Building an animal liver fibrosis bioimaging database for the MR imaging severity index establishment: progress report
Yeon Ji Chae1, Chul-Woong Woo2, Sang-Tae Kim2, Young-Jin Kim2, Ji-Yeon Suh2, Ji-heon Kang2, Kyung-Won Kim3, Yoonseok Choi4, and Dong-Cheol Woo1,2

1Department of Convergence Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea, Republic of, 2Convergence Medicine Research Center, Asan Institute for Life Sciences, Asan Medical Center, Seoul, Korea, Republic of, 3Department of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea, Republic of, 4Medical Research Institute, Gangneung Asan Hospital, Gangneung-si, Korea, Republic of


The purpose of this study is to establish the imaging severity index of thioacetamide (TAA)-induced animal liver fibrosis model by magnetic resonance imaging (MRI) techniques.


Despite the development of novel treatment options for chronic liver diseases, mortality rates of liver disease patients are still high in Korea. A lot of research efforts are invested in developing better regimes to cure those diseases; however, failures of new drug development still occur during each step.1 The evaluation system for drug efficacy with the imaging modality is not well established in preclinical research areas. Although many biomarkers have been emerged as the indicator for subject assignments, it is still difficult to distinguish the disease severity of the subjects that would assign into the control and experimental groups.2 Therefore, we aim to develop the bioimaging database and assess the feasibility for preclinical liver fibrosis severity index establishment with MRI.


Six-week-old male Sprague-Dawley (SD) rats were used and randomly divided into two groups as follows: Control (n = 7) and thioacetamide (TAA; n = 6) groups. To induce liver fibrosis, TAA was intraperitoneally injected with 200 mg/kg three times weekly for eight weeks (Fig.1). MR imaging was assessed every two weeks using a 9.4-T magnet. The MR images were obtained as follow: (1) T1-weighted dynamic contrast-enhanced (DCE)-MRI with TR/TE = 70/2.47 ms, FOV = 60 × 35 mm2, 400 images, total scan time = about 46 min. 25 μmol/kg Gadoxetic acid (Gd-EOB-DTPA; Primovist®) was intravenously injected after 120 sec. (2) T2* map with TR/TE = 800/2.56 ms, FOV = 60 × 35 mm2. The relative enhancement rate (RER) was calculated using the RER(t) = [SI(t)-SI(0)/SI(0)]×100(%) equation.3 The area under the curve to maximum time (AUCtmax) was calculated by the integration of areas from 0 to 6 min 72 sec (SI(t); SI of the liver after Gd-EOB-DTPA injection, SI(0); average of pre-contrast SI). The blood samples were collected from the tail vein every two weeks. Aspartate aminotransferase (AST), alanine aminotransferase (ALT), total bilirubin (TBIL) and albumin (ALB) were measured with Hitachi 7180 Autoanalyzer. The 4% paraformaldehyde-fixed, and paraffin-embedded liver tissue samples were sectioned at 4 µm and stained with hematoxylin and eosin (H&E) and Masson's trichrome (MT). Images were obtained under a Zeiss-Axioscope‚Ö° microscope. The lobular inflammation was scored as follow: no foci (score-0), <2 foci / 200× (score-1), 2-4 foci / 200× (score-2), >4 foci / 200× (score-3). The hepatocyte ballooning was scored as follow: none (score-0), few ballooned cells (score-1), many ballooned cells (score-2). The fibrosis stage by Brunt4 was graded as follow: none (stage-0), portal fibrosis (stage-1), portal fibrosis with few septa (stage-2), septal or bridging fibrosis (stage-3), cirrhosis (stage-4). Statistical analysis was performed using SPSS 18.0. One-way ANOVA, and independent t-tests were performed to compare the mean between different values and p < 0.05 was considered significant.


