Quantification of hepatic perfusion and hepatocyte function with dynamic gadoxetic acid-enhanced MRI in patients with chronic liver disease

Application of Pharmacokinetic Modeling to Characterize Hepatobiliary Disposition of Imaging Agents and Alterations due to Liver Injury in Isolated Perfused Rat Livers

BACKGROUND

Understanding the impact of altered hepatic uptake and/or efflux on the hepatobiliary disposition of the imaging agents [99mTc]Mebrofenin (MEB) and [153Gd]Gadobenate dimeglumine (BOPTA) is important for proper estimation of liver function.

METHODS

A multi-compartmental pharmacokinetic (PK) model describing MEB and BOPTA disposition in isolated perfused rat livers (IPRLs) was developed. The PK model was simultaneously fit to MEB and BOPTA concentration-time data in the extracellular space, hepatocytes, bile canaliculi, and sinusoidal efflux in livers from healthy rats, and to BOPTA concentration-time data in rats pretreated with monocrotaline (MCT).

RESULTS

The model adequately described MEB and BOPTA disposition in each compartment. The hepatocyte uptake clearance was much higher for MEB (55.3 mL/min) than BOPTA (6.67 mL/min), whereas the sinusoidal efflux clearance for MEB (0.000831 mL/min) was lower than BOPTA (0.0127 mL/min). The clearance from hepatocytes to bile (CLbc) for MEB (0.658 mL/min) was similar to BOPTA (0.642 mL/min) in healthy rat livers. The BOPTA CLbc was reduced in livers from MCT-pretreated rats (0.496 mL/min), while the sinusoidal efflux clearance was increased (0.0644 mL/min).

CONCLUSION

A PK model developed to characterize MEB and BOPTA disposition in IPRLs was used to quantify changes in the hepatobiliary disposition of BOPTA caused by MCT pretreatment of rats to induce liver toxicity. This PK model could be applied to simulate changes in the hepatobiliary disposition of these imaging agents in rats in response to altered hepatocyte uptake or efflux associated with disease, toxicity, or drug-drug interactions.

Mathematical models for biomarker calculation of drug-induced liver injury in humans and experimental models based on gadoxetate enhanced magnetic resonance imaging

BACKGROUND

Drug induced liver injury (DILI) is a major concern when developing new drugs. A promising biomarker for DILI is the hepatic uptake rate of the contrast agent gadoxetate. This rate can be estimated using a novel approach combining magnetic resonance imaging and mathematical modeling. However, previous work has used different mathematical models to describe liver function in humans or rats, and no comparative study has assessed which model is most optimal to use, or focused on possible translatability between the two species.

AIMS

Our aim was therefore to do a comparison and assessment of models for DILI biomarker assessment, and to develop a conceptual basis for a translational framework between the species.

METHODS AND RESULTS

We first established which of the available pharmacokinetic models to use by identifying the most simple and identifiable model that can describe data from both human and rats. We then developed an extension of this model for how to estimate the effects of a hepatotoxic drug in rats. Finally, we illustrated how such a framework could be useful for drug dosage selection, and how it potentially can be applied in personalized treatments designed to avoid DILI.

CONCLUSION

Our analysis provides clear guidelines of which mathematical model to use for model-based assessment of biomarkers for liver function, and it also suggests a hypothetical path to a translational framework for DILI.

Noninvasive staging of liver fibrosis: review of current quantitative CT and MRI-based techniques

Liver fibrosis features excessive protein accumulation in the liver interstitial space resulting from repeated tissue injury due to chronic liver disease. Liver fibrosis eventually proceeds to cirrhosis and associated complications. So, early diagnosis and staging of liver fibrosis are of vital importance for clinical treatment. Liver biopsy remains the gold standard for the diagnosing and staging of fibrosis, but it is suboptimal due to various limitations. Recently, efforts have been made to migrate toward noninvasive techniques for assessing liver fibrosis. CT is relatively easy to perform, relatively standardized for different scanners, and does not require additional hardware in liver fibrosis staging. MRI is frequently performed to characterize indeterminate liver lesions. Because it does not use ionizing radiation and features high image contrast, its role has increased in the staging of liver fibrosis. More recently, several studies on liver fibrosis staging using deep learning algorithms in CT or MRI have been proposed and have shown meaningful results. In this review, we summarize the basic concept, diagnostic performance, and advantages and limitations of each technique to noninvasively stage liver fibrosis.

