Effective Diffusion and Tortuosity in Brain White Matter.

Area of Science:

• Biomedical Engineering
• Computational Neuroscience
• Medical Physics

Background:

• Glioblastomas have poor patient survival rates.
• Convection-enhanced delivery (CED) shows promise but requires complex models.
• Accurate simulation parameters, like tortuosity, are challenging to estimate.

Purpose of the Study:

• To propose a novel method for computing tortuosity in fibrous tissue.
• To model white matter geometry for improved simulation accuracy.
• To enhance the effectiveness of drug delivery techniques like CED.

Main Methods:

• Developed a computational model incorporating white matter's geometric features.
• Calculated tortuosity based on varying extracellular space widths.
• Validated results against existing experimental data.

Main Results:

• Tortuosity was computed using a new method.
• A decrease in extracellular space width led to an increase in tortuosity (from 1.35 to 1.85).
• The model's predictions align well with literature-reported experimental data.

Conclusions:

• The proposed method accurately computes tortuosity, a key parameter for drug diffusion.
• Understanding tortuosity's relationship with extracellular space is vital for glioblastoma treatment modeling.
• This work contributes to more effective numerical simulations for advanced therapies.