3d Liver Analysis
3d Liver Analysis - Related Videos
12:39
DUCT: Double Resin Casting followed by Micro-Computed Tomography for 3D Liver Analysis
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Cited by 2 •
2021
Double resin casting micro-computed tomography, or DUCT, enables visualization, digitalization, and segmentation of two tubular systems simultaneously to facilitate 3D analysis of organ architecture. DUCT combines ex vivo injection of two radiopaque resins followed by micro-computed tomography scanning and segmentation of the tomographic data.
06:42
Cerebrovascular Casting of the Adult Mouse for 3D Imaging and Morphological Analysis
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Cited by 29 •
2011
In this article, we present a simple, practical technique for cerebrovascular casting that is easy to perform and can be utilized to image the vascular tree of the adult mouse brain.
09:27
Analysis of Liver Microenvironment During Early Progression of Non-Alcoholic Fatty Liver Disease-Associated Hepatocellular Carcinoma in Zebrafish
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Cited by 8 •
2021
Here, we present how to generate a non-alcoholic fatty liver disease (NAFLD)-associated Hepatocellular Carcinoma (HCC) zebrafish model to study the impact of cholesterol surplus on liver microenvironment and immune cell landscape.
12:35
In vivo Liver Endocytosis Followed by Purification of Liver Cells by Liver Perfusion
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Cited by 14 •
2011
The study of liver sinusoidal endothelial cells (SECs) must be performed with primary cells obtained from the animal as no cell lines exist. This method relies on liver digestion and differential centrifugation for SEC purification for subsequent culturing and experimentation.
05:37
A 3D Quantification Technique for Liver Fat Fraction Distribution Analysis Using Dixon Magnetic Resonance Imaging
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Cited by 1 •
2023
This study introduces a unique 3D quantification method for liver fat fraction (LFF) distribution using Dixon Magnetic Resonance Imaging (Dixon MRI). LFF maps, derived from in-phase and water-phase images, are integrated with 3D liver contours to differentiate LFF patterns between normal and steatotic livers, enabling precise assessment of liver fat content.
FAQs
By representing the liver as a volume rather than as separate two-dimensional views, the analysis retains the spatial relationships among tissue regions, lesions, and blood vessels. Computational reconstruction allows these structures to be examined together, so their location and organization remain part of the assessment. This perspective can reveal disease-related patterns or anatomical details that individual planar images may not fully convey.
Segmentation separates relevant anatomical or pathological regions within reconstructed liver data, while quantitative measurements assign numerical descriptions to those regions. Together, these steps turn visual information into analyzable features such as lesion characteristics, vessel structure, fibrosis, or regional tissue volume. The resulting measurements support systematic characterization of liver structure and disease-related change.
Lesions, blood vessels, fibrosis, and regional tissue volume are important targets because they represent different aspects of liver anatomy, tissue organization, or pathology. Examining them within the same three-dimensional framework can connect localized abnormalities with surrounding structures and regional variation. This combined view helps characterize disease patterns without reducing the assessment to a single feature or isolated image.
The workflow begins by reconstructing liver anatomy from imaging data. Computational segmentation then identifies relevant structures or regions, followed by quantitative measurements of features such as lesions, vessels, fibrosis, or regional tissue volume. Interpreting these measurements in their preserved spatial context allows investigators to assess anatomical organization and disease-related changes for medical evaluation or research.
Clinicians may use the approach for noninvasive assessment of liver disease, tumor characterization, surgical planning, and evaluation of treatment response. Its volumetric perspective helps relate abnormalities to surrounding anatomy, which is particularly relevant when understanding lesion location or regional tissue organization. These capabilities can support more informed assessment of hepatic pathology and decisions involving planned interventions.
By quantifying structure and preserving relationships among regions, lesions, and vessels, 3D liver analysis can contribute to disease modeling and more precise investigation of hepatic pathology. Regional tissue measurements also provide a way to examine variation across the organ rather than treating it as uniform. This supports research focused on how structural changes relate to liver disease and function.