Computational modeling of flow-altering surgeries in basilar aneurysms

Area of Science:

• Biomedical Engineering
• Medical Imaging
• Fluid Dynamics

Background:

• Pathological basilar artery hemodynamics pose challenges for surgical interventions.
• Accurate prediction of postoperative flow is crucial for clinical decision-making.

Purpose of the Study:

• To evaluate the utility of image-based computational fluid dynamics (CFD) models in predicting postoperative hemodynamics for basilar artery aneurysms.
• To assess the potential of CFD simulations in guiding surgical interventions for flow alterations.

Main Methods:

• Patient-specific CFD models were created using MR angiography and velocimetry data.
• Simulations were performed for preoperative and postoperative scenarios, including virtual contrast transport.
• Models were validated against in vivo 4D Flow MRI measurements and postoperative imaging data.

Main Results:

• CFD predictions showed close agreement with MR imaging data.
• Simulations helped identify interventions that could reduce aneurysm flow while maintaining basilar trunk flow.
• The models estimated the likelihood of intra-aneurysmal thrombus deposition.

Conclusions:

• Image-based CFD modeling is a valuable tool for guiding clinical decisions in basilar artery aneurysm interventions.
• This approach can predict potential complications and assess the success of surgical options prior to procedures.