Gadoxetate acid-enhanced MRI of hepatocellular carcinoma in a c-myc/TGFα transgenic mouse model including signal intensity and fat content: Initial experience

Department of Nuclear Medicine, Johann Wolfgang Goethe University Hospital, Frankfurt, Germany.
Cancer Imaging (Impact Factor: 2.07). 03/2012; 12(1):72-8. DOI: 10.1102/1470-7330.2012.0009
Source: PubMed


Genetically engineered mouse models, such as double transgenic c-myc/TGFα mice, with specific pathway abnormalities might be more successful at predicting the clinical response of hepatocellular carcinoma (HCC) treatment. But a major drawback of the tumour models is the difficulty of visualizing endogenously formed tumours. The optimal imaging procedure should be brief and minimally invasive. Magnetic resonance imaging (MRI) satisfies these criteria and gadoxetate acid-enhanced MRI improves the detection of HCC. Fat content is stated to be an additional tool to help assess tumour responses, for example, in cases of radiofrequency ablation. Therefore the aim of this study was to investigate if gadoxetate acid-enhanced MRI could be used to detect HCC in c-myc/TGFα transgenic mice by determining the relation between the signal intensity of HCC and normal liver parenchyma and the corresponding fat content as a diagnostic marker of HCC. In our study, 20 HCC in c-myc/TGFα transgenic male mice aged 20-34 weeks were analyzed. On gadoxetate acid-enhanced MRI, the signal intensity was 752.4 for liver parenchyma and 924.5 for HCC. The contrast to noise ratio was 20.4, the percentage enhancement was 267.1% for normal liver parenchyma and 353.9% for HCC. The fat content was 11.2% for liver parenchyma and 16.2% for HCC. There was a correlation between fat content and signal intensity with r = 0.7791. All parameters were statistically significant with P < 0.05. Our data indicate that gadoxetate acid contrast enhancement allows sensitive detection of HCC in c-myc/TGFα transgenic mice and determination of the fat content seems to be an additional useful parameter for HCC.

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Available from: Thomas Vogl, Nov 28, 2014