Multivariable Analysis of Clinical Influence Factors on Liver Enhancement of Gd-EOB-DTPA-Enhanced 3T MRI

Key words

abdomen - MR imaging - contrast agents

Introduction

MRI imaging of the liver plays a decisive role in the clinical routine. It has become established in recent years as a good, noninvasive method for the detection and characterization of focal and diffuse liver lesions. The use of liver-specific contrast agents allows general tissue perfusion evaluation in the vascular phases and provides specific information about hepatocytes.

Gadolinium ethoxybenzyl diethylenetriamine pentaacetic acid (Gd-EOB-DTPA) is a widely used contrast agent with selective liver-specific uptake [1] [2]. After the vascular phases, there is liver-specific accumulation with an increase in signal intensity in T1-weighted sequences. The specific accumulation within the liver can be observed after 10 minutes up to at least 2 hours with a wash-in period of 20 minutes being used in the clinical routine [3] [4]. As a result of this additional hepatobiliary phase (HBP), liver-specific contrast agents are particularly helpful in the detection and characterization of liver lesions [5] [6] [7].

From the clinical routine it is generally known that there are cases in which there is only minimal contrast enhancement in the HBP after 20 minutes. Studies have shown that the accumulation of Gd-EOB-DTPA in the liver parenchyma in the case of liver fibrosis and cirrhosis is slowed or reduced [8] [9] [10] [11] [12] [13] and consequently adequate diagnosis of liver lesions could be limited.

To our knowledge, there are no studies regarding the inadequate uptake of Gd-EOB-DTPA in a patient collective without liver parenchyma damage. The goal of this study was to analyze clinical factors that could influence the uptake of Gd-EOB-DTPA.

Materials and Methods

Patient collective

In the period from May 2012 to February 2014, 553 weight-adapted Gd-EOB-DTPA-enhanced MRI examinations were performed. 286 patients were excluded from this study due to diffuse liver parenchyma damage or primary liver lesions. In addition, patients with treatment damaging the liver parenchyma (n = 115), motion artifacts, or incomplete examination (n = 28) were excluded from this study. In total, 124 patients were included in this retrospective study. These patients underwent Gd-EOB-DTPA-enhanced MRI examination for secondary liver lesion clarification. The study was approved by the local ethics committee of the medical faculty of the university. [Table 1] shows the patient characteristics for this study.

Table 1 Patient characteristics in the individual subgroups. Data are shown as average ± standard deviation.

	all patients (n = 124)	HRE (n = 52)	MRE (n = 63)	LRE (n = 9)
age (years)	59.9 ± 14.6	57.3 ± 14.7	61.2 ± 15.1	66.4 ± 7.8
gender, n (%)
male	67 (54)	27 (52)	34 (54)	6 (67)
female	57 (46)	25 (48)	29 (46)	3 (33)
weight (kg)	74.7 ± 14.2	77.1 ± 15.2	72.4 ± 13.1	77.0 ± 14.7
height (m)	1.7 ± 0.1	1.7 ± 0.1	1.7 ± 0.1	1.7 ± 0.1
liver volume (ml)	1890.9 ± 475.4	1789.3 ± 358.6	1861.4 ± 363.6	2683.9 ± 921.8
spleen volume (ml)	386.1 ± 222.8	321.5 ± 137.0	410.9 ± 248.3	585.2 ± 299.1
Δ liver volume (ml)	316.1 ± 441.9	170.49 ± 324.01	329.0 ± 328.7	1066.8 ± 849.7
aspartate aminotransferase (AST) (U/l)	22.5 ± 8.6	21.2 ± 7.9	22.5 ± 8.6	28.9 ± 10.4
alanine aminotransferase (ALT) (U/l)	27.2 ± 9.9	29.4 ± 10.0	25.9 ± 9.7	23.0 ± 8.6
gamma glutamyl transferase (GGT) (U/l)	101.9 ± 111.5	79.4 ± 59.5	91.8 ± 70.8	322.9 ± 292.5
bilirubin (total) (mg/dl)	0.6 ± 0.3	0.5 ± 0.2	0.6 ± 0.3	0.9 ± 0.3
thrombocytes (/nl)	221.8 ± 115.0	229.0 ± 78.5	208.6 ± 92.7	271.6 ± 304.7
estimated glomerular filtration rate (eGFR) (ml/min/1.73m2)	98.0 ± 24.1	96.0 ± 23.2	99.1 ± 25.5	101.2 ± 20.4

