Is MRI-based CFD able to improve clinical treatment of coarctations of aorta?

Area of Science:

• Cardiovascular Medicine
• Biomedical Engineering
• Medical Imaging

Background:

• Coarctation of the aorta (CoA) presents long-term challenges despite surgical or stent interventions due to altered hemodynamics.
• Image-based computational fluid dynamics (CFD) offers potential for improved diagnosis and treatment planning in CoA.

Purpose of the Study:

• To evaluate the efficacy of CFD in improving aortic hemodynamics for coarctation of the aorta (CoA) patients.
• To compare pre- and post-treatment hemodynamics with virtual treatment simulations.

Main Methods:

• Utilized MRI and angiography data for 13 CoA patients to create patient-specific CFD models.
• Employed ZIBAmira for segmentation and geometry reconstruction, and ANSYS Fluent for simulating peak systole flow conditions.
• Compared pre-treatment, post-treatment, and virtual treatment hemodynamics, including pressure drop and wall shear stress (WSS).

Main Results:

• Virtual CFD treatment significantly reduced pressure drop by a mean of 2.8 ± 3.15 mmHg compared to post-treatment values.
• Mean wall shear stress (WSS) was significantly reduced by 3.8 Pa following virtual treatment.
• MRI-based CFD demonstrated potential for optimizing hemodynamics, specifically reducing pressure drop and improving WSS at the stenosis segment.

Conclusions:

• CFD modeling shows significant potential to improve post-treatment hemodynamics in coarctation of the aorta (CoA) patients.
• Optimizing pressure drop through CFD-guided virtual treatment can lead to substantial reductions in wall shear stress (WSS).
• This approach may enhance long-term prognosis for patients with coarctation of the aorta.