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Related Experiment Video

Updated: Aug 29, 2025

An In Vitro 3D Model and Computational Pipeline to Quantify the Vasculogenic Potential of iPSC-Derived Endothelial Progenitors

An In Vitro 3D Model and Computational Pipeline to Quantify the Vasculogenic Potential of iPSC-Derived Endothelial Progenitors

Published on: May 13, 2019

An analysis modality for vascular structures combining tissue-clearing technology and topological data analysis.

Kei Takahashi¹, Ko Abe², Shimpei I Kubota¹

¹Department of Molecular Pathology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan.

Nature Communications

|September 12, 2022

Summary

This summary is machine-generated.

This study introduces Clear, Unobstructed Brain/body Imaging Cocktails and Computational Analysis (CUBIC) for high-resolution 3D imaging of mouse vasculature. CUBIC effectively visualizes and analyzes blood and lymphatic networks, aiding disease model studies.

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Three-dimensional Reconstruction of the Vascular Architecture of the Passive CLARITY-cleared Mouse Ovary

Three-dimensional Reconstruction of the Vascular Architecture of the Passive CLARITY-cleared Mouse Ovary

Published on: December 10, 2017

Related Experiment Videos

Last Updated: Aug 29, 2025

An In Vitro 3D Model and Computational Pipeline to Quantify the Vasculogenic Potential of iPSC-Derived Endothelial Progenitors

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Published on: May 13, 2019

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Published on: March 29, 2018

Three-dimensional Reconstruction of the Vascular Architecture of the Passive CLARITY-cleared Mouse Ovary

Three-dimensional Reconstruction of the Vascular Architecture of the Passive CLARITY-cleared Mouse Ovary

Published on: December 10, 2017

Area of Science:

Vascular Biology
Biomedical Imaging
Computational Biology

Background:

Understanding blood and lymphatic vasculature in mice is limited by current imaging and quantification methods.
High-resolution visualization of complex vascular networks remains a challenge.

Purpose of the Study:

To evaluate the utility of tissue-clearing technology, specifically CUBIC, for visualizing adult mouse vasculature.
To assess CUBIC's capability in analyzing vascular structures using advanced computational methods.

Main Methods:

Utilized Clear, Unobstructed Brain/body Imaging Cocktails and Computational Analysis (CUBIC) for high-resolution 3D imaging.
Employed machine learning for signal classification and topological data analysis with non-homogeneous Poisson process models for geometric feature extraction.
Applied the methodology to mouse disease models to evaluate vascular structural differences.

Main Results:

CUBIC enabled clear, high-resolution 3D imaging of organ-specific vascular structures.
Machine learning and mathematical frameworks successfully extracted geometric features from vascular images.
Structural differences in vasculature were effectively evaluated in mouse disease models.

Conclusions:

CUBIC is a valuable tool for the analysis of vascular structures.
This approach, combining 3D imaging with mathematical frameworks, shows feasibility for future vascular research.