HRE: high relative enhancement; MRE: medium relative enhancement; LRE: low relative enhancement

MRI

All examinations were performed on a clinical 3 T system (Magnetom Skyra, Siemens Healthcare). A combination of body and spine coil elements (18-channel body matrix coil, 24-channel spine matrix coil) was used for signal detection. A T1-weighted VIBE (volume interpolated breath hold examination) sequence with fat suppression was performed during a breath-hold:

Repetition time (TR): 3.09 ms; echo time (TE): 1.16 ms; flip angle: 9°; parallel imaging factor: 2; slices: 64; reconstructed voxel size: 1.3 mm × 1.3 mm × 3.0 mm; measured voxel size: 1.7 mm × 1.3 mm × 4.5 mm; acquisition time: 14 sec.

The entire liver was visualized with this sequence before (unenhanced) and in the hepatobiliary phase (HBP) (20 min.).

Gd-EOB-DTPA (Primovist; Bayer Schering Pharma AG, Berlin, Germany) was used as the liver-specific contrast agent. All patients received a body weight-adapted dose (0.1 ml/kg body weight) that was administered as a bolus with a flow rate of 1 mL/s with subsequent flushing with 20 ml of NaCL.

Sequence analysis

To calculate the average signal intensity (SI), three circular regions of interest (ROIs) were manually positioned by an examiner in each liver lobe at the same position in the different sequences and were corrected depending on respiratory movement. Special attention was paid to omit visible vessels, liver lesions, or regions with artifacts. The size of the ROIs ranged from 1.0 cm² to 3.5 cm². The thus measured average signal intensity was viewed as representative for the entire liver. The relative signal change (relative enhancement, RE) between the unenhanced phase and the hepatobiliary phase was calculated from this as follows:

The liver volume and spleen volume were determined in all patients from the MRI dataset with the help of iNtuition-Viewer software (TeraRecon Inc, San Mateo, Calif). Both the spleen volume and liver volume were determined on the basis of the semiautomatic region-growing algorithm and subsequent manual edge correction by an evaluator with hepatobiliary radiology experience. A marker was placed in the target organ in the image datasets of the hepatobiliary phase and this marker was used by the semiautomatic region-growing algorithm for initial segmenting of the organ. In a second work step, this segmenting was manually checked and corrected if necessary.

Statistical analysis

Statistical analysis was performed via IBM SPSS Statistics (Version 21.0.0.1, Chicago, IL). All data are specified as average ± standard deviation if not otherwise specified.

A simple linear regression analysis of clinical factors was used to determine its influence on the relative signal change. In addition to patient characteristics (age, gender, weight, height), the signal intensity baseline (SI_(native)), the estimated glomerular filtration rate (eGFR) [14], laboratory liver values (GGT, AST, ALT, total bilirubin, number of thrombocytes), as well as the spleen volume and liver volume were examined. The total liver volume (TLV) expected on the basis of the body weight was estimated using the formula described by Vauthey et al. [15]. TLV = 191.80 + 18.51 × weight [kg]. The delta liver volume (Δ liver volume) was then calculated as the difference with respect to the actual liver volume: Δ liver volume = liver volume – TLV

A multiple linear regression of all significant measured values (inclusion criterion: p ≤ 0.05) and a pairwise comparison were then performed. For the pairwise comparison, the patients were divided into three groups on the basis of the relative signal change (RE). An RE > 100 % corresponded to a high signal change (high relative enhancement (HRE); n = 52), an RE between 100 % and 50 % corresponded to a medium signal change (medium relative enhancement (MRE); n = 63) and an RE < 50 % corresponded to a low signal change (low relative enhancement (LRE); n = 9). The non-parametric Mann-Whitney test was used to compare the groups to one another. All statistical analyses were two-sided and p < 0.05 indicated a significant result.

Results

The simple linear regression analysis ([Table 2]) shows a significant (p ≤ 0.05) influence on the relative signal change due to the age of the patient, the liver volume, the spleen volume, and the Δ liver volume as well as the following transaminases: Aspartate aminotransferase (AST), alanine aminotransferase (ALT) and gamma glutamyl transferase (GGT).

