Methods for characterizing human coronary artery deformation from cardiac-gated computed tomography data

Area of Science:

• Biomedical Engineering
• Medical Imaging
• Cardiovascular Research

Background:

• Accurate quantification of coronary artery dynamics is crucial for effective coronary stent design.
• Cardiac motion significantly alters vessel geometry, posing challenges for device development.
• Existing methods may not fully capture the complex 3D deformations of coronary arteries.

Purpose of the Study:

• To develop and validate novel computational methods for quantifying dynamic changes in human coronary arteries.
• To enable precise measurement of length, curvature, and bifurcation angles under cardiac motion.
• To provide data for improving the design and performance prediction of coronary stents.

Main Methods:

• Utilized cardiac-gated computed tomography (CT) data to reconstruct 3D coronary artery geometry and centerlines.
• Developed 3D distortion-free vessel straightening and landmark matching for strain and twisting quantification.
• Employed best-fit torus computation for bending deformation analysis and linear fitting for bifurcation angle measurement.

Main Results:

• Successfully quantified dynamic vascular deformations, including strain, twisting, and bending.
• Verified the proposed methods using a software phantom and applied them to patient-specific CT datasets.
• Demonstrated the ability to measure changes in curvature and bifurcation angles.

Conclusions:

• The developed methods provide accurate quantification of coronary artery deformations during cardiac motion.
• These findings can inform the design of more realistic bench-top tests for endovascular devices.
• Improved in vivo environment replication will lead to better device performance prediction and more durable stent designs.