The influence of optimization target selection on the structure of arterial tree models generated by constrained...

Area of Science:

• Computational biology
• Biomedical engineering
• Mathematical modeling

Background:

• Understanding the complex branching structures of arteries is crucial for studying blood flow and cardiovascular health.
• Previous models often simplify arterial geometry, limiting their ability to capture intricate physiological behaviors.

Purpose of the Study:

• To investigate how different optimization target functions influence the structural characteristics of computationally generated arterial models.
• To quantify and explain the relationship between optimization objectives and resulting arterial tree morphology.

Main Methods:

• Employed a constrained constructive optimization method to generate arterial models.
• Utilized a parameterized family of target functions to systematically alter optimization goals.
• Analyzed structural differences using numerical indexes, including blood transport path length and pressure profiles.

Main Results:

• Demonstrated that varying the target function leads to visually and quantitatively distinct arterial tree structures.
• Identified clear dependencies of blood transport path length, pressure profile, and segment orientation on the chosen optimization target.
• Provided theoretical explanations for the observed structural changes.

Conclusions:

• The computational method effectively generates diverse arterial models by adjusting optimization targets.
• Optimization objectives significantly dictate arterial morphology, impacting key hemodynamic parameters.
• This approach offers a valuable tool for exploring the principles governing vascular network development and function.