Novel In Vivo Micro-Computed Tomography Imaging Techniques for Assessing the Progression of Non-Alcoholic Fatty Liver Disease
March 24th, 2023
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.
We consider this protocol significant because it demonstrates a non-invasive simple and easy method to assess over time key indicators for the diagnosis of liver disease. This imaging methodology allows for analysis over time of liver statuses, evaluation of the relative blood volume, portal vein diameter, intensity of the vascular network, all important parameters of liver pathology. Understanding the adaptations of the hepatic vascular network during NAFLD progression and correlating this with specific markers such as steatosis, inflammation, and fibrosis can help establish new efficient therapy schemes.
This technique aids in the identification of such markers and also upgrades the value of mice in preclinical studies focusing on the development of novel therapies against disease progression. To begin, place the anesthetized animal in the CT scanner cradle. Apply ophthalmic ointment, secure the nose cone, and set the scanning parameters on the CT scanner.
Prepare the tail vein catheter and place the mouse on a bed to warm the tail in warm water. Insert the catheter into the tail vein and administer the first contrast agent via an injection, performed slowly and manually with a duration of one to three minutes. Then, acquire whole body and liver scans at different time points.
Follow the same procedure for the administration of the second contrast agent, 10 days following the final reading with the first contrast agent. After loading the DICOM file of the pre-contrast scan, adjust the contrast to see the liver, spleen, and white adipose tissue clearly. Under the 3D ROI tool, select add ROI to generate multiple ROIs to perform sampling in the areas where the liver, spleen, and adipose tissue appear clear with no apparent blood vessels and fat.
Under paint mode, choose Sphere. Tick the box 2D only and select a diameter of eight pixels from the dropdown menu to paint ROI over data. From the erode dilate feature, choose minus one erode.
Perform sampling by segmenting the 2D ROIs on the areas of interest using the Sphere tool on the transverse plane. Go to navigation and select show table to display the quantification table containing the calculated hounds field unit values for each ROI. Then, plug the values into this equation.
Calculate the percentage of liver fat. Load the eXIA scan DICOM file, and adjust the contrast to see the liver, spleen, and left ventricle clearly. Under the 3D ROI tool, select add ROI to segment multiple ROIS for the liver.
Under paint mode, select 2D only, and choose Sphere add a diameter of eight pixels to paint ROI over data. From the erode dilate feature, choose minus one erode. Specify a name and color for each ROI and select show table to display the quantification table containing the calculated HU values for each ROI.
After repeating these steps to obtain PV organ t0, insert the values into the equation shown on the screen to extract the percentage contrast corresponding to the functional tissue uptake lipid transfer. Load the ExiTron scan DICOM file, and adjust the contrast to see the liver vascular network clearly. Select add ROI to generate a 3D ROI for the liver.
Define the liver ROI by marking the desired area. Then choose the background ROI from the ROI selector. Click on the Perform Cut icon, to remove the background without changing the liver ROI.
Activate the maximum intensity projection viewer. Then, under segmentation algorithms denoted by the magic wand icon, select connected thresholding to resegment the liver ROI. Set the thresholds by entering the minimum and maximum values and obtain the vascular network.
Again, remove the background liver tissue to get a clear representation of the vascular network. After loading the ExiTron scan DICOM file, adjust the contrast to see the liver, spleen, and left ventricle clearly. Select add ROI and segment ROIs for the liver and a large blood vessel.
Define the segmentation layers to generate 2D ROIs for each tissue. Repeat the steps for the pre-contrast DICOM file to obtain the mean brightness of the liver before the contrast agent injection. For the portal vein diameter, locate the transversal planes of three to four slices above the junction of the superior mesenteric and splenic veins, and then go to navigation followed by distance sanitation, select line to measure the exact distance between two points.
The average contrast values are presented by this grouped data. The functional tissue uptake assay indicated a higher accumulation and slower clearance of the eXIA contrast agent in mice with non-alcoholic fatty liver disease compared to healthy controls. These representative results indicate the differences in the percentage of liver fat, hepatic vascular network volume, portal vein diameter, and hepatic relative blood volume between mice with non-alcoholic fatty liver disease and healthy controls.
Micro-CT imaging with without any contrast agent, indicated a higher percentage of liver fat in mice with non-alcoholic fatty liver disease compared to controls. Similarly, a higher hepatic vascular network volume, hepatic relative blood volume, and a larger portal vein diameter were found in mice with non-alcoholic fatty liver disease compared to healthy controls. The most important thing to remember while attempting this technique is to constantly be accurate on the anatomical region selected.
Choosing the wrong anatomical spot can lead in non accurate results. By following this methodology and protocol, an accurate evaluation of liver disease staging can be performed. Thus, it can act as a specified platform for evaluating new drug efficiency.
This technique paves the way for new, easier, and more accurate ways to evaluate liver pathologies and initiate relevant drug development assays.