Table 2 Resuslts of the simple linear regression analyses with the relative signal change as a dependent variable.

independent variables	B (95 % CI)	r2	p-value
age (years)	–0.37 (–0.68; –0.06)	0.043	0.021
gender	2.35 (–7.01; 11.71)	0.002	0.620
height (m)	–21.32 (–74.99; 32.35)	0.005	0.433
weight (kg)	0.23 (–0.10; 0.55)	0.015	0.173
liver volume (ml)	–0.02 (–0.03; –0.01)	0.102	≤ 0.001
spleen volume (ml)	–0.03 (–0.05; –0.01)	0.08	0.001
Δ liver volume (ml)	–0.03 (–0.03; –0.02)	0.174	≤ 0.001
baseline (SI(native))	0.08 (–0.06; 0.21)	0.01	0.260
aspartate aminotransferase (U/l)	–0.73 (–1.29; –0.17)	0.057	0.011
alanine aminotransferase (U/l)	0.48 (0.02; 0.95)	0.033	0.043
gamma glutamyl transferase (U/l)	–0.08 (–0.12; –0.04)	0.118	≤ 0.001
bilirubin (total) (mg/dl)	–13.93 (–30.62; 2.76)	0.022	0.101
thrombocytes (/nl)	–0.00 (–0.04; 0.04)	0	0.908
estimated glomerular filtration rate (ml/min/1.73 m2)	–0.13 (–0.32; 0.07)	0.014	0.190

B: Regression coefficient, CI: Confidence interval, R²: Coefficient of determination, p: Level of significance.

The result of the multiple linear regression is shown in [Table 3]. In this analysis the spleen volume and Δ liver volume as well as the transferase AST are significant predictors of the relative signal change.

Table 3 results of the multiple linear regression analysis with the relative signal change as a dependent variable. The model showed a coefficient of determination (R²) of 0.352.

independent variables	B (95 % CI)	p-value
age (years)	–0.149 (–0.462; 0.164)	0.347
liver volume (ml)	0.004 (–0.015; 0.023)	0.694
spleen volume (ml)	–0.031 (–0.052; –0.01)	0.004
Δ liver volume (ml)	–0.024 (–0.043; –0.004)	0.017
aspartate aminotransferase (U/l)	–0.676 (–1.289; –0.062)	0.031
alanine aminotransferase (U/l)	0.399 (–0.113; 0.91)	0.125
gamma glutamyl transferase (U/l)	–0.036 (–0.082; 0.011)	0.131

B: Regression coefficient, CI: Confidence interval, p: Level of significance.

The pairwise comparison ([Fig. 1]) of the significant measured values of the simple linear regression analysis yielded significant differences in the AST and the GGT for the transaminases. The comparison of the HRE and the LRE showed a significantly increased value in the LRE group for AST (p = 0.038) and GGT (p = 0.021). A significant difference (p = 0.032) between the LRE and MRE group was seen in the case of GGT. No significant difference between the HRE and MRE group could be found.

Fig. 1 shows the pairwise comparison of clinical factors between the individual subgroups with the corresponding p-values. The data are shown as box plots with the Tukey algorithm being used in the box and whisker plot. HRE: high relative enhancement, MRE: medium relative enhancement, LRE: low relative enhancement.

Further significances resulted for the liver volume and spleen volume in the comparison of the LRE and MRE and in the comparison of the LRE and HRE. Patients in the LRE group had a significantly greater liver volume (2683.9 ± 921.8 ml) and spleen volume (585.2 ± 299.1 ml) compared to the MRE group and the HRE group ([Table 1], [Fig. 1]).

In the pairwise comparison only the Δ liver volume showed a significant difference between all subgroups ([Fig. 1]). With 1066.8 ± 849.7 ml, patients in the LRE group had the greatest deviation from the calculated liver volume with the patients in the HRE group having the lowest deviation (321.5 ± 137.0 ml). [Fig. 2] shows the effect of the Δ liver volume on the signal intensity in the HBP.

Fig. 2 T1-weighted VIBE sequence with fat suppression of the unenhanced phase a, c and the hepatobiliary phase b, d after 20 minutes. a, b show sequences of a male patient with a weight of 104 kg and a height of 1.89 m. The calculated liver volume was 2117 ml, with the actual liver volume being only 1625 ml. This yielded a Δ liver volume of –492 ml. c, d show sequences of a male patient with a weight of 90 kg and a height of 1.72 m. The calculated liver volume was 1858 ml, with the actual liver volume being only 3755 ml. The Δ liver volume was 1897 ml. The average signal intensity was as follows: 213.8 a; 492.4 b; 199.5 c; 297.0 d. The relative signal change was 130 % between a–b and 49 % between c–d.