Hepatectomy-Induced Alterations in Hepatic Perfusion and Function - Toward Multi-Scale Computational Modeling for a Better Prediction of Post-hepatectomy Liver Function

Liver resection causes marked perfusion alterations in the liver remnant both on the organ scale (vascular anatomy) and on the microscale (sinusoidal blood flow on tissue level). These changes in perfusion affect hepatic functions via direct alterations in blood supply and drainage, followed by indirect changes of biomechanical tissue properties and cellular function. Changes in blood flow impose compression, tension and shear forces on the liver tissue. These forces are perceived by mechanosensors on parenchymal and non-parenchymal cells of the liver and regulate cell-cell and cell-matrix interactions as well as cellular signaling and metabolism. These interactions are key players in tissue growth and remodeling, a prerequisite to restore tissue function after PHx. Their dysregulation is associated with metabolic impairment of the liver eventually leading to liver failure, a serious post-hepatectomy complication with high morbidity and mortality. Though certain links are known, the overall functional change after liver surgery is not understood due to complex feedback loops, non-linearities, spatial heterogeneities and different time-scales of events. Computational modeling is a unique approach to gain a better understanding of complex biomedical systems. This approach allows (i) integration of heterogeneous data and knowledge on multiple scales into a consistent view of how perfusion is related to hepatic function; (ii) testing and generating hypotheses based on predictive models, which must be validated experimentally and clinically. In the long term, computational modeling will (iii) support surgical planning by predicting surgery-induced perfusion perturbations and their functional (metabolic) consequences; and thereby (iv) allow minimizing surgical risks for the individual patient. Here, we review the alterations of hepatic perfusion, biomechanical properties and function associated with hepatectomy. Specifically, we provide an overview over the clinical problem, preoperative diagnostics, functional imaging approaches, experimental approaches in animal models, mechanoperception in the liver and impact on cellular metabolism, omics approaches with a focus on transcriptomics, data integration and uncertainty analysis, and computational modeling on multiple scales. Finally, we provide a perspective on how multi-scale computational models, which couple perfusion changes to hepatic function, could become part of clinical workflows to predict and optimize patient outcome after complex liver surgery.

New Pharmacokinetic Parameters of Imaging Substrates Quantified from Rat Liver Compartments

Hepatobiliary imaging is increasingly used by pharmacologists to quantify liver concentrations of transporter-dependent drugs. However, liver imaging does not quantify concentrations in extracellular space, hepatocytes, and bile canaliculi. Our study compared the compartmental distribution of two hepatobiliary substrates gadobenate dimeglumine [BOPTA; 0.08 liver extraction ratio (ER)] and mebrofenin (MEB; 0.93 ER) in a model of perfused rat liver. A gamma counter placed over livers measured liver concentrations. Livers were preperfused with gadopentetate dimeglumine to measure extracellular concentrations. Concentrations coming from bile canaliculi and hepatocytes were calculated. Transporter activities were assessed by concentration ratios between compartments and pharmacokinetic parameters that describe the accumulation and decay profiles of hepatocyte concentrations. The high liver concentrations of MEB relied mainly on hepatocyte and bile canaliculi concentrations. In contrast, the three compartments contributed to the low liver concentrations obtained during BOPTA perfusion. Nonlinear regression analysis of substrate accumulation in hepatocytes revealed that cellular efflux is measurable ∼4 minutes after the start of perfusion. The hepatocyte-to-extracellular concentration ratio measured at this time point was much higher during MEB perfusion. BOPTA transport by multidrug resistance associated protein 2 induced an aquaporin-mediated water transport, whereas MEB transport did not. BOPTA clearance from hepatocytes to bile canaliculi was higher than MEB clearance. MEB did not efflux back to sinusoids, whereas BOPTA basolateral efflux contributed to the decrease in hepatocyte concentrations. In conclusion, our ex vivo model quantifies substrate compartmental distribution and transport across hepatocyte membranes and provides an additional understanding of substrate distribution in the liver. SIGNIFICANCE STATEMENT: When transporter-dependent drugs target hepatocytes, cellular concentrations are important to investigate. Low concentrations on cellular targets impair drug therapeutic effects, whereas excessive hepatocyte concentrations may induce cellular toxicity. With a gamma counter placed over rat perfused livers, we measured substrate concentrations in the extracellular space, hepatocytes, and bile canaliculi. Transport across hepatocyte membranes was calculated. The study provides an additional understanding of substrate distribution in the liver.

