An Introductory Overview of Image-Based Computational Modeling in Personalized Cardiovascular Medicine

Area of Science:

• Biomedical Engineering
• Computational Medicine
• Cardiovascular Research

Background:

• Cardiovascular diseases are the leading global cause of death, with limited understanding of underlying mechanisms.
• Current diagnostic and treatment testing methods are often invasive, hindering patient-specific research.
• Advancements in biomedical imaging and computer simulations enable new non-invasive approaches.

Purpose of the Study:

• To review the state-of-the-art and limitations of image-based modeling (IBM) in cardiovascular medicine.
• To explore the application of IBM for personalized cardiovascular investigations and treatments.
• To provide an accessible overview of IBM methods for a broader audience.

Main Methods:

• Discussion of three core physics models: electrophysiology, biomechanics, and hemodynamics within cardiovascular IBM.
• Review of imaging methods used to derive cardiac anatomy for patient-specific models.
• Explanation of the relationship between imaging data and modeling algorithms.

Main Results:

• IBM integrates imaging data with physics-based models for comprehensive cardiovascular analysis.
• The review covers the fundamental aspects of modeling approaches for accessibility.
• Identifies current limitations and areas for future development in cardiovascular IBM.

Conclusions:

• Image-based modeling holds significant potential to revolutionize non-invasive cardiovascular diagnosis.
• IBM facilitates virtual design and testing of treatments and assistive devices.
• Future evolution of IBM methods promises deeper insights into cardiovascular diseases.