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 Concept Videos

Brain Imaging01:14

Brain Imaging

Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic Stimulation (TMS).

You might also read

Related Articles

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

Sort by
Same author

Molecular dynamics simulation of high slip flow of water confined between graphene nanochannels at experimentally accessible shear rates.

The Journal of chemical physics·2026
Same author

Vacuum-Laser Fabrication of Programmable Soft Actuators.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)·2026
Same author

Low Arrhythmic Risk in Individuals With Brugada ECG Pattern and a Negative dST-Tiso Criterion.

The American journal of cardiology·2026
Same author

First-Principles Models of Triboelectrification.

Small methods·2026
Same author

A machine learning model for assessing fetal health during pregnancy.

Frontiers in bioengineering and biotechnology·2026
Same author

Electrically Tunable Friction through Surface Adsorption Layer Restructuring.

ACS applied materials & interfaces·2025
Same journal

Effect of muscle atrophy on fracture healing: insights from a tibial musculoskeletal-finite element model.

Biomechanics and modeling in mechanobiology·2026
Same journal

A multi-fidelity poroelastic finite element and machine learning framework for characterizing respiratory mechanics in porcine lungs.

Biomechanics and modeling in mechanobiology·2026
Same journal

Mechanics and mechanobiology of arterial development.

Biomechanics and modeling in mechanobiology·2026
Same journal

Mechanics-driven emergence of mesenchymal migration features.

Biomechanics and modeling in mechanobiology·2026
Same journal

Parameter estimation in blood flow models from highly undersampled k-space magnetic resonance imaging data.

Biomechanics and modeling in mechanobiology·2026
Same journal

Integrating serial block-face SEM with voxel-based finite element analysis for high-fidelity micromechanical modelling of anisotropic soft tissues: application to human dermis.

Biomechanics and modeling in mechanobiology·2026
See all related articles

Related Experiment Video

Updated: Jun 19, 2026

Targeting Neuronal Fiber Tracts for Deep Brain Stimulation Therapy Using Interactive, Patient-Specific Models
14:14

Targeting Neuronal Fiber Tracts for Deep Brain Stimulation Therapy Using Interactive, Patient-Specific Models

Published on: August 12, 2018

9.4K

Models and tissue mimics for brain shift simulations.

Antonio E Forte1, Stefano Galvan2, Daniele Dini2

  • 1Department of Mechanical Engineering, Imperial College London, London, SW7 2AZ, UK. antonio.forte10@imperial.ac.uk.

Biomechanics and Modeling in Mechanobiology
|September 8, 2017
PubMed
Summary
This summary is machine-generated.

Accurate brain shift prediction is crucial for neurosurgery. This study developed a numerical model using a hydrogel tissue mimic, validating a hybrid poro-hyper-viscoelastic formulation for improved surgical accuracy.

Keywords:
BiomechanicsBrain phantomBrain tissueFE modellingImage-guided surgerySoft tissue

More Related Videos

A MRI-Based Toolbox for Neurosurgical Planning in Nonhuman Primates
08:41

A MRI-Based Toolbox for Neurosurgical Planning in Nonhuman Primates

Published on: July 17, 2020

5.4K
Patient-Specific Polyvinyl Alcohol Phantom Fabrication with Ultrasound and X-Ray Contrast for Brain Tumor Surgery Planning
08:41

Patient-Specific Polyvinyl Alcohol Phantom Fabrication with Ultrasound and X-Ray Contrast for Brain Tumor Surgery Planning

Published on: July 14, 2020

9.1K

Related Experiment Videos

Last Updated: Jun 19, 2026

Targeting Neuronal Fiber Tracts for Deep Brain Stimulation Therapy Using Interactive, Patient-Specific Models
14:14

Targeting Neuronal Fiber Tracts for Deep Brain Stimulation Therapy Using Interactive, Patient-Specific Models

Published on: August 12, 2018

9.4K
A MRI-Based Toolbox for Neurosurgical Planning in Nonhuman Primates
08:41

A MRI-Based Toolbox for Neurosurgical Planning in Nonhuman Primates

Published on: July 17, 2020

5.4K
Patient-Specific Polyvinyl Alcohol Phantom Fabrication with Ultrasound and X-Ray Contrast for Brain Tumor Surgery Planning
08:41

Patient-Specific Polyvinyl Alcohol Phantom Fabrication with Ultrasound and X-Ray Contrast for Brain Tumor Surgery Planning

Published on: July 14, 2020

9.1K

Area of Science:

  • Biomedical Engineering
  • Computational Mechanics
  • Neurosurgery

Background:

  • Brain shift, the deformation of brain tissue during surgery, poses risks.
  • Accurate prediction is vital for enhancing surgical precision and patient safety.

Purpose of the Study:

  • To develop and validate an accurate numerical model for predicting brain shift.
  • To evaluate constitutive models for simulating complex brain tissue behavior.

Main Methods:

  • Development of a composite hydrogel tissue mimic with realistic mechanical properties.
  • Utilizing MRI scans for 3D deformation measurements of a brain-skull mimic.
  • Evaluating various constitutive laws for numerical simulation.

Main Results:

  • The hydrogel mimic accurately reproduced brain tissue's dynamic mechanical behavior.
  • A hybrid poro-hyper-viscoelastic material formulation showed promise for brain shift simulation.
  • Accurate constitutive laws are essential for modeling this complex tissue.

Conclusions:

  • The developed numerical model and material formulation can improve brain shift prediction.
  • This approach offers a controlled environment to study brain deformation, reducing confounding factors.
  • Findings support the use of advanced constitutive models for safer neurosurgical interventions.