A model selection framework to quantify microvascular liver function in gadoxetate-enhanced MRI: Application to healthy liver, diseased tissue, and hepatocellular carcinoma

PURPOSE

We introduce a novel, generalized tracer kinetic model selection framework to quantify microvascular characteristics of liver and tumor tissue in gadoxetate-enhanced dynamic contrast-enhanced MRI (DCE-MRI).

METHODS

Our framework includes a hierarchy of nested models, from which physiological parameters are derived in 2 regimes, corresponding to the active transport and free diffusion of gadoxetate. We use simulations to show the sensitivity of model selection and parameter estimation to temporal resolution, time-series duration, and noise. We apply the framework in 8 healthy volunteers (time-series duration up to 24 minutes) and 10 patients with hepatocellular carcinoma (6 minutes).

RESULTS

The active transport regime is preferred in 98.6% of voxels in volunteers, 82.1% of patients' non-tumorous liver, and 32.2% of tumor voxels. Interpatient variations correspond to known co-morbidities. Simulations suggest both datasets have sufficient temporal resolution and signal-to-noise ratio, while patient data would be improved by using a time-series duration of at least 12 minutes.

CONCLUSIONS

In patient data, gadoxetate exhibits different kinetics: (a) between liver and tumor regions and (b) within regions due to liver disease and/or tumor heterogeneity. Our generalized framework selects a physiological interpretation at each voxel, without preselecting a model for each region or duplicating time-consuming optimizations for models with identical functional forms.

Recent Progress in the Molecular Imaging of Nonalcoholic Fatty Liver Disease

Pathological fibrosis of the liver is a landmark feature in chronic liver diseases, including nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH). Diagnosis and assessment of progress or treatment efficacy today requires biopsy of the liver, which is a challenge in, e.g., longitudinal interventional studies. Molecular imaging techniques such as positron emission tomography (PET) have the potential to enable minimally invasive assessment of liver fibrosis. This review will summarize and discuss the current status of the development of innovative imaging markers for processes relevant for fibrogenesis in liver, e.g., certain immune cells, activated fibroblasts, and collagen depositions.

CT and MR perfusion techniques to assess diffuse liver disease

Perfusion imaging allows for the quantitative extraction of physiological perfusion parameters of the liver microcirculation at levels far below the spatial the resolution of CT and MR imaging. Because of its peculiar structure and architecture, perfusion imaging is more challenging in the liver than in other organs. Indeed, the liver is a mobile organ and significantly deforms with respiratory motion. Moreover, it has a dual vascular supply and the sinusoidal capillaries are fenestrated in the normal liver. Using extracellular contrast agents, perfusion imaging has shown its ability to discriminate patients with various stages of liver fibrosis. The recent introduction of hepatobiliary contrast agents enables quantification of both the liver perfusion and the hepatocyte transport function using advanced perfusion models. The purpose of this review article is to describe the characteristics of liver perfusion imaging to assess chronic liver disease, with a special focus on CT and MR imaging.

Magnetic resonance-based biomarkers in nonalcoholic fatty liver disease and nonalcoholic steatohepatitis

Nonalcoholic fatty liver disease is a growing epidemic affecting 30% of the adult population in the Western world. Its progressive form, nonalcoholic steatohepatitis (NASH), is associated with an increased risk of advanced fibrosis, cirrhosis and liver-related mortality. Therefore, the detection of NAFLD and risk stratification according to the severity of the disease is crucial for the management of patients with NAFLD. Liver biopsy for such risk stratification strategies is limited by its cost and risks; therefore, noninvasive alternatives have been developed. Among noninvasive biomarkers developed in NAFLD, magnetic resonance (MR)-based biomarkers have emerged as key noninvasive biomarkers in NAFLD with the ability to accurately detect hepatic steatosis and liver fibrosis. The potential utility of MRI for the detection of NASH and functional liver assessment has also recently emerged. In the current review, we will discuss the data supporting the utility of MR-based biomarker for the detection of features of NAFLD and its potential use in clinical practice and clinical research in NAFLD.

Liver function quantification of patients with portal vein embolization using dynamic contrast-enhanced MRI for assessment of hepatocyte uptake and elimination

PURPOSE

We evaluated pharmacokinetic models which quantify liver function including biliary elimination based on a dynamic Gd-EOB-DTPA-enhanced magnetic resonance imaging (MRI) technique with sparse data collection feasible in clinical routine.

