多b值扩散加权成像在原发性和转移性肝癌鉴别诊断中的价值

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Abstract Objective: To investigate the value of multi b-value DWI double exponential function model in differential diagnosis between primary and metastatic hepatocellular carcinoma. Methods: Forty-one cases of primary hepatocellular carcinoma (23 cases) and metastatic hepatocellular carcinoma (18 cases) confirmed by surgical pathology or puncture were scanned by multi b-value DWI of MRI, being 0, 100, 400, 800, 400 s/mm2. The quantitative values of single exponential function (Slow ADC-Mono, Fast ADC-Mono) and double exponential function (Slow ADC-bi, Fast ADC-bi) were measured and related data were analyzed. Results: Except Fast ADC-Mono, the quantitative values of Slow ADC-Mono, Slow ADC-bi, and Fast ADC-bi were statistically different among primary hepatocellular carcinoma, metastatic hepatocellular carcinoma and normal tissue by single factor analysis of variance. Comparing the LSD results of primary hepatocellular carcinoma and metastatic hepatocellular carcinoma, the quantitative values of both Slow ADC-Mono and Fast ADC-Mono showed no statistical difference between the two groups, while the values of Slow ADC-bi and Fast ADC-bi were statistically different. The quantitative values of Slow ADC-bi were highest in normal tissues, followed by primary liver cancer and lowest in metastatic liver cancer, while the Fast ADC-bi values were highest in primary liver cancer, followed by metastatic liver cancer and highest in normal tissues. In the same disease or normal tissues, whether they were in single exponential function model or double exponential function model, the quantitative values of Fast ADC were far greater than those of Slow ADC. Conclusion: The Slow ADC and Fast ADC parameters of the double exponential function model reflect the cytological characteristics of the malignant tumor to a certain extent. The double exponential function model of multi-b value DWI is of significance in differential diagnosis between primary hepatocellular carcinoma and metastatic hepatocellular carcinoma.

Key words： liver neoplasms magnetic resonance imaging diffusion weighted imaging exponential model

Received: 12 September 2017

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	Articles by authors
	ZHANG Zhijing
	WU Aiqin
	ZHANG Xiaoyu
	FU Yao
	DUAN Weimin
	ZHENG Wenlong.

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https://xb.wmu.edu.cn/EN/ OR https://xb.wmu.edu.cn/EN/Y2018/V48/I5/361

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