Discussion

Different imaging methods are available for the daily clinical challenge of detecting and differentiating liver lesions. Studies have already shown that MRI examination is superior to other examinations as a result of the soft tissue contrast enhancement [16] [17]. The method of choice in the diagnosis and classification of liver lesions is currently dynamic contrast-enhanced MRI [18] [19] [20]. The liver-specific contrast agent Gd-EOB-DTPA is suitable for detecting and characterizing liver lesions particularly by combining vascular phases with an additional hepatobiliary phase [21] [22] [23] [24].

The hepatobiliary phase of Gd-EOB-DTPA is made possible by the selective uptake of membrane-bound organic anion transporters (OATP1 B1 / B3) [1] [25] [26]. In addition to biliary elimination [11] [27], Gd-EOB-DTPA is also eliminated with the help of glomerular filtration in the kidneys [4]. The systems can replace one another in the event of damage to one system [28] [29].

It was already shown in different studies that liver function affects the hepatobiliary system [8] [9] [10] [11] [12] [13]. The goal of this study was to analyze clinical factors that could influence the uptake of Gd-EOB-DTPA in a patient collective without liver parenchyma damage.

Like every human organ, the liver is subject to an aging process. In addition to a reduction in liver perfusion and liver volume, the enzyme activity of the liver decreases with age. These changes can affect the uptake as well as the elimination of metabolites [30]. The univariate analysis accordingly showed a significant negative correlation (p = 0.021) between patient age and signal behavior.

The transaminases AST, ALT, and GGT are located in different cell organelles. AST is primarily located in the mitochondria (80 %) but is also found free in the cytoplasm in 20 % of cases. AST is present in different organs such as the liver, heart, and skeletal musculature. Increases in AST occur primarily in the presence of liver metastases, myocarditis, pulmonary embolisms, and chronic alcohol abuse. Although there was a significant negative correlation between AST and RE in the simple and multiple regression analysis, there was only a significant difference (p = 0.038) in the group analysis between the subgroups HRE and LRE ([Fig. 1 d]).

In contrast to AST, ALT is largely specific for liver diseases. It is free in the cytoplasm of the hepatocytes in up to 85 % of cases and is bound in the mitochondria in up to 15 % of cases. Increases in ALT are present in liver metastases and chronic alcohol abuse as well as in the case of a fatty liver. Contrary to the expected negative correlation, ALT showed a positive correlation in our collective. This paradoxical correlation with a low level of significance of p = 0.043 in the simple regression analysis did not yield significant differences between the individual subgroups in the pairwise group analysis.

In contrast to the other liver parameters, GGT is only membrane-bound. It is the most sensitive indicator in problems involving the bile duct system and the liver parenchyma. Significantly higher values were seen in the group analysis in the comparison of the LRE to the HRE (p = 0.021) and in the comparison to the MRE (p = 0032). However, significance could not be found in the multiple linear regression. Increases are seen even in the case of minor damage, such as uncomplicated viral hepatitis, mononucleosis, chronic alcohol abuse, and a fatty liver.

It was shown in recently published studies that the variance in liver volume in patients with liver cirrhosis or acute liver failure correlates well with liver function [31] [32]. Spleen size also plays an important role in the determination of liver function. Different approaches already described, such as spleen volume and the spleen/liver volume ratio, correlate with the liver fibrosis stage [33] [34]. However, different factors such as venous reflux or disruptions in the hematological system affect spleen volume. Moreover, spleen volume cannot be determined in patients with a splenectomy.

The influence of liver and spleen volume on the uptake of Gd-EOB-DTPA could only be shown in this study in the comparison of the LRE subgroup to the MRE and HRE subgroups. There was no significant difference between the MRE and HRE subgroups.

The Δ liver volume showed a significant correlation with the signal intensity change both in the regression analyses and in the pairwise group analysis.
The determination of the Δ liver volume made it possible to detect patients with a liver that is disproportionately large with respect to body weight. Since Gd-EOB-DTPA dose is determined based solely on body weight, inadequate contrast enhancement can occur in patients whose liver volume does not correlate with their body weight. Consequently, these patients receive a dose of Gd-EOB-DTPA that is too low for their liver volume thus resulting in a lower signal intensity in the HBP [3] [4]. This increases the risk of overlooking lesions in the liver parenchyma.

Liver volume-adapted administration of Gd-EOB-DTPA as a form of personalized medicine could help to increase the signal change within the liver during the HBP in these patients. Preliminary imaging can be indicative here and provide information and orientation regarding liver volume or the last contrast agent application. Insufficient doses in the preliminary examination should not be adopted. If no preliminary examinations are available, an estimation of liver volume based on unenhanced sequences prior to contrast agent administration would be a further option for adapting the quantity of Gd-EOB-DTPA to be applied.