METHODS

Twelve patients with embolized liver segments following interventional treatment of primary liver cancer or hepatic metastasis underwent MRI. During Gd-EOB-DTPA bolus administration, a 3D dynamic gradient-echo (GRE) MRI examination was performed over approx. 28 min. Interrupted data sampling was started approx. 5 min after contrast agent administration. Different implementations of dual-inlet models were tested, namely the Euler method (DE) and convolution with residue functions (C). A simple uptake model (U) and an uptake- elimination model (UE) extended by incorporating the biliary contrast agent elimination rate (K_e) were evaluated.

RESULTS

The uptake-elimination model, calculated via the simple Euler method (UE- DE) and by convolution (UE-C), yielded similar overall estimates in terms of fitting quality and agreement with published values. The Euler method was approx. 50 times faster and yielded a mean elimination rate of K_e=1.8±1.2mL/(min·100 mL) in nonembolized liver tissue, which was significantly higher (p=8.8·10^-4) than in embolized tissue K_e=0.4±0.4 mL/(min·100 mL). Fractional hepatocyte volume v_h was not significantly higher in nonembolized tissue (52.4 ± 13.4 mL/100 mL) compared to embolized tissue (44.4 ± 26.1 mL/100 mL).

CONCLUSIONS

Interrupted late enhancement MRI data sampling in conjunction with the uptake-elimination model, deconvolved by integration of the differential rate equation and combined with the simple uptake model implemented with the Euler method (U-DE), turned out to be a stable and practical method for reliable noninvasive assessment of liver function.

Use of imaging to assess the activity of hepatic transporters

Introduction: Membrane transporters of the SLC and ABC families are abundantly expressed in the liver, where they control the transfer of drugs/drug metabolites across the sinusoidal and canalicular hepatocyte membranes and play a pivotal role in hepatic drug clearance. Noninvasive imaging methods, such as PET, SPECT or MRI, allow for measuring the activity of hepatic transporters in vivo, provided that suitable transporter imaging probes are available.Areas covered: We give an overview of the working principles of imaging-based assessment of hepatic transporter activity. We discuss different currently available PET/SPECT radiotracers and MRI contrast agents and their applications to measure hepatic transporter activity in health and disease. We cover mathematical modeling approaches to obtain quantitative parameters of transporter activity and provide a critical assessment of methodological limitations and challenges associated with this approach.Expert opinion: PET in combination with pharmacokinetic modeling can be potentially applied in drug development to study the distribution of new drug candidates to the liver and their clearance mechanisms. This approach bears potential to mechanistically assess transporter-mediated drug-drug interactions, to assess the influence of disease on hepatic drug disposition and to validate and refine currently available in vitro-in vivo extrapolation methods to predict hepatic clearance of drugs.

GAN and dual-input two-compartment model-based training of a neural network for robust quantification of contrast uptake rate in gadoxetic acid-enhanced MRI

PURPOSE

Gadoxetic acid uptake rate (k₁ ) obtained from dynamic, contrast-enhanced (DCE) magnetic resonance imaging (MRI) is a promising measure of regional liver function. Clinical exams are typically poorly temporally characterized, as seen in a low temporal resolution (LTR) compared to high temporal resolution (HTR) experimental acquisitions. Meanwhile, clinical demands incentivize shortening these exams. This study develops a neural network-based approach to quantitation of k₁ , for increased robustness over current models such as the linearized single-input, two-compartment (LSITC) model.

METHODS

Thirty Liver HTR DCE MRI exams were acquired in 22 patients with at least 16 min of postcontrast data sampled at least every 13 s. A simple neural network (NN) with four hidden layers was trained on voxel-wise LTR data to predict k₁ . Low temporal resolution data were created by subsampling HTR data to contain six time points, replicating the characteristics of clinical LTR data. Both the total length and the placement of points in the training data were varied considerably to encourage robustness to variation. A generative adversarial network (GAN) was used to generate arterial and portal venous inputs for use in data augmentation based on the dual-input, two-compartment, pharmacokinetic model of gadoxetic acid in the liver. The performance of the NN was compared to direct application of LSITC on both LTR and HTR data. The error was assessed when subsampling lengths from 16 to 4 min, enabling assessment of robustness to acquisition length.

RESULTS

For acquisition lengths of 16 min NRMSE (Normalized Root-Mean-Squared Error) in k₁ was 0.60, 1.77, and 1.21, for LSITC applied to HTR data, LSITC applied to LTR data, and GAN-augmented NN applied to LTR data, respectively. As the acquisition length was shortened, errors greatly increased for LSITC approaches by several folds. For acquisitions shorter than 12 min the GAN-augmented NN approach outperformed the LSITC approach to a statistically significant extent, even with HTR data.

