Clinical value of 18F-FDG uptake, described by metabolic tumor volume, total lesion glycolysis and#br#
standard uptake values in breast cancer
1.Department of Nuclear Medicine, Shengjing Hospital of China Medical University, Shenyang 110004, China;
2.GE Medical Systems Trade Development(Shanghai) Co., LTD, Shenyang 110003, China
Abstract：Objective: The aim of this study was to observe the value of different metabolic parameters(MTV, TLG, SUVmax, SUVmean and SUVpeak) in breast cancer. Materials and Methods: Forty-eight patients of breast cancer underwent PET/CT imaging before operation consecutively from December 2011 to August 2015, maximum, peak and mean standardized uptake values(SUVmax, SUVpeak and SUVmean), metabolic tumor volume(MTV) and total lesion glycolysis(TLG) in the primary tumor were calculated and compared with sizes, metastatic situation, immunohistochemical characterization and oestrogen receptor(ER), progesterone receptor(PR), HER-2 status, being analyzed with T-text, ANOVA, spearman analysis. Results: Most of metabolic parameters were higher in high T-grade lesions, significant correlation was found between all metabolic parameters in T2~T4 and T0~T1, all the parameters were higher in M1/N1~N3 than lesions compared with M0/N0, significant correlation was found only for TLG and MTV(P＜0.05). TLG and MTV were higher in the cancers with Ki67≥14％, however there was no correlation between the Ki67 or p53 expression and all the parameters. No significant correlation was found between all metabolic parameters and ER, PR or HER-2 status. Conclusion: Metabolic tumor volume, total lesion glycolysis and SUV combined detection can be used as an evaluation index for judging the malignant degree and invasiveness, MTV and TLG are the better index.
张 倩1，辛 军1，李 红2. 18F-FDG PET/CT显像半定量参数MTV、TLG联合#br#
SUV在乳腺癌诊断中的应用价值[J]. 中国临床医学影像杂志, 2016, 27(9): 620-624.
ZHANG Qian1, XIN Jun1, LI Hong2. Clinical value of 18F-FDG uptake, described by metabolic tumor volume, total lesion glycolysis and#br#
standard uptake values in breast cancer. JOURNAL OF CHINA MEDICAL IMAGING, 2016, 27(9): 620-624.
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2016, Vol. 27 
