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Metabolic Parameters of PET/CT Combined with MR-DWI in Diagnosis of Regional Lymph Node Involvement in Rectal Cancer
Author(s): 
Pages: 489-495
Year: Issue:  6
Journal: Journal of Oncology

Keyword:  rectal cancerLN involvement;
Abstract: [Objective] To evaluate the metabolic parameters of preoperative PET/CT and MRI-DWI in predicting the regional lymph nodes(rLN)involvement in rectal cancer.[Methods] Thirty-four rectal cancer patients without previous antineoplastic treatment were enrolled in the study.All patients received rectal 3.0T high resolution MRI and then whole body PET/CT,the surgery was performed a week after completion of the examinations.The PET/CT metabolic parameters and DWI parameters of primary rectal tumors were measured on the workstation,including the average standard uptake value(SUVmean),the maximum standard uptake value(SUVmax),metabolic tumor volume(MTV) and total lesion glycolysis(TLG) and apparent diffusion coeffecient (ADC)value.According to pathologic findings patients were divided into rLN negative group and rLN positive group.The differences of metabolic parameters and ADC values between the two groups were analyzed and the effect of various parameters on the prediction of rLN involvement was analyzed by using ROC curve.[Results] The rLN (+) group showed significantly higher values of MTVs and TLGs,and lower values of ADCmean than rLN(-) group.ROC curve analysis showed that optimal cut-off to diagnosis rLN involvement of MTV2.5,MTV3.0,MTV3.5,TLG2.5,TLG 3.0,TLG 3.5 and ADCmean were 33.69,23.12,20.95,187.97,166.31,73.77 and 166.31,respectively.KruskalWallis test showed that there were no differences in the diagnostic value of various parameters for rLN involvement.Multivariate analysis showed that TLG2.5 was an independent correlative factor to predict rLN involvement in rectal cancer.[Conclusion] PET/CT metabolic parameters and MR-DWI ADC are of guiding value in differentiating benign or malignant of rLN in rectal cancer preoperatively,and high TLG2.5 value is an independent risk factor to predict rLN involvement in rectal cancer.
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