The retrospective character of this study represents a limitation. Since this evaluation was performed retrospectively, volume-adapted administration of Gd-EOB-DTPA could not be examined. As a result, a recommendation regarding the extent of dose adaptation cannot be made on the basis of the present data. Additional studies are needed to better evaluate this data.

However, it can be concluded from the present data of this study that a weight-adapted dose of Gd-EOB-DTPA (0.1 ml/kg body weight) achieved an adequate signal change of the liver in the HBP in 93 % of patients (HRE + MRE; 115/124). Significantly limited contrast enhancement of the liver in the HBP occurred in only 7 % of the study collective (n = 9, LRE).

• References

• 1 van Montfoort JE, Stieger B, Meijer DK et al. Hepatic uptake of the magnetic resonance imaging contrast agent gadoxetate by the organic anion transporting polypeptide Oatp1. The Journal of pharmacology and experimental therapeutics 1999; 290: 153-157
• 2 Pascolo L, Cupelli F, Anelli PL et al. Molecular mechanisms for the hepatic uptake of magnetic resonance imaging contrast agents. Biochem Biophys Res Commun 1999; 257: 746-752
• 3 Reimer P, Rummeny EJ, Shamsi K et al. Phase II clinical evaluation of Gd-EOB-DTPA: dose, safety aspects, and pulse sequence. Radiology 1996; 199: 177-183
• 4 Hamm B, Staks T, Muhler A et al. Phase I clinical evaluation of Gd-EOB-DTPA as a hepatobiliary MR contrast agent: safety, pharmacokinetics, and MR imaging. Radiology 1995; 195: 785-792
• 5 Haimerl M, Wachtler M, Platzek I et al. Added value of Gd-EOB-DTPA-enhanced Hepatobiliary phase MR imaging in evaluation of focal solid hepatic lesions. BMC medical imaging 2013; 13: 41
• 6 Sun HY, Lee JM, Shin CI et al. Gadoxetic acid-enhanced magnetic resonance imaging for differentiating small hepatocellular carcinomas (< or =2 cm in diameter) from arterial enhancing pseudolesions: special emphasis on hepatobiliary phase imaging. Invest Radiol 2010; 45: 96-103
• 7 Bieze M, van den Esschert JW, Nio CY et al. Diagnostic accuracy of MRI in differentiating hepatocellular adenoma from focal nodular hyperplasia: prospective study of the additional value of gadoxetate disodium. American journal of roentgenology 2012; 199: 26-34
• 8 Nishie A, Asayama Y, Ishigami K et al. MR prediction of liver fibrosis using a liver-specific contrast agent: Superparamagnetic iron oxide versus Gd-EOB-DTPA. Journal of magnetic resonance imaging: JMRI 2012; 36: 664-671
• 9 Verloh N, Haimerl M, Rennert J et al. Impact of liver cirrhosis on liver enhancement at Gd-EOB-DTPA enhanced MRI at 3Tesla. European journal of radiology 2013; 82: 1710-1715
• 10 Ryeom HK, Kim SH, Kim JY et al. Quantitative evaluation of liver function with MRI Using Gd-EOB-DTPA. Korean journal of radiology: official journal of the Korean Radiological Society 2004; 5: 231-239
• 11 Tsuda N, Okada M, Murakami T. Potential of gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (Gd-EOB-DTPA) for differential diagnosis of nonalcoholic steatohepatitis and fatty liver in rats using magnetic resonance imaging. Invest Radiol 2007; 42: 242-247
• 12 Nilsson H, Blomqvist L, Douglas L et al. Assessment of liver function in primary biliary cirrhosis using Gd-EOB-DTPA-enhanced liver MRI. HPB the official journal of the International Hepato Pancreato Biliary Association 2010; 12: 567-576
• 13 Verloh N, Haimerl M, Zeman F et al. Assessing liver function by liver enhancement during the hepatobiliary phase with Gd-EOB-DTPA-enhanced MRI at 3 Tesla. European radiology 2014;
• 14 Levey AS, Bosch JP, Lewis JB et al. A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group. Annals of internal medicine 1999; 130: 461-470
• 15 Vauthey JN, Abdalla EK, Doherty DA et al. Body surface area and body weight predict total liver volume in Western adults. Liver transplantation official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society 2002; 8: 233-240
