Using a diet-induced non-alcoholic fatty liver disease (NAFLD) mouse model, we describe the use of novel in vivo micro-computed tomography imaging techniques as a non-invasive method to assess the progression stages of NAFLD, focusing predominantly on the hepatic vascular network due to its significant involvement in NAFLD-related hepatic dysregulation.
Non-alcoholic fatty liver disease (NAFLD) is a growing global health issue, and the impact of NAFLD is compounded by the current lack of effective treatments. Considerable limiting factors hindering the timely and accurate diagnosis (including grading) and monitoring of NAFLD, as well as the development of potential therapies, are the current inadequacies in the characterization of the hepatic microenvironment structure and the scoring of the disease stage in a spatiotemporal and non-invasive manner. Using a diet-induced NAFLD mouse model, we investigated the use of in vivo micro-computed tomography (CT) imaging techniques as a non-invasive method to assess the progression stages of NAFLD, focusing predominantly on the hepatic vascular network due to its significant involvement in NAFLD-related hepatic dysregulation. This imaging methodology allows for longitudinal analysis of liver steatosis and functional tissue uptake, as well as the evaluation of the relative blood volume, portal vein diameter, and density of the vascular network. Understanding the adaptations of the hepatic vascular network during NAFLD progression and correlating this with other ways of characterizing the disease progression (steatosis, inflammation, fibrosis) using the proposed method can pave the way toward the establishment of new, more efficient, and reproducible approaches for NAFLD research in mice. This protocol is also expected to upgrade the value of preclinical animal models for investigating the development of novel therapies against disease progression.
Non-alcoholic fatty liver disease (NAFLD) is a metabolic disease that affects approximately 25% of the population and >80% of morbidly obese people1. An estimated one-third of these individuals progress to non-alcoholic steatohepatitis (NASH), which is characterized by hepatic steatosis, inflammation, and fibrosis2. NASH is a disease stage with a significantly higher risk for the development of cirrhosis and hepatocellular carcinoma (HCC)3,4. For this reason, NASH is currently the second most common cause of liver transplantation, and it is also expected to soon become the most important predictor of liver transplantation5,6,7. Despite its prevalence and severity, no disease-specific therapy is available for NAFLD, and the existing treatments only aim to tackle disease-associated pathologies such as insulin resistance and hyperlipidemia5,6.
In recent years, the pathophysiological role and adaptations of the endothelium and, in general, of the vascular network of metabolic tissues, such as the adipose tissue and the liver, have been gaining more importance in research, especially during obesity and metabolic dysregulation7,8. The endothelium is a cellular monolayer that lines the vascular network internally, acting as a functional and structural barrier. It also contributes to various physiological and pathological processes, such as thrombosis, metabolite transport, inflammation, and angiogenesis9,10. In the case of the liver, the vascular network is, among other features, characterized by the presence of highly specialized cells, defined as liver sinusoidal endothelial cells (LSECs). These cells lack a basement membrane and have multiple fenestrae, allowing for the easier transfer of substrates between the blood and liver parenchyma. Due to their distinctive anatomical location and characteristics, LSECs likely have a crucial role in the pathophysiological processes of the liver, including the development of liver inflammation and fibrosis during NAFLD/NASH. Indeed, the pathological, molecular, and cellular adaptations that LSECs undergo in the course of NAFLD contribute to the disease progression11. Specifically, the LSEC-dependent hepatic angiogenesis that takes place during NAFLD is significantly associated with the development of inflammation and the progression of the disease to NASH or even HCC12. Besides, obesity-related early NAFLD is characterized by the development of insulin resistance in LSECs, which precedes the development of hepatic inflammation or other advanced NAFLD signs13.
Additionally, LSECs have recently emerged as central regulators of hepatic blood flow and vascular network adaptations during liver disease of several etiologies14,15. Indeed, chronic liver disease is characterized by prominent intra-hepatic vasoconstriction and increased resistance to blood flow, which contribute to the development of portal hypertension16. In the case of NAFLD, several LSEC-related mechanisms contribute to this phenomenon. For instance, LSEC-specific insulin resistance, as mentioned above, is associated with reduced insulin-dependent vasodilation of the hepatic vasculature13. Besides, over the course of the disease, the liver vasculature becomes more sensitive to vasoconstrictors, further contributing to impairment of the hepatic blood flow and leading to the emergence of shear stress, which both result in a disruption of the sinusoidal microcirculation17. These facts suggest that the vasculature is a key target in liver disease. Nevertheless, limiting factors hindering the timely diagnosis and monitoring of NAFLD/NASH, as well as the development of potential therapies, are the inadequacies in the consistent characterization of the hepatic microenvironment and (micro)vascular structure, as well as the scoring of the disease stage in a spatiotemporal and non-invasive manner.