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Overview
This study investigates a novel non-invasive micro-computed tomography (micro-CT) imaging technique to monitor the progression of non-alcoholic fatty liver disease (NAFLD) in a diet-induced mouse model. The method focuses on analyzing the hepatic vascular network, a key factor in liver disease dysregulation.
Key Study Components
Research Area
- Non-alcoholic fatty liver disease (NAFLD)
- Micro-computed tomography imaging
- Hepatic vascular network analysis
Background
- NAFLD is a common liver condition associated with various metabolic disorders.
- Understanding liver vascular changes is critical for assessing disease progression.
- Current methods for evaluating liver disease often lack non-invasive approaches.
Methods Used
- In vivo micro-CT imaging techniques
- Diet-induced NAFLD mouse model
- Contrast agents to visualize liver pathology
Main Results
- Identified changes in hepatic vascular network volume and portal vein diameter.
- Correlation established between liver fat percentage and vascular characteristics.
- Demonstrated feasibility of using micro-CT for long-term liver disease assessment.
Conclusions
- The study validates a non-invasive imaging method for monitoring NAFLD progression.
- Findings may contribute to the development of new therapeutic strategies.
Frequently Asked Questions
Executive Industry Relevance
Non-invasive in vivo micro-CT imaging of NAFLD progression in preclinical models addresses a critical gap in longitudinal, quantitative assessment of hepatic pathology. This approach enables high-resolution, reproducible measurement of vascular and tissue changes, supporting predictive confidence in early-stage drug discovery and translational research. Integrating these imaging outputs into the discovery pipeline enhances decision-making for therapeutic hypothesis testing and candidate triage.
Strategic Applications in Biopharma R&D
Early Discovery & Target Validation
- Enables quantitative interrogation of hepatic vascular adaptations linked to NAFLD progression.
- Supports biological de-risking by correlating vascular metrics with steatosis, inflammation, and fibrosis markers.
- Facilitates functional target validation through non-invasive, longitudinal monitoring in disease-relevant models.
- Improves predictive confidence for advancing therapeutic hypotheses targeting liver pathology.
Screening & Assay Development
- Provides standardized, reproducible imaging outputs for evaluating compound effects on liver structure and function.
- Enables assay development with quantitative readouts such as liver fat percentage and vascular network density.
- Supports scalability and platform reuse across preclinical NAFLD studies.
- Enhances screening readiness by enabling reliable, non-terminal assessment of disease progression.
Translational & Preclinical Research
- Aligns preclinical imaging biomarkers with disease-relevant endpoints for translational continuity.
- Enables risk-adjusted advancement decisions by providing objective, quantitative disease staging data.
- Facilitates evaluation of therapeutic efficacy in longitudinal studies without repeated animal sacrifice.
- Supports mechanistic de-risking by linking imaging outputs to functional tissue uptake and vascular remodeling.
Pipeline & Workflow Integration
This imaging protocol integrates into the discovery continuum from early target validation through preclinical candidate evaluation in NAFLD models.
- Discovery Biology: Supports hypothesis testing and pathway clarification by quantifying hepatic vascular and tissue changes.
- Screening: Delivers reproducible, quantitative imaging outputs for compound evaluation and assay standardization.
- Analytics: Provides statistical measurements of liver fat, vascular network volume, and portal vein diameter for condition comparison.
- Translational Research: Bridges preclinical findings to clinical endpoints by aligning imaging biomarkers with disease progression.
- Enterprise Reuse: Establishes a reusable imaging platform for diverse NAFLD-focused R&D programs.
Operational & Enterprise Impact
- Scientific Value: Increases predictive confidence and reduces mechanistic ambiguity in NAFLD target validation.
- Operational Value: Standardizes non-invasive, longitudinal assessment for reproducibility and scalability.
- Strategic Value: Enables better go/no-go decisions and capital efficiency by providing objective disease staging data.
- Portfolio Impact: Supports risk-adjusted prioritization and advancement of NAFLD therapeutic candidates.
Implementation Considerations
- Requires expertise in small animal imaging and hepatic disease modeling.
- Demands access to micro-CT instrumentation and advanced image analysis software.
- Necessitates cross-team standardization of anatomical region selection and ROI segmentation.
- Adaptation across different preclinical models may require protocol optimization.
- Accuracy depends on precise anatomical targeting and consistent imaging parameters.
Biopharma FAQs
Chapters in this video
0:04
Introduction
1:06
Animal Preparation and Imaging Workflow
2:02
Evaluation of Hepatic Lipid Deposition/Steatosis
3:21
Functional Tissue Uptake/Lipid (Chylomicron) Transfer in the Liver
4:27
Architecture and Density of the Hepatic Vascular Network
5:32
Hepatic Relative Blood Volume
6:33
Results: Average Contrast Values and the Micro‐CT Imaging in Mice with NAFLD and Healthy Controls
7:50
Conclusion
