Patient-Specific Size and Age Scaling in a Zero Dimensional Cardiovascular Model

Area of Science:

• Physiology
• Biomedical Engineering
• Computational Biology

Background:

• Patient-specific computational cardiovascular models are crucial for clinical applications.
• Physiological variations across individuals necessitate personalized modeling approaches.
• Allometric scaling laws describe how physiological traits change with body size.

Purpose of the Study:

• To advance computational cardiovascular models towards individualization.
• To implement allometric scaling laws based on patient age, weight, height, and sex.
• To test the realism of scaled cardiovascular models across diverse populations.

Main Methods:

• Developed a scaling methodology for the Aplysia Cardiovascular Lab lumped-parameter model.
• Utilized Swedish growth charts for male and female subjects from birth to adulthood.
• Simulated underweight, overweight, and average individuals across a lifespan (birth to 80 years).

Main Results:

• Generated realistic physiological data for diverse patient demographics.
• Model outputs included hemodynamics, cardiac and respiratory function, gas exchange, and energy expenditure.
• Aggregate Z scores demonstrated good agreement with published data for infant, pediatric, and geriatric simulations.

Conclusions:

• Allometric scaling laws effectively generate parameter sets for diverse individuals.
• This methodology enables modeling of varied patient populations.
• The approach supports novel, individualized clinical applications for cardiovascular modeling.