Micro-computed tomography (CT) imaging is currently the gold-standard non-invasive imaging method for accurately depicting anatomical information within a living organism. Micro-CT and MRI represent two complementary imaging methods that can cover a vast range of pathologies and provide exceptional resolution and detail in the imaged structures and tissues. Micro-CT, in particular, is a very fast and accurate tool that is often used for studying pathologies such as bone diseases and associated bone surface changes18, assessing the progression of pulmonary fibrosis over time19, diagnosing lung cancer and its staging20, or even examining dental pathologies21, without any special preparation (or destruction) of the samples being imaged.
The imaging technology of micro-CT is based on the different attenuation properties of various organs in terms of the interaction of X-rays with matter. Organs presenting high X-ray attenuation differences are depicted with high contrast in CT images (i.e., the lungs appear dark and the bones light). Organs presenting very similar attenuation properties (different soft tissues), are challenging to distinguish on CT images22. To address this limitation, specialized contrast agents based on iodine, gold, and bismuth have been extensively investigated for in vivo use. These agents alter the attenuation properties of the tissues in which they accumulate, are cleared slowly from the circulation, and enable the uniform and stable opacification of the entire vascular system or chosen tissues23.
In human diagnostics, CT imaging and comparable techniques, such as MRI-derived proton density fat fraction, are already in use for the determination of hepatic fat content24,25. In the context of NAFLD, high soft tissue contrast is essential to accurately distinguish pathological lesions or small vessels. For this purpose, contrast agents providing enhanced contrast of the liver tissue characteristics are utilized. Such tools and materials allow for the study of multiple liver characteristics and possible pathology expressions, such as the architecture and density of the vascular network, lipid deposition/steatosis, and functional tissue uptake/lipid (chylomicron) transfer in the liver. Additionally, hepatic relative blood volume and portal vein diameter can also be evaluated. In a very short scan time, all these parameters provide different and complementary information on the evaluation and progression of NAFLD, which can be used to develop a non-invasive and detailed diagnosis.
In this article, we provide a step-by-step protocol for the use of novel in vivo micro-CT imaging techniques as a non-invasive method to assess the progression stages of NAFLD. Using this protocol, the longitudinal analysis of liver steatosis and functional tissue uptake, as well as the evaluation of the relative blood volume, portal vein diameter, and density of the vascular network, can be performed and applied in mouse models of liver disease.
All procedures were carried out by BIOEMTECH's personnel in accordance with European and national welfare regulations and were approved by national authorities (license number EL 25 BIOexp 45/PN 49553 21/01/20). All experiments were designed and reported with adherence to ARRIVE guidelines26. The mice were purchased from the Hellenic Pasteur Institute, Athens, Greece.
NOTE: Animals were group-housed in individually ventilated cages enriched with rails and cardboard tubes in a room at 20-22 °C, with a relative humidity of 50%-60% and a 12 h light/dark cycle (light 07:00 am-07:00 pm). A combination of a high-fat diet (HFD) and high-fructose corn syrup (HFCS), a fructose- and glucose-containing sweetener widely used in modern types of fat-enriched diets, was used to induce NAFLD as a recognized reliable model27,28,29,30. At 7-8 weeks of age, male C57BL/6 mice were given ad libitum access to either a normal diet (n = 2) with 10% of kilocalories from fat or a HFD (n = 2) containing 60% of kilocalories from fat supplemented with 5% HFCS in water for 22 weeks. Body weight was obtained weekly using a digital balance, and during the experimental period, animal welfare was monitored on alternate days using a score sheet. At the end of the imaging protocol, the mice were euthanized via cervical dislocation.
1. Animal preparation
NOTE: The imaging protocol is summarized in Figure 1.
2. Pre-scanning preparation
NOTE: Imaging is performed in two experimental phases to allow for the first contrast agent to be adequately cleared from the circulation and tissues. eXIA (first contrast agent) is administered in the first phase and ExiTron (second contrast agent) in the second phase, as described in the "Imaging workflow" section (section 3) below.