The TAA-induced group showed significantly decreased body weights at four weeks (Fig.2A). The AST, ALT, and TBIL were significantly increased in the TAA-induced group at 8-weeks (Fig.2B). In the histological analyses, inflammatory cells and scarring were observed near the portal triad following TAA injection (Fig.3). TAA-induced group showed increased lobular inflammation (0 vs. 2), hepatocyte ballooning (0 vs. 2), and fibrosis stage (0 vs. 3.3) (Table 1). With the analyses of the serum levels and histology, we confirmed that TAA injection generated the animal models that bear the liver fibrosis. We next evaluated the degree of hepatic fibrosis with MRI. T1-weighted DCE and T2*map images was acquired (Fig.4A and C). In comparison analyses of RER, TAA-induced group showed decrease of RER compared to the control from the second weeks (Fig.4B). The AUCtmax and T2* map showed significantly decreased in the TAA-induced group, especially at 6th and 8th weeks compared to the control (Fig.4D). All the MRI data also implied that liver fibrosis was progressed under the TAA injection. After all, Pearson correlation were calculated between MR data and several hepatic enzymes. T2* map with AST or with ALT have shown significant negative correlations. Between AST and ALT, AUCtmax and T2* map showed significant positive correlations (Table 2). Our data demonstrated that correlations between blood tests and MR images were existed as the fibrosis progressed.


The current report is the part of the ongoing project for the preclinical liver fibrosis imaging severity index establishment. Due to the small numbers of subjects, we haven’t generated the severity index standard in this report. However, as MRI data with serum and histological data showed correlative relations, we had preliminary severity index guideline (data not shown) with our current database. Because our study will be carried out until the sufficient analyzed data are gathered, we expect that the imaging-based severity index will be established soon.


This study was supported by grants of Basic Science Research Program through the National Research Foundation of Korea funded by the Ministry of Education [2018R1A2B2007694]


1. Cook, D., et al., Lessons learned from the fate of AstraZeneca's drug pipeline: a five-dimensional framework. Nat Rev Drug Discov, 2014. 13(6): p. 419-31.

2. Nallagangula, K.S., et al., Liver fibrosis: a compilation on the biomarkers status and their significance during disease progression. Future Sci OA, 2018. 4(1): p. FSO250.

3. Yamada, T., et al., Gd-EOB-DTPA-enhanced-MR imaging in the inflammation stage of nonalcoholic steatohepatitis (NASH) in mice. Magn Reson Imaging, 2016. 34(6): p. 724-729.

4. Brunt, E.M., Grading and staging the histopathological lesions of chronic hepatitis: the Knodell histology activity index and beyond. Hepatology, 2000. 31(1): p. 241-6.


Figure 1. The scheme of TAA-induced hepatic fibrosis animal model.

Figure 2. Comparison of body weight and several hepatic enzymes expression between control and TAA induced group.

(A) The bodyweight changes (*p < 0.05, **p < 0.01).

(B) Expression of several hepatic enzymes (AST, ALT, TBIL, and ALB) in the serum (*p < 0.05, **p < 0.01, ***p < 0.001).

Figure 3. Histological analysis in TAA-induced hepatic fibrosis animal model.

To evaluated inflammation and fibrosis area, H&E and MT staining was performed.

Figure 4. MR images evaluation of liver following TAA injection.

(A) Axial MR images of the liver with ROI (red box) in control and TAA-induced groups at day 0, 14, 28, 42 and 56.

(B) Relative enhancement rate (RER) were analyzed.

(C) T2* map images of the liver.

(D) Area under the curve to maximum time (AUCtmax) and T2* map was analyzed.

Table 1. Histologic quantification of liver injury in TAA-induced hepatic fibrosis animal model.

Lobular inflammation, hepatocyte ballooning and fibrosis grade were analyzed.

Table 2. Pearson correlation coefficient (r) and p-value (p) between the control group and TAA group following a period.

The MRI results correlated with the expression of several hepatic enzymes results.

Proc. Intl. Soc. Mag. Reson. Med. 27 (2019)