CONCLUSIONS

The study indicates that data length is significant for LSITC analysis as applied to DCE data for standard temporal sampling, and that machine learning methods, such as the implemented NN, have potential for much greater resilience to shortened acquisition time than directly fitting to the LSITC model.

Application Value of Magnetic Resonance Perfusion Imaging in the Early Diagnosis of Rat Hepatic Fibrosis

Objective

To assess the application value of perfusion-weighted imaging (PWI) in early diagnosis, quantitation, and hepatic fibrosis staging by analyzing the related parameters in hepatic fibrosis.

Methods

A total of 60 rats were randomly divided into the hepatic fibrosis and control groups, and carbon tetrachloride (CCL4) was used to establish the liver fibrosis model. All rats underwent PWI examination, and the trend of the time-signal intensity curve (TIC, automatically generated by the software) was observed. Also, the perfusion parameters, maximum signal reduction ratio (SRRmax), time to peak (TTP), and mean transit time (MTT), were analyzed and compared with pathological staging.

Results

The TIC curve was characterized by slow wash-in and wash-out with a low and wide peak. The PWI perfusion parameters were statistically significant in specific groups (P < 0.05): SRRmax values (control group and F3, F4), TTP, and MTT values (control group and F2–F4, F1 and F3, F1 and F4, and F2 and F4 in addition to TTP values for F1 and F2). Pearson's correlation analysis showed a negative correlation of SRRmax with hepatic fibrosis stage (r = −0.439, P < 0.05), while TTP and MTT values were positively correlated with hepatic fibrosis stage (TTP, r = 0.798; MTT, r = 0.647; all P < 0.001).

Conclusions

PWI perfusion parameters reflect the degree of hepatic fibrosis, especially TTP and MTT, and PWI is recommended for the early diagnosis of liver fibrosis for timely intervention and treatment of the disease and delaying its progression.

Model-inferred mechanisms of liver function from magnetic resonance imaging data: Validation and variation across a clinically relevant cohort

Estimation of liver function is important to monitor progression of chronic liver disease (CLD). A promising method is magnetic resonance imaging (MRI) combined with gadoxetate, a liver-specific contrast agent. For this method, we have previously developed a model for an average healthy human. Herein, we extended this model, by combining it with a patient-specific non-linear mixed-effects modeling framework. We validated the model by recruiting 100 patients with CLD of varying severity and etiologies. The model explained all MRI data and adequately predicted both timepoints saved for validation and gadoxetate concentrations in both plasma and biopsies. The validated model provides a new and deeper look into how the mechanisms of liver function vary across a wide variety of liver diseases. The basic mechanisms remain the same, but increasing fibrosis reduces uptake and increases excretion of gadoxetate. These mechanisms are shared across many liver functions and can now be estimated from standard clinical images.

Being able to accurately and reliably estimate liver function is important when monitoring the progression of patients with liver disease, as well as when identifying drug-induced liver injury during drug development. A promising method for quantifying liver function is to use magnetic resonance imaging combined with gadoxetate. Gadoxetate is a liver-specific contrast agent, which is taken up by the hepatocytes and excreted into the bile. We have previously developed a mechanistic model for gadoxetate dynamics using averaged data from healthy volunteers. In this work, we extended our model with a non-linear mixed-effects modeling framework to give patient-specific estimates of the gadoxetate transport-rates. We validated the model by recruiting 100 patients with liver disease, covering a range of severity and etiologies. All patients underwent an MRI-examination and provided both blood and liver biopsies. Our validated model provides a new and deeper look into how the mechanisms of liver function varies across a wide variety of liver diseases. The basic mechanisms remain the same, but increasing fibrosis reduces uptake and increases excretion of gadoxetate.

