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Prognostic Value of Combined FDG PET and MRI Analysis of Cervical Cancer: A Systematic Review and Meta-Analysis
William Wei1, Dominic Ku2, Natalie Rutherford3
1Austin Health, Deakin University, Heidelberg, Victoria, Australia.
Introduction:
Accurate risk stratification in cervical cancer remains challenging, and imaging biomarkers may add prognostic value beyond staging. This systematic review was conducted to evaluate the published data on the integrated use of 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) and magnetic resonance imaging (MRI) in cervical cancer, with a specific analysis of the correlation between functional and anatomical imaging parameters and the identification of prognostic imaging markers.
Methods:
A comprehensive database search was conducted to identify studies that examined functional and anatomical imaging parameters using PET and MRI in the analysis of cervical cancer. A total of 328 articles were screened, and 107 full-text articles were reviewed. 34 studies were ultimately included in the systematic review.
Results:
Thirty Four papers were reviewed for systematic review. Key functional and anatomical imaging parameters were analysed. 11 papers analysed PET standardised uptake value (SUV) and MRI apparent diffusion coefficient (ADC) correlations which were suitable for meta-analysis. Moderate negative correlations between SUV and ADC values were statistically significant across multiple studies. Furthermore, metabolic tumour volume (MTV) and total lesion glycolysis (TLG) were shown to be statistically correlated with tumour grade, FIGO staging and survival outcomes (disease-free survival, DFS, and overall survival, OS). Imaging parameters predictive of local recurrence, metastatic disease and survival outcomes were analysed.
Conclusion:
This systematic review of 34 studies on FDG PET and MRI in cervical cancer shows that imaging biomarkers predict recurrence, metastasis, and outcomes. Collectively, the literature supports the potential role of integrated PET/MRI biomarkers for improved prognostic stratification beyond conventional staging systems.
