Preliminary study of MR diffusion tensor imaging of the liver for the diagnosis of hepatocellular carcinoma

Citations of this article
Mendeley users who have this article in their library.


Objectives: To evaluate the feasibility of differentiating between hepatocellular carcinomas (HCC) and healthy liver using diffusion tensor imaging (DTI). Material and Methods: All subjects underwent an abdominal examination on a 3.0T MRI scanner. Two radiologists independently scored the image quality (IQ). An optimal set of DTI parameters was obtained from a group of fifteen volunteers with multiple b-values (100, 300, 500, and 800 s/mm2) and various diffusion-encoding directions (NED = 6, 9, and 12)using two way ANOVA analysis. Eighteen Patients with HCC underwent DTI scans with the optimized parameters. Fractional anisotropy(FA) and average apparent diffusion coefficient (ADC) values were measured. The differences of FA and ADC values between liver healthy region and HCC lesion were compared through paired t tests. Results: There were no significant changes in liver IQ and FA/ADC values with increased NED (P>0.05), whereas the liver IQ and FA/ADC values decreased significantly with increased b-values(P <0.05). Good IQ, acceptable scan time and reasonable FA/ADC values were acquired using NED = 9 with b-value of (0,300) s/mm2. Using the optimized DTI sequence, ADC value of the tumor lesion was significantly lower than that of the healthy liver region (1.30 ± 0.34×10-3 vs 1.52 ± 0.27×10-3 mm2/s, P = 0.013), whereas the mean FA value of the tumor lesion (0.42 ± 0.11) was significantly higher than the normal liver region (0.32 ± 0.10) (P = 0.004). Conclusion: Either FA or ADC value from DTI can be used to differentiate HCC from healthy liver. HCC lead to higher FA value and lower ADC value on DTI than healthy liver. Copyright:




Li, X., Liang, Q., Zhuang, L., Zhang, X., Chen, T., Li, L., … Hu, J. (2015). Preliminary study of MR diffusion tensor imaging of the liver for the diagnosis of hepatocellular carcinoma. PLoS ONE, 10(8).

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free