Diagnostic performance of quantitative measures from [18F]FDG PET/CT, [18F]FEC PET/CT, and DW-MRI in the detection of lymph node metastases in endometrial and cervical cancer: data from the MAPPING study
Year: 2025
Type: article
Abstract: Purpose To evaluate the diagnostic performance of quantitative measures derived from [ 18 F]FDG PET/CT, [ 18 F]FEC PET/CT, and DW-MRI in the detection of lymph node metastases in endometrial and cervical cancer with comparison to standard visual PET analysis with histology as the reference standard. Methods Subanalysis of quantitative data from the prospective multicentre MAPPING study. Nodal and tumour SUV max from [ 18 F]FDG PET/CT and [ 18 F]FEC PET/CT and ADC mean from DW-MRI were documented. Nodal-to-tumour ratios (NTR) and SUV max -to-ADC mean ratio (STAR) were calculated. Optimal cut-offs of quantitative measures were compared to visual assessment on a regional basis using histopathology as the reference standard. Results Scans from 112 patients (36 cervical and 76 endometrial cancers; 340 nodal regions) were eligible for quantitative image analysis. Lower ADC mean on DW-MRI was observed in metastatic nodes for cervical cancer but not for endometrial cancer. Quantitative measures were significantly higher in malignant than benign nodal regions on [ 18 F]FDG PET/CT and [ 18 F]FEC PET/CT in endometrial cancer. SUV max cut-offs showed similar performance to visual assessment in the diagnosis of metastatic lymph nodes in endometrial cancer whilst ADC mean cut-offs showed significantly lower specificity than visual assessment. Interobserver agreement was excellent for SUV max measurements on both [ 18 F]FDG PET/CT and [ 18 F]FEC PET/CT, but poor for ADC mean on DW-MRI. Conclusion Quantitative measures from [ 18 F]FDG PET/CT, [ 18 F]FEC PET/CT, or DW-MRI did not outperform visual assessment in the detection of nodal metastases in endometrial cancer. Therefore, the implementation of these quantitative measures as standalone diagnostic tools in routine clinical practice is not recommended.
Authors: Ben G King, Nishat Bharwani, William Wilson, Gary J.R Cook, Aslam Sohaib, Marielle Nobbenhuis, Victoria Warbey, Marc E. Miquel, Dow-Mu Koh, Katja N De Paepe, Pierre Martin-Hirsch, Sadaf Ghaem-Maghami, Christina Fotopoulou, Helen Stringfellow, Sudha Sundar, Ranjit Manchanda, Anju Sahdev, Allan Hackshaw, Tara D. Barwick, Andrea G. Rockall
Institutions: University of Edinburgh, Imperial College Healthcare NHS Trust, Imperial College London, Cancer Research UK, University College London, St Thomas' Hospital, King's College London, Royal Marsden NHS Foundation Trust, Royal Marsden Hospital, Guy's and St Thomas' NHS Foundation Trust, Beth Israel Deaconess Medical Center, Harvard University, Lancashire Teaching Hospitals NHS Foundation Trust, University of Birmingham, Queen Mary University of London, Barts Health NHS Trust, London School of Hygiene & Tropical Medicine, St Bartholomew's Hospital
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,490
Awards: G7790000102, G8885116652
OpenAlex ID: W4415777441