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FDG-PET/MRI with high-resolution DWI characterises the distinct phenotypes of endometrial cancer
H Tsuyoshi1, T Tsujikawa2, S Yamada1
1Department of Obstetrics and Gynecology, Faculty of Medical Sciences, University of Fukui, Fukui, Japan.
Aim:
To evaluate the capability of integrated 2-[18F]-fluoro-2-deoxy-d-glucose (FDG)-positron-emission tomography (PET)/magnetic resonance imaging (MRI) to characterise the distinct phenotypes of endometrial cancer.
Materials And Methods:
Thirty-one patients with endometrial cancer (23 with type I, including 17 G1 and six G2 endometrioid adenocarcinomas, and eight with type II, including three G3 endometrioid adenocarcinomas, two carcinosarcomas, and three serous carcinomas) underwent pretreatment FDG-PET/MRI with simultaneous reduced field-of-view diffusion-weighted imaging (DWI). The standardised uptake value (SUV), apparent diffusion coefficient (ADC), and SUV-to-ADC ratio were compared between low-risk (type I and stage I and negative for lymph-vascular space invasion [LVSI]) and high-risk cancers. The diagnostic accuracy for discriminating the cancer phenotypes was evaluated using receiver operating characteristic (ROC) analysis.
Results:
The SUV was not significantly different between low-risk and high-risk endometrial cancers. High-risk cancers had a significantly lower ADC (756±232×10-6) and a greater SUV-to-ADC ratio (21.7±7.7×109) than low-risk cancers (937±154×10-6, p<0.05 and 13.1±4.1×109, p<0.005, respectively). On comparison of the area under the ROC curves (AUCs), the SUV-to-ADC ratio demonstrated the greatest diagnostic accuracy (ratio 0.83, ADC 0.72, and SUV 0.66). The AUCs for the ratios were significantly higher than those for the SUV values (p<0.05). The optimal SUV-to-ADC cut-off value of 16.9×109 for predicting high-risk cancer revealed a sensitivity of 73%, specificity of 81%, and accuracy of 77%, which was significantly higher than the accuracy for SUV.
Conclusion:
The SUV-to-ADC ratio obtained using integrated FDG-PET/MRI with high-resolution DWI reflects tumour aggressiveness including LVSI, and will be useful for lesion characterisation to decide on an appropriate therapeutic strategy for endometrial cancer.
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