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  • Title: FDG PET/CT diagnostic criteria may need adjustment based on MRI to estimate the presurgical risk of extrapelvic infiltration in patients with uterine endometrial cancer.
    Author: Sudo S, Hattori N, Manabe O, Kato F, Mimura R, Magota K, Sugimori H, Hirata K, Sakuragi N, Tamaki N.
    Journal: Eur J Nucl Med Mol Imaging; 2015 Apr; 42(5):676-84. PubMed ID: 25504022.
    Abstract:
    PURPOSE: The staging of endometrial cancer requires surgery which carries the risk of morbidity. FDG PET/CT combined with anatomical imaging may reduce the number of unnecessary lymphadenectomies by demonstrating the risk of extrapelvic infiltration. The purpose of this study was to optimize FDG PET/CT diagnostic criteria for risk assessment in endometrial cancer after first-line risk triage with MRI. METHODS: The study population comprised 37 patients who underwent curative surgery for the treatment of endometrial cancer. First, the risk of extrapelvic infiltration was triaged using MRI. Second, multiple glucose metabolic profiles of the primary lesion were assessed with FDG PET/CT, and these were correlated with the histopathological risk of extrapelvic infiltration including lymphovascular space invasion (LVSI) and high-grade malignancy (grades 2 and 3). The results of histological correlation were used to adjust FDG PET/CT diagnostic criteria. RESULTS: Presurgical assessment using MRI was positive for deep (>50 %) myometrial invasion in 17 patients. The optimal FDG PET/CT diagnostic criteria vary depending on the results of MRI. Specifically, SUVmax (≥16.0) was used to indicate LVSI risk with an overall diagnostic accuracy of 88.2 % in patients with MRI findings showing myometrial invasion. High-grade malignancy did not correlate with any of metabolic profiles in this patient group. In the remaining patients without myometrial invasion, lesion glycolysis (LG) or metabolic volume were better indicators of LVSI than SUVmax with the same diagnostic accuracy of 80.0 %. In addition, LG (≥26.9) predicted high-grade malignancy with an accuracy of 72.2 %. Using the optimized cut-off criteria for LVSI, glucose metabolic profiling of primary lesions correctly predicted lymph node metastasis with an accuracy of 73.0 %, which was comparable with the accuracy of visual assessment for lymph node metastasis using MRI and FDG PET/CT. CONCLUSION: FDG PET/CT diagnostic criteria may need adjustment based on the anatomical information provided by MRI. The optimized criteria can predict the risk of pathology-proven LVSI correctly in 83.8 % of patients before surgery, and thus would improve presurgical treatment planning.
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