3. Imaging workflow
4. Data extraction and analysis
NOTE: In this protocol, the data extraction and analysis steps based on a specific imaging processing software (see Table of Materials) are provided. The described steps may need to be adapted when using different software.
In this representative study, micro-CT imaging without any contrast agent indicated a higher percentage of liver fat in mice with NAFLD compared to controls (Table 2), confirming the pathology. Using the ExiTron contrast agent and the hepatic vascular network architecture and density analysis described above, the total volume density of the hepatic vascular network was found to be higher in mice with NAFLD compared to healthy controls (Figure 6, Table 2). Mice with NAFLD also had a larger portal vein diameter compared to control mice (Table 2), a structural alteration associated with portal hypertension during liver disease34,36,37. Similarly, the hepatic rBV of animals with NAFLD was calculated to be higher compared to healthy controls (Table 2).
Furthermore, the analysis of the functional tissue uptake assay indicated a higher accumulation and slower clearance of the eXIA contrast agent in mice with NAFLD compared to healthy controls (Figure 7). These results suggest that steatotic hepatocytes likely undergo high levels of cellular endocytosis and distribution, though accompanied by reduced metabolic catabolism or clearance/secretion. Overall, this finding aligns with the phenotype of reduced hepatic metabolic activity, as expected in the case of fatty infiltration/NAFLD38,39.
Figure 1: Schematic depicting an overview of the experimental protocol. Please click here to view a larger version of this figure.
Figure 2: Representative images highlighting the proposed areas used to perform sampling for segmenting the 2D ROI for the liver (red), spleen (green), and WAT (blue). Please click here to view a larger version of this figure.
Figure 3: Representative example of segmenting a 2D ROI for calculating steatosis. (A) The Cross Hair tool is used to select a 2D ROI on a desired area of the liver on the transverse plane. (B) The process is repeated on the sagittal and coronal planes to complete the segmentation of the 2D ROI. Please click here to view a larger version of this figure.
Figure 4: Representative example of a segmentation layer for generating a 2D liver ROI. Central parts of the organ are manually selected, avoiding the border regions to eliminate noise. Please click here to view a larger version of this figure.
Figure 5: 2D axial area. Representative examples of the 2D axial area of the different slices chosen to measure the portal vein diameter in mice with NAFLD and healthy controls. Please click here to view a larger version of this figure.
Figure 6: Hepatic vascular network architecture. Representative extracted images of the hepatic vascular network architecture, as shown through CT segmentation, obtained from a control mouse (176.9 mm3) and a mouse with NAFLD (390.3 mm3). Please click here to view a larger version of this figure.
Figure 7: Average contrast values. Grouped data showing the average contrast values, which represent the hepatic tissue uptake over 48 h post injection of eXIA in mice with NAFLD (n = 2) and healthy controls (n = 2). All grouped data are expressed as mean ± standard deviation. Please click here to view a larger version of this figure.
ExiA | ExiTron | |||
Time Point | Whole Body Scan | Liver Scan | Whole Body Scan | Liver Scan |
Pre-contrast | X | X | X | X |
10 min PI | – | – | – | X |
15 min PI | O | O | – | – |
45 min PI | X | X | – | – |
2 h PI | O | O | – | – |
4 h PI | – | – | X | X |
24 h PI | O | O | – | – |
48 h PI | X | X | – | – |
Table 1: Time points of the CT scans. The appropriate time points of the whole body and liver scans acquired pre- and post-injection (PI) of the contrast agents. X indicates mandatory scans, – indicates no scans, and O indicates optional (recommended but not mandatory) scans.
Control (n = 1–2) | NAFLD (n = 1–2) | |
% Liver fat | 2.4 ± 1.5% | 18.4 ± 3.1% |
Hepatic vascular network volume | 176.9 mm3 | 390.3 mm3 |
Portal vein diameter | 1.1 mm | 1.4 mm |
Hepatic relative blood volume | ~54% | ~79% |
Table 2: Representative results indicating differences in the percentage of liver fat, hepatic vascular network volume, portal vein diameter, and hepatic relative blood volume between mice with NAFLD and healthy controls.