• 16 Ichikawa T, Saito K, Yoshioka N et al. Detection and characterization of focal liver lesions: a Japanese phase III, multicenter comparison between gadoxetic acid disodium-enhanced magnetic resonance imaging and contrast-enhanced computed tomography predominantly in patients with hepatocellular carcinoma and chronic liver disease. Invest Radiol 2010; 45: 133-141
• 17 Semelka RC, Martin DR, Balci C et al. Focal liver lesions: comparison of dual-phase CT and multisequence multiplanar MR imaging including dynamic gadolinium enhancement. Journal of magnetic resonance imaging 2001; 13: 397-401
• 18 Petersein J, Spinazzi A, Giovagnoni A et al. Focal liver lesions: evaluation of the efficacy of gadobenate dimeglumine in MR imaging – a multicenter phase III clinical study. Radiology 2000; 215: 727-736
• 19 Hamm B, Thoeni RF, Gould RG et al. Focal liver lesions: characterization with nonenhanced and dynamic contrast material-enhanced MR imaging. Radiology 1994; 190: 417-423
• 20 Kim YK, Kwak HS, Kim CS et al. Hepatocellular carcinoma in patients with chronic liver disease: comparison of SPIO-enhanced MR imaging and 16-detector row CT. Radiology 2006; 238: 531-541
• 21 Zizka J, Klzo L, Ferda J et al. Dynamic and delayed contrast enhancement in upper abdominal MRI studies: comparison of gadoxetic acid and gadobutrol. European journal of radiology 2007; 62: 186-191
• 22 Asayama Y, Tajima T, Nishie A et al. Uptake of Gd-EOB-DTPA by hepatocellular carcinoma: radiologic-pathologic correlation with special reference to bile production. European journal of radiology 2011; 80: e243-e248
• 23 Kobayashi S, Matsui O, Gabata T et al. Relationship between signal intensity on hepatobiliary phase of gadolinium ethoxybenzyl diethylenetriaminepentaacetic acid (Gd-EOB-DTPA)-enhanced MR imaging and prognosis of borderline lesions of hepatocellular carcinoma. European journal of radiology 2012; 81: 3002-3009
• 24 Akai H, Matsuda I, Kiryu S et al. Fate of hypointense lesions on Gd-EOB-DTPA-enhanced magnetic resonance imaging. European journal of radiology 2012; 81: 2973-2977
• 25 Weinmann HJ, Bauer H, Frenzel T et al. Mechanism of hepatic uptake of gadoxetate disodium. Academic radiology 1996; 3 (Suppl. 02) S232-S234
• 26 Van Beers BE, Pastor CM, Hussain HK. Primovist, Eovist: what to expect?. Journal of hepatology 2012; 57: 421-429
• 27 Tsuboyama T, Onishi H, Kim T et al. Hepatocellular carcinoma: hepatocyte-selective enhancement at gadoxetic acid-enhanced MR imaging – correlation with expression of sinusoidal and canalicular transporters and bile accumulation. Radiology 2010; 255: 824-833
• 28 Tamada T, Ito K, Sone T et al. Gd-EOB-DTPA enhanced MR imaging: evaluation of biliary and renal excretion in normal and cirrhotic livers. European journal of radiology 2011; 80: e207-e211
• 29 Muhler A, Heinzelmann I, Weinmann HJ. Elimination of gadolinium-ethoxybenzyl-DTPA in a rat model of severely impaired liver and kidney excretory function. An experimental study in rats. Invest Radiol 1994; 29: 213-216
• 30 Tajiri K, Shimizu Y. Liver physiology and liver diseases in the elderly. World journal of gastroenterology: WJG 2013; 19: 8459-8467
• 31 Tong C, Xu X, Liu C et al. Assessment of liver volume variation to evaluate liver function. Frontiers of medicine 2012; 6: 421-427
• 32 Zhou XP, Lu T, Wei YG et al. Liver volume variation in patients with virus-induced cirrhosis: findings on MDCT. American journal of roentgenology 2007; 189: W153-W159
• 33 Liu P, Li P, He W et al. Liver and spleen volume variations in patients with hepatic fibrosis. World journal of gastroenterology 2009; 15: 3298-3302
• 34 Goshima S, Kanematsu M, Watanabe H et al. Gd-EOB-DTPA-enhanced MR imaging: prediction of hepatic fibrosis stages using liver contrast enhancement index and liver-to-spleen volumetric ratio. Journal of magnetic resonance imaging: JMRI 2012; 36: 1148-1153