Utility of Computational Modeling in Reassessing the Threshold for Intervention and Progression into Type A Aortic...

Area of Science:

• Cardiovascular Surgery
• Biomedical Engineering
• Medical Imaging

Background:

• Early assessment of aortic dissection (AD) is critical for cardiovascular surgeons.
• Current diagnostics for type A AD rely on CT scans measuring aortic diameter.
• Improved diagnostic thresholds are needed to predict AD progression and surgical complications.

Purpose of the Study:

• To enhance type A AD diagnosis by correlating hemodynamic factors with aortic diameter growth.
• To utilize computational fluid dynamics (CFD) to analyze wall shear stress (WSS) in predicting AD progression.
• To reassess current diameter-based diagnostic criteria for AD using CFD insights.

Main Methods:

• Converted pre- and post-AD CT scan data from 15 patients into 3D geometries.
• Employed a transitional-turbulent CFD model to analyze wall shear stress (WSS) and its derivatives.
• Compared WSS parameters and pressure gradients across patient groups based on annual aortic diameter growth.

Main Results:

• Group 1 (normal diagnosis) showed pre-AD time-average WSS (TAWSS) of 2-4 Pa, dropping post-AD (<1.5 Pa) with elevated oscillatory shear index (OSI).
• Group 2 (abnormal diagnosis) exhibited post-AD TAWSS <3 Pa and OSI 0.1-0.31 near tear sites.
• A dual-risk profile was identified: low TAWSS promotes thrombosis, high TAWSS drives dissection progression.

Conclusions:

• WSS parameters (TAWSS, OSI) can assess ascending aorta dilation, particularly with extreme aortic diameters.
• Pre-AD analysis indicated high shear stress in the true lumen correlates with a diastolic pressure drop post-AD.
• CFD modeling offers a novel approach to predict AD progression and refine diagnostic criteria.