etc.) offer valuable tumor characterization and outcome prediction.

Conclusions:

  • AI utilizing tracers beyond [18F]F-FDG can significantly enhance PET imaging diagnostic performance for specific indications.
  • AI-derived features provide clinicians with information not visible to the naked eye, aiding daily practice.