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Correlation of Minimum Apparent Diffusion Coefficient and Maximum Standardized Uptake Value of the Primary Tumor with Clinicopathologic Characteristics in Endometrial Cancer

OBJECTIVE: To explore the correlation of the primary tumor’s maximum standardized uptake value (SUV(max)) and minimum apparent diffusion coefficient (ADC(min)) with clinicopathologic features, and to determine their predictive power in endometrial cancer (EC). METHODS: A total of 45 patients who had...

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Detalles Bibliográficos
Autores principales: Sürer Budak, Evrim, Toptaş, Tayfun, Aydın, Funda, Öner, Ali Ozan, Çevikol, Can, Şimşek, Tayup
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Galenos Publishing 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5350502/
https://www.ncbi.nlm.nih.gov/pubmed/28291007
http://dx.doi.org/10.4274/mirt.30306
Descripción
Sumario:OBJECTIVE: To explore the correlation of the primary tumor’s maximum standardized uptake value (SUV(max)) and minimum apparent diffusion coefficient (ADC(min)) with clinicopathologic features, and to determine their predictive power in endometrial cancer (EC). METHODS: A total of 45 patients who had undergone staging surgery after a preoperative evaluation with (18)F-fluorodeoxyglucose (FDG) positron emission tomography/computerized tomography (PET/CT) and diffusion-weighted magnetic resonance imaging (DW-MRI) were included in a prospective case-series study with planned data collection. Multiple linear regression analysis was used to determine the correlations between the study variables. RESULTS: The mean ADC(min) and SUV(max) values were determined as 0.72±0.22 and 16.54±8.73, respectively. A univariate analysis identified age, myometrial invasion (MI) and lymphovascular space involvement (LVSI) as the potential factors associated with ADC(min) while it identified age, stage, tumor size, MI, LVSI and number of metastatic lymph nodes as the potential variables correlated to SUV(max). In multivariate analysis, on the other hand, MI was the only significant variable that correlated with ADC(min) (p=0.007) and SUV(max) (p=0.024). Deep MI was best predicted by an ADC(min) cutoff value of ≤0.77 [93.7% sensitivity, 48.2% specificity, and 93.0% negative predictive value (NPV)] and SUV(max) cutoff value of >20.5 (62.5% sensitivity, 86.2% specificity, and 81.0% NPV); however, the two diagnostic tests were not significantly different (p=0.266). CONCLUSION: Among clinicopathologic features, only MI was independently correlated with SUV(max) and ADC(min). However, the routine use of (18)F-FDG PET/CT or DW-MRI cannot be recommended at the moment due to less than ideal predictive performances of both parameters.