The current recommended method for NAFLD diagnosis and staging in humans is liver biopsy, which harbors the risk of bleeding complexities, as well as sampling inaccuracies40. On the contrary, in animal models, such diagnosis is performed by histology post-mortem, although protocols for survivable liver biopsy are now available and are recommended when the study design allows41. The use of post-mortem histology means that a large number of animals are required to investigate the progression of this disease. As such, a study cannot be performed in the same animal while the disease progresses; variability is also expected to be higher when comparing samples obtained at different time points from different animals. In this article, we provide an innovative, non-invasive in vivo micro-CT approach, applied in an established experimental animal model of NAFLD, that enables the longitudinal evaluation of disease progression through the quantification of functional parameters, namely liver steatosis and functional tissue uptake, the relative blood volume, the portal vein diameter, and the density of the vascular network, in the same animal.
Micro-CT imaging is currently the gold-standard non-invasive imaging method for accurately depicting anatomical information within a living organism. Micro-CT has the capability to reach a high spatial resolution, thus representing a valuable tool for studying very fine details in a vast range of pathologies. Furthermore, it is a fast and reliable tool to study disease progression over time21,22,23,24 by exploiting the intrinsic characteristics of X-rays without interfering with the integrity of the imaged sample. One major advantage of this technique in animal research is the ability to use a combination of selected contrast agents administered without any complicated preparations (non-invasive). This allows for several parameters to be extracted from the same animal scanned longitudinally during the progression of the disease, ensuring maximal output and compliance with the ARRIVE guidelines and the 3Rs26. Furthermore, micro-CT scanners provide high-resolution images in very short acquisition times (with scan durations of just a few minutes or less), with the interpretation of the results in 2D and 3D formats being relatively easy (especially when using user-friendly software, as proposed here).
All the scans described in this protocol were performed on a small rodent CT scanner (see Table of Materials). The CT system performs a spiral scan, and it can provide images with 100 µm resolution. It operates between 35-80 kVp and 10-500 µA tube current. The CT data acquisitions last 7-10 min per scan and are reconstructed through an image space reconstruction algorithm (ISRA) at 100 µm spatial resolution. CT imaging is performed using the following parameters: i) high-resolution protocol at 50 kVp for WB scans and ii) high-resolution multirotation local scan at 50 kVp for local liver scans. All the parameters are set up in the scanning device software (see Table of Materials) provided with the system by following the instructions on the user interface. The reconstruction is performed through a Feldkamp, Davis, and Kress (FDK) algorithm with a voxel size of 0.1 mm. CT artifacts are minimized by periodically calibrating the detectors and maintaining the system well through appropriate services. If artifacts occur, the problematic detector that causes the ring artifact can be remotely canceled and the image corrected.
The described technical protocol was optimized using the eXIA and ExiTron contrast agents, which were selected due to their special formulations and temporal biokinetics in the various tissues. eXIA is a fully biodegradable contrast agent that contains 160 mg/mL iodine as an X-ray attenuating agent. Once injected intravenously, this contrast agent shows the blood residence time (with a clearance half-time of >30 min) and is then taken up by metabolically active organs such as the liver, spleen, myocardium, and brown adipose tissue. The first contrast agent is, therefore, appropriate for the non-invasive in vivo detection of liver and spleen abnormalities, myocardial infarction, and cardiomyopathy, as well as for identifying and quantifying active brown adipose tissue. ExiTron is an alkaline earth metal-based nanoparticle contrast agent of ~12,000 HU undiluted density42, which is specifically formulated for preclinical CT imaging. On intravenous injection, the second contrast agent circulates in the bloodstream, and it is taken up by the cells of the reticuloendothelial system43, including macrophages within the liver.
There are certain limitations associated with the proposed methodology. For this protocol to be successful, no CT signal should be detected from the first contrast agent prior to administering the second contrast agent. The time frame proposed in this protocol was selected following optimization experiments (and based on other studies)44, which suggested that the first contrast agent has slow clearance. As the second contrast agent has an even slower clearance rate45,46, it must be administered second, following the complete clearance of the first contrast agent. Indeed, we have identified the clearance of the first contrast agent to be satisfactory after 12 days of injection. Depending on the duration of the animal model used, this time scale could allow the comparison of two time points at which the liver disease might have progressed. Considering that the feeding protocol used here takes 22 weeks, a time-lapse of 12 days is not expected to cause significant changes in the disease progression. The experimenter is required to perform appropriate validation and optimization before adjusting the proposed imaging protocol. One must also assess the cost-benefit analysis of the progression and image signal before altering the type and concentration of the contrast agents used, as well as the time frame of administration.
