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Predicting Glioma Recurrence Using 18F-FDG PET/CT, MRI, and Tumor Markers: A Combined Approach.

Jingsong Wei1

  • 1Department of Neurosurgery, Northern Theater General Hospital, Shenyang, Liaoning Province, 110016, People's Republic of China.

International Journal of General Medicine
|May 12, 2025
PubMed
Summary

Combining 18F-FDG PET/CT, MRI, and tumor markers like monocyte-to-lymphocyte ratio (MLR) and neutrophil-to-lymphocyte ratio (NLR) significantly improves glioma recurrence prediction. This multimodal approach offers higher accuracy than individual tests for detecting tumor regrowth.

Keywords:
18F-FDG PET/CTMRIcorrelationgliomapredictive valuerecurrencetumor markers

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Area of Science:

  • Neuro-oncology
  • Radiology
  • Oncologic Imaging
  • Biomarkers

Background:

  • Glioma recurrence poses a significant clinical challenge, necessitating accurate and early detection methods.
  • Current diagnostic tools may have limitations in comprehensively assessing recurrence risk.

Purpose of the Study:

  • To evaluate the combined predictive value of 18F-FDG PET/CT, MRI, and specific tumor markers for glioma recurrence.
  • To determine if a multimodal diagnostic approach enhances the accuracy of glioma recurrence detection compared to individual modalities.

Main Methods:

  • Retrospective analysis of 82 glioma patients, divided into recurrence (n=19) and no recurrence (n=63) groups.
  • Acquisition of 18F-FDG PET/CT (SUVmax, L/N), MRI (ADC, CBF), and serum tumor markers (MLR, NLR).
  • Statistical comparison of parameters between groups, correlation analysis, and ROC curve analysis for diagnostic value.

Main Results:

  • Recurrent gliomas showed significantly higher SUVmax, L/N, NLR, and MLR, and lower ADC and CBF (P < 0.05).
  • All assessed parameters demonstrated significant correlations with glioma recurrence.
  • Combined modalities achieved an AUC of 0.856, outperforming individual markers in sensitivity and specificity.

Conclusions:

  • 18F-FDG PET/CT parameters (SUVmax, L/N), MRI metrics (ADC, CBF), and tumor markers (MLR, NLR) are significantly correlated with glioma recurrence.
  • The integrated assessment of these multimodal parameters offers superior diagnostic value for predicting glioma recurrence.