摘要
AIM:To determine whether and how magnetic resonance imaging(MRI)-based total liver volume(TLV) and diffusion weighted imaging(DWI) could predict liver fibrosis.METHODS:Sixteen experimental mature mini-pigs(6 males,10 females),weighing between 20.0 and 24.0 kg were prospectively used to model liver fibrosis induced by intraperitoneal injection of 40% CCl4 dissolved in fat emulsion twice a week for 16 wk,and by feeding 40% CCl4 mixed with maize flour twice daily for the subsequent 5 wk.All the survival animals underwent percutaneous liver biopsy and DWI using b = 300,500 and 800 s/mm2 followed by abdominal gadolinium-enhanced MRI at the 0,5th,9th,16th and 21st weekend after beginning of the modeling.TLV was obtained on enhanced MRI,and apparent diffusion coefficient(ADC) was obtained on DWI.Hepatic tissue specimens were stained with hematoxylin and Masson' s trichrome staining for staging liver fibrosis.Pathological specimens were scored using the human METAVIR classification system.Statistical analyses were performed to determine whether and how the TLV and ADC could be used to predict the stage of liver fibrosis.RESULTS:TLV increased from stage 0 to 2 and decreased from stage 3(r = 0.211;P < 0.001).There was a difference in TLV between stage 0-1 and 2-4(P = 0.03) whereas no difference between stage 0-2 and 3-4(P = 0.71).TLV could predict stage ≥ 2 [area under receiver operating characteristic curve(AUC) = 0.682].There was a decrease in ADC values with increasing stage of fibrosis for b = 300,500 and 800 s/mm2(r =-0.418,-0.535 and-0.622,respectively;all P < 0.001).Differences were found between stage 0-1 and 2-4 in ADC values for b = 300,500 and 800 s/mm2,and between stage 0-2 and 3-4 for b = 500 or 800 s/mm2(all P < 0.05).For predicting stage ≥ 2 and ≥ 3,AUC was 0.803 and 0.847 for b = 500 s/mm2,and 0.848 and 0.887 for b = 800 s/mm2,respectively.CONCLUSION:ADC for b = 500 or 800 s/mm2 could be better than TLV and ADC for b = 300 s/mm2 to pre-dict fibrosis stage ≥ 2 or ≥ 3.
AIM：To determine whether and how magnetic resonance imaging（MRI）-based total liver volume（TLV） and diffusion weighted imaging（DWI） could predict liver fibrosis.METHODS：Sixteen experimental mature mini-pigs（6 males,10 females）,weighing between 20.0 and 24.0 kg were prospectively used to model liver fibrosis induced by intraperitoneal injection of 40% CCl4 dissolved in fat emulsion twice a week for 16 wk,and by feeding 40% CCl4 mixed with maize flour twice daily for the subsequent 5 wk.All the survival animals underwent percutaneous liver biopsy and DWI using b = 300,500 and 800 s/mm2 followed by abdominal gadolinium-enhanced MRI at the 0,5th,9th,16th and 21st weekend after beginning of the modeling.TLV was obtained on enhanced MRI,and apparent diffusion coefficient（ADC） was obtained on DWI.Hepatic tissue specimens were stained with hematoxylin and Masson＇ s trichrome staining for staging liver fibrosis.Pathological specimens were scored using the human METAVIR classification system.Statistical analyses were performed to determine whether and how the TLV and ADC could be used to predict the stage of liver fibrosis.RESULTS：TLV increased from stage 0 to 2 and decreased from stage 3（r = 0.211;P 〈 0.001）.There was a difference in TLV between stage 0-1 and 2-4（P = 0.03） whereas no difference between stage 0-2 and 3-4（P = 0.71）.TLV could predict stage ≥ 2 [area under receiver operating characteristic curve（AUC） = 0.682].There was a decrease in ADC values with increasing stage of fibrosis for b = 300,500 and 800 s/mm2（r =-0.418,-0.535 and-0.622,respectively;all P 〈 0.001）.Differences were found between stage 0-1 and 2-4 in ADC values for b = 300,500 and 800 s/mm2,and between stage 0-2 and 3-4 for b = 500 or 800 s/mm2（all P 〈 0.05）.For predicting stage ≥ 2 and ≥ 3,AUC was 0.803 and 0.847 for b = 500 s/mm2,and 0.848 and 0.887 for b = 800 s/mm2,respectively.CONCLUSION：ADC for b = 500 or 800 s/mm2 could be better than TLV and ADC for b = 300 s/mm2 to pre-dict f
基金
Supported by National Natural Science Foundation of China,No. 81050033
Key Projects in the Sichuan Province Science and Technology Pillar Program,No. 2011SZ0237
the Science Fund for Distinguished Young Scholars of Sichuan Province,China,No. 2010JQ0039