Additionally, both contrast agents can only be tolerated up to a specific total volume of administration before reaching toxic levels for the animal43. Due to the fact that a maximal contrast agent volume is required to ensure optimal contrast, in combination with the slow clearance rate of the agents, a one-time injection is suggested for this analysis. Repeated administrations of these or other appropriate alternative contrast agents could also be used for different experiments, as long as the total volume of the contrast agent remains below the recommended limit at any given time point. Another requirement for successful imaging using this micro-CT protocol is the correct administration of the contrast agents. As stated in the protocol, the experimenter should ensure a slow infusion of the agent at the appropriate dosage directly into the bloodstream through the vein, without any bubbles. Failure to do so will compromise the imaging resolution and outputs. Therefore, the selection of an optimal dosage and appropriate administration methods (infusion and duration between different agents) reduces the risk of toxicity and the associated limitations in the CT imaging.
For scanning at multiple time points, attention should be given to keeping the anesthesia duration as short as possible. Since CT scanning only takes a few minutes to complete, the anesthesia can be reversed between some scans to minimize the risk associated with prolonged anesthesia durations. Repeated anesthesia inductions also have risks. However, placing the animals on a heated pad between scans and ensuring sufficient hydration helps with recovery and the maintenance of physiology. Furthermore, the exposure to ionizing radiation emitted by X-rays is adequate to influence organ and cell biology, making this potentially harmful to the animals and, consequently, resulting in biased and misleading experimental data22. As the expected dose to be delivered per scan is around 385 mGy, mice receiving multiple scans during the study can receive up to 1.8 Gy or more. This is a significant radiation dose for mice that could have potentially harmful effects on their tissue biology. This is especially concerning since an increase in dose is required when reducing the isotropic voxel spacing while maintaining the same image quality22.
In terms of image post-processing using the recommended software (see Table of Materials), segmentation masks are created using a mixture of region-growing and thresholding tools, and this is the most time-consuming step of the analysis. In some cases, manual modifications of the obtained segmentations should be carried out using a smoothing method. To optimize the edge-preserving and noise-reduction properties of the desired network, we recommend a Gaussian filter with a value of 0.3. Representative images of such a vascular network are shown in Figure 6 (post-processed using an open-access DICOM medical image viewer). The key limitation in terms of measuring the vascular network is that the software does not have the capability to accurately separate the selected defined ROI (which represents the vascular network of the liver) from the background (which represents the surrounding liver tissue); therefore, the appropriate threshold must be selected through trial and error. Initially, the user defines a lower threshold value of 600 HU and a maximum of 10,000 HU. If the extracted vascular network and the separation from the surrounding tissue are not acceptable, then the lower value is adjusted via trial and error following stepwise changes of 50-100 HU. The process is repeated by the user until the vascular network is sufficiently separated from the tissue.
In conclusion, understanding the adaptations of the hepatic vascular network during NAFLD progression and correlating them with other methods of disease characterization using the proposed method can pave the way towards the establishment of new, more efficient, and reproducible approaches for NAFLD research in mice. This protocol is also expected to upgrade the value of preclinical animal models for investigating the development of novel therapies against disease progression.
The authors have nothing to disclose.
Figure 1 was created with BioRender.com. This work was supported by the Hellenic Foundation for Research and Innovation (#3222 to A.C.). Anna Hadjihambi is funded by The Roger Williams Institute of Hepatology, Foundation for Liver Research.
eXIA160 | Binitio Biomedical, Inc. | https://www.binitio.com/?Page=Products | |
High fat diet with 60% of kilocalories from fat | Research Diets, New Brunswick, NJ, USA | D12492 | |
High-fructose corn syrup | Best flavors, CA | hfcs-1gallon | |
Lacrinorm ophthalmic ointment | Bausch & Lomb | ||
Normal diet with 10% of kilocalories from fat | Research Diets, New Brunswick, NJ, USA | D12450 | |
Viscover ExiTron nano 12000 | Milteny Biotec, Bergisch Gladbach, Germany | 130-095-698 | |
VivoQuant | Invicro | ||
X-CUBE | Molecubes, Belgium | https://www.molecubes.com/systems/ |