Hepatocyte Concentrations of Imaging Compounds Associated with Transporter Inhibition: Evidence in Perfused Rat Livers

In the liver, several approaches are used to investigate and predict the complex issue of drug-induced transporter inhibition. These approaches include in vitro assays and pharmacokinetic models that predict how inhibitors modify the systemic and liver concentrations of the victim drugs. Imaging is another approach that shows how inhibitors might alter liver concentrations stronger than systemic concentrations. In perfused rat livers associated with a gamma counter that measures liver concentrations continuously, we previously showed how fluxes across transporters generate the hepatocyte concentrations of two clinical imaging compounds, one with a low extraction ratio [gadobenate dimeglumine (BOPTA)] and one with a high extraction ratio [mebrofenin (MEB)]. BOPTA and MEB are transported by rat organic anion transporting polypeptide and multiple resistance-associated protein 2, which are both inhibited by rifampicin. The aim of the study is to measure how rifampicin modifies the hepatocyte concentrations and membrane clearances of BOPTA and MEB and to determine whether these compounds might be used to investigate transporter-mediated drug-drug interactions in clinical studies. We show that rifampicin coperfusion greatly decreases BOPTA hepatocyte concentrations, but increases those of MEB. Rifampicin strongly decreases BOPTA hepatic clearance. In contrast, rifampicin decreases moderately MEB hepatic clearance and blocks the biliary intrinsic clearance, increasing MEB hepatocyte concentrations. In conclusion, low concentrations prevent the quantification of BOPTA biliary intrinsic clearance, while MEB is a promising imaging probe substrate to evidence transporter-mediated drug-drug interactions when inhibitors act on influx and efflux transporters.

OATPB1/B3 and MRP3 expression in hepatocellular adenoma predicts Gd-EOB-DTPA uptake and correlates with risk of malignancy

BACKGROUND AND AIMS

Hepatobiliary phase (HBP) Gd-EOB-DTPA-enhanced magnetic resonance imaging (MRI) has increased the accuracy in differentiating focal nodular hyperplasia (FNH) and hepatocellular adenoma (HCA). However, the ability of this technique to distinguish HCA subtypes remains controversial. The aim of this study was to investigate the expression of hepatocyte transporters (OATPB1/B3, MRP2, MRP3) in HCA subtypes, hence to understand their MRI signal intensity on HBP Gd-EOB-DTPA-enhanced MRI.

METHODS

By means of immunohistochemistry (IHC), we scored the expression of OATPB1/B3, MRP2 and MRP3, in resected specimens of FNH (n = 40), subtyped HCA (n = 58) and HCA with focal malignant transformation (HCA-HCC, n = 4). Results were validated on a supplementary set of FNH (n = 6), subtyped HCA (n = 17) and HCA-HCC (n = 1) with Gd-EOB-DTPA MR images.

RESULTS

All FNH showed a preserved expression of hepatocytes transporters. Beta-catenin-activated HCA (at highest risk of malignant transformation) and HCA-HCC were characterized by preserved/increased OATPB1/B3 expression (predictor of hyperintensity on HBP), as opposed to other HCA subtypes (P < 0.01) that mostly showed OATPB1/B3 absence (predictor of hypointensity on HBP). HCA-HCC showed an additional MRP3 overexpressed profile (P < 0.01). On HBP Gd-EOB-DTPA-enhanced MRI, FNH and HCA signal intensity reflected the profile predicted by their specific OATPB1/B3 tissue expression. The hyperintense vs hypointense HBP signal criterion was able to distinguish all higher risk HCA and HCA-HCC (100% accuracy).

CONCLUSIONS

OATPB1/B3 and MRP3 IHC and signal intensity on HBP Gd-EOB-DTPA-enhanced MRI can help to stratify HCA according to their risk of malignant transformation.

Isolated Perfused Rat Livers to Quantify the Pharmacokinetics and Concentrations of Gd-BOPTA

With recent advances in liver imaging, the estimation of liver concentrations is now possible following the injection of hepatobiliary contrast agents and radiotracers. However, how these images are generated remains partially unknown. Most experiments that would be helpful to increase this understanding cannot be performed in vivo. For these reasons, we investigated the liver distribution of the magnetic resonance (MR) contrast agent gadobenate dimeglumine (Gd-BOPTA, MultiHance®, Bracco Imaging) in isolated perfused rat livers (IPRLs). In IPRL, we developed a new set up that quantifies simultaneously the Gd-BOPTA compartment concentrations and the transfer rates between these compartments. Concentrations were measured either by MR signal intensity or by count rates when the contrast agent was labelled by [¹⁵³Gd]. With this experimental model, we show how the Gd-BOPTA hepatocyte concentrations are modified by temperature and liver flow rates. We define new pharmacokinetic parameters to quantify the canalicular transport of Gd-BOPTA. Finally, we present how transfer rates generate Gd-BOPTA concentrations in rat liver compartments. These findings better explain how liver imaging with hepatobiliary radiotracers and contrast agents is generated and improve the image interpretation by clinicians.