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Related Experiment Video

Updated: Oct 10, 2025

A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells

A Method for 3D Reconstruction and Virtual Reality Analysis of Glial and Neuronal Cells

Published on: September 28, 2019

Deciphering tumour tissue organization by 3D electron microscopy and machine learning.

Baudouin Denis de Senneville^1,2, Fatma Zohra Khoubai³, Marc Bevilacqua⁴

¹CNRS, University of Bordeaux, "Institut de Mathématiques de Bordeaux" (IMB), UMR5251, 351 cours Libération, F-33400, Talence, France.

Communications Biology

|December 14, 2021

Summary

This study reveals key 3D bioarchitectural parameters in childhood hepatoblastoma tumors. Understanding tumor cell size, blood vessel connections, and bile canaliculus-like structures aids future onconanotomy research.

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Published on: August 16, 2020

Area of Science:

Oncology
Bioengineering
Microscopy

Background:

Tumor 3D organization and architectural parameters remain poorly understood.
Hepatoblastoma is the most common childhood liver cancer.

Purpose of the Study:

To analyze the spatial and 3D organization of hepatoblastoma patient-derived xenograft tissues.
To identify bioarchitectural parameters influencing tumor internal architecture.

Main Methods:

Serial block-face scanning electron microscopy for 3D imaging.
Integrated workflow: 3D imaging, segmentation (manual & machine learning), mathematics, infographics.
Digital reconstitution of entire hepatoblastoma samples, including cells, organelles, and vasculature.

Main Results:

Hepatoblastoma cell size correlates with nucleus, cytoplasm, and mitochondrial mass.
Anatomical connections observed between blood capillaries and tumor cell planar alignment/size.
Tumor cells showed polarization towards a bile canaliculus-like structure.

Conclusions:

Identified novel bioarchitectural parameters shaping tumor internal and spatial organization.
This pilot study provides a foundation for the emerging field of onconanotomy.
Highlights the importance of 3D ultrastructural analysis in cancer research.