Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Modelling liver tissue properties using a non-linear visco-elastic model for surgery simulation.

Jean-Marc Schwartz1, Marc Denninger, Denis Rancourt

  • 1Computer Vision and Systems Laboratory, Department of Electrical Engineering, Laval University, Que., Canada G1K 7P4.

Medical Image Analysis
|February 22, 2005
PubMed
Summary

This study presents a new computational method for simulating soft tissue mechanics, crucial for planning liver cancer surgery. The advanced model accurately captures non-linear and visco-elastic behaviors, outperforming simpler linear models in simulations.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Transcriptome-driven constraint-based modelling reveals metabolic targets for ovarian cancer.

Cancer & metabolism·2026
Same author

Human pluripotent stem cell model of multiple epiphyseal dysplasia with MATN3 mutation identifies altered matrix organisation and upregulation of the cholesterol biosynthesis pathway.

Osteoarthritis and cartilage·2026
Same author

Building basement membranes with computational approaches.

Matrix biology : journal of the International Society for Matrix Biology·2025
Same author

From Discovery to Delivery: A Rapid and Targeted Proteomics Workflow for Monitoring Chinese Hamster Ovary Biomanufacturing.

Molecular & cellular proteomics : MCP·2025
Same author

Exploring focal adhesion data: dynamic parameter extraction from FRAP and FLAP experiments using chemical master equation.

Frontiers in molecular biosciences·2025
Same author

Flux Sampling Suggests Metabolic Signatures of High Antibody-Producing CHO Cells.

Biotechnology and bioengineering·2025

Area of Science:

  • Computational mechanics
  • Biomedical engineering
  • Surgical simulation

Background:

  • Accurate modeling of biological soft tissue mechanics is essential for surgical planning, particularly for liver cancer treatments.
  • Linear elasticity is insufficient for capturing the complex mechanical properties of biological tissues.
  • Existing simulation methods may not meet the real-time computational demands of percutaneous surgery simulation.

Purpose of the Study:

  • To develop an extended tensor-mass method for fast computation of non-linear and visco-elastic mechanical forces and deformations.
  • To create a simulation tool for planning cryogenic surgical treatment of liver cancer.
  • To validate the model's accuracy in simulating soft tissue behavior during needle insertion.

Main Methods:

Related Experiment Videos

  • Extension of the linear elastic tensor-mass method to incorporate non-linear and visco-elastic properties.
  • Development of a computational model for simulating soft tissue mechanical responses.
  • Experimental characterization of deer liver tissue mechanical properties using a biopsy needle perforation setup.

    • Main Results:

    • The proposed model successfully simulates diverse non-linear and visco-elastic mechanical behaviors at real-time compatible speeds.
    • Experimental data confirmed that linear models are inadequate for simulating needle-tissue interactions.
    • The developed model accurately predicted the axial load experienced by the needle during liver tissue perforation.

    Conclusions:

    • The enhanced tensor-mass method provides a fast and accurate approach for simulating soft tissue mechanics.
    • This simulation tool holds significant potential for improving the planning and execution of liver cancer surgeries.
    • The model's ability to capture complex material behaviors is critical for realistic surgical simulations.