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The value of a nomogram based on 18F-FDG PET/CT metabolic parameters and metabolic heterogeneity in predicting distant metastasis in gastric cancer

  • 0Department of Nuclear Medicine, Second Affiliated Hospital of Fujian Medical University, Donghai Street No. 950, Fengze District, Quanzhou 362018, PR China.
Japanese Journal of Clinical Oncology +

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December 10, 2024

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December 10, 2024

View abstract on PubMed

Summary

This summary is machine-generated.

Metabolic heterogeneity index (HI)-1 from 18F-FDG PET/CT is a key predictor of distant metastasis in gastric cancer. Combining HI-1 with tumor marker CA72-4 improves prediction accuracy and clinical benefit for patients.

Area Of Science

  • Oncology
  • Nuclear Medicine
  • Radiomics

Background

  • Gastric cancer poses a significant global health challenge, with distant metastasis being a primary determinant of patient outcomes.
  • Accurate prediction of distant metastasis is crucial for effective treatment planning and improving survival rates in gastric cancer patients.

Purpose Of The Study

  • To evaluate the predictive value of metabolic parameters and metabolic heterogeneity derived from pretreatment 18F-FDG PET/CT for distant metastasis in gastric cancer.
  • To develop and validate a nomogram model incorporating these parameters for enhanced metastasis prediction.

Main Methods

  • Eighty-six gastric adenocarcinoma patients underwent pretreatment 18F-FDG PET/CT scans.
  • Metabolic parameters (SUVmax, SUVmean, MTV, TLG) and heterogeneity indices (HI-1, HI-2) were analyzed.
  • A nomogram prediction model was built using a training cohort and validated on a separate cohort.

Main Results

  • Distant metastasis was observed in 36% of patients.
  • Higher levels of CA72-4, MTV, TLG, and HI-1 were significantly associated with distant metastasis (P < .05).
  • CA72-4 and HI-1 were identified as independent risk factors for distant metastasis (P < .05).
  • The nomogram demonstrated high predictive performance in both training (AUC: 0.874) and validation (AUC: 0.915) cohorts.

Conclusions

  • Metabolic heterogeneity index (HI)-1 is an independent predictor of distant metastasis in gastric cancer.
  • A combined prediction model using HI-1 and CA72-4 offers significant clinical utility and improved prediction accuracy.

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