Validation performance comparison for finite element models of the human brain.

Area of Science:

• Biomechanics
• Computational Neuroscience
• Medical Imaging

Background:

• Finite element (FE) models are crucial for simulating brain injury.
• Validating these models against experimental data is essential for accuracy.
• Comparing different FE models aids in selecting the most reliable ones.

Purpose of the Study:

• To compare the performance of six validated brain finite element (FE) models.
• To evaluate model accuracy against localized brain motion validation data.
• To assess model robustness across diverse experimental configurations.

Main Methods:

• Utilized six validated brain finite element (FE) models.
• Employed five distinct experimental configurations for validation.
• Measured model performance using the Correlation and Analysis (CORA) metric.

Main Results:

• The KTH model achieved the highest average CORA rating.
• The ABM model received the highest average rating for cadaver impact validation.
• Performance varied across models and experimental setups.

Conclusions:

• The KTH and ABM models demonstrate strong performance in brain motion simulation.
• The CORA metric provides an objective measure for inter-model comparison.
• FE model validation techniques are vital for advancing computational biomechanics.