Imaging-based characterization of convective tissue properties.

Area of Science:

• Biomedical Engineering
• Pharmacokinetics
• Nanomedicine

Background:

• Convective transport is crucial for nanomedicine delivery, but traditional pharmacokinetic models lack spatial detail.
• Classical compartmental models assume spatially invariant mass transport, failing to capture convection-dependent phenomena.
• Parameters from existing models may not directly reflect convective transport dynamics in tissues.

Purpose of the Study:

• To develop and validate an imaging-based approach for directly measuring tissue permeability relevant to nanomedicine accumulation.
• To provide an alternative framework for parameterizing mathematical models in nanomedicine treatment planning.
• To investigate the correlation between the proposed method and established models.

Main Methods:

• An imaging-based framework was developed to measure tissue properties, specifically permeability in the context of Darcy flow.
• Measurements were compared against an extended Tofts model as a control.
• A pixel-wise iterative clustering algorithm was employed to reduce the parameter space of the acquired measurements.

Main Results:

• The proposed imaging approach directly measures tissue permeability, offering insights into nanoparticle transport.
• Measurements obtained from the new method showed a significant correlation with those from the extended Tofts model.
• The pixel-wise clustering algorithm effectively reduced the dimensionality of the measurement data.

Conclusions:

• The developed imaging approach provides a direct measure of tissue permeability relevant to convective transport in nanomedicine.
• The findings suggest this method can yield information comparable to established compartmental models.
• This approach offers a valuable alternative framework for parameterizing models in nanomedicine, particularly for convection-dominated scenarios.