Towards non-invasive computational-mechanics and imaging-based diagnostic framework for personalized cardiology for coarctation

Area of Science:

• Cardiovascular Science
• Biomedical Engineering
• Medical Imaging

Background:

• Coarctation of the aorta (COA) is a congenital narrowing of the descending aorta.
• Accurate diagnosis of COA relies on precise blood flow quantification, which is currently limited by underdeveloped fluid-dynamics methods.
• COA diagnosis requires assessing both local blood flow dynamics and global hemodynamics due to the heart's interaction with the vascular network.

Purpose of the Study:

• To develop a novel, fast, computational-mechanics and imaging-based framework for non-invasive COA diagnosis.
• To enable accurate quantification of local and global hemodynamics for COA patients.
• To provide new diagnostic analyses beyond conventional methods.

Main Methods:

• Developed a framework integrating the Lattice Boltzmann method and lumped-parameter modeling.
• Utilized routine, non-invasive clinical patient data.
• Validated the framework against clinical cardiac catheterization, finite-volume method calculations, and Doppler echocardiography.

Main Results:

• The framework successfully quantifies local and global hemodynamics in COA.
• Demonstrated the ability to provide diagnostic information not achievable with current methods.
• Validation confirmed the framework's accuracy against established clinical and computational techniques.

Conclusions:

• The developed framework offers a powerful tool for non-invasive COA diagnosis.
• This approach can significantly improve clinical outcomes, risk assessment, and treatment planning for COA patients.
• The integration of computational mechanics and imaging provides a new paradigm for diagnosing complex cardiovascular conditions.