IVIM improves preoperative assessment of microvascular invasion in HCC

  • Yi Wei
  • Zixing Huang
  • Hehan Tang
  • Liping Deng
  • Yuan Yuan
  • Jiaxing Li
  • Dongbo Wu
  • Xiaocheng Wei
  • Bin SongEmail author



To prospectively evaluate the potential role of intravoxel incoherent motion (IVIM) and conventional radiologic features for preoperative prediction of microvascular invasion (MVI) in patients with hepatocellular carcinoma (HCC).


Institutional review board approval and written informed consent were obtained for this study. A cohort comprising 115 patients with 135 newly diagnosed HCCs between January 2016 and April 2017 were evaluated. Two radiologists independently reviewed the radiologic features and the apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudodiffusion coefficient (D*), and pseudodiffusion component fraction (f) were also measured. Interobserver agreement was checked and univariate and multivariate logistic regressions were used for screening the risk factors. Receiver operating characteristics (ROC) curve analyses were performed to evaluate the diagnostic performance.


Features significantly related to MVI of HCC at univariate analysis were reduced ADC (odds ratio, 0.341; 95% CI, 0.211–0.552; p < 0.001), D (odds ratio, 0.141; 95% CI, 0.067–0.299; p < 0.001), and irregular circumferential enhancement (odds ratio, 9.908; 95% CI, 3.776–25.996; p < 0.001). At multivariate analysis, only D value (odds ratio, 0.096; 95% CI, 0.025–0.364; p < 0.001) was the independent risk factor for MVI of HCC. The mean D value for MVI of HCC showed an area under ROC curves of 0.815 (95% CI, 0.740–0.877).


IVIM model–derived D value is superior to ADC measured with mono-exponential model for evaluating the MVI of HCC. Among MR imaging features, tumor margin, enhancement pattern, tumor capsule, and peritumoral enhancement were not predictive for MVI.

Key Points

• Diffusion MRI is useful for non-invasively evaluating the microvascular invasion of hepatocellular carcinoma.

• IVIM model is advantageous over mono-exponential model for assessing the microvascular invasion of hepatocellular carcinoma.

• Decreased D value was the independent risk factor for predicting MVI of HCC.


Magnetic resonance imaging Hepatocellular carcinoma Diagnostic imaging 





Apparent diffusion coefficient


Area under curve


Confidence interval


Computed tomography


True diffusion coefficient


Pseudodiffusion coefficient


Diffusion-weighted imaging


Pseudodiffusion component fraction


Hepatocellular carcinoma


Intra-class correlation coefficient


Intravoxel incoherent motion


Liver acceleration volume acquisition


Magnetic resonance imaging


Microvascular invasion


Odds ratio


Positron emission tomography


Receiver operating characteristics


Region of interest


Whole tumor volume



This study was funded by Research Grant of National Nature Science Foundation of China and Science (Grant number 81471658) and Technology Support Program of Sichuan Province (Grant number 2017SZ0003) and Science and Technology Support Program of Sichuan Province (Grant number 2017SZ0185).

Compliance with ethical standards


The scientific guarantor of this publication is Bin Song.

Conflict of interest

The authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.

Statistics and biometry

One of the authors (Yi Wei) has significant statistical expertise.

Informed consent

Written informed consent was obtained from all subjects (patients) in this study.

Ethical approval

Institutional Review Board approval was obtained.


• prospective

• diagnostic study

• performed at one institution


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Copyright information

© European Society of Radiology 2019

Authors and Affiliations

  1. 1.Department of Radiology, West China HospitalSichuan UniversityChengduChina
  2. 2.Department of Liver Surgery, West China HospitalSichuan UniversityChengduChina
  3. 3.Center of Infectious Diseases, West China HospitalSichuan UniversityChengduChina
  4. 4.GE Healthcare ChinaBeijingChina

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