MRI-Based Computational Fluid Dynamics for Diagnosis and Treatment Prediction: Clinical Validation Study in Patients With Coarctation of Aorta

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Abstract

Purpose:

To reduce the need for diagnostic catheterization and optimize treatment in a variety of congenital heart diseases, magnetic resonance imaging (MRI)-based computational fluid dynamics (CFD) is proposed. However, data about the accuracy of CFD in a clinical context are still sparse. To fill this gap, this study compares MRI-based CFD to catheterization in the coarctation of aorta (CoA) setting.

Materials and Methods:

Thirteen patients with CoA were investigated by routine MRI prior to catheterization. 3D whole-heart MRI was used to reconstruct geometries and 4D flow-sensitive phase-contrast MRI was used to acquire flows. Peak systolic flows were simulated using the program FLUENT.

Results:

Peak systolic pressure drops in CoA measured by catheterization and CFD correlated significantly for both pre- and posttreatment measurements (pre: r = 0.98, p = 0.00; post: r = 0.87, p = 0.00). The pretreatment bias was −0.5 ± 3.33 mmHg (95% confidence interval −2.55 to 1.47 mmHg). CFD predicted a reduction of the peak systolic pressure drop after treatment that ranged from 17.6 ± 5.56 mmHg to 6.7 ± 5.58 mmHg. The posttreatment bias was 3.0 ± 2.91 mmHg (95% CI −1.74 to 5.43 mmHg).

Conclusion:

Peak systolic pressure drops can be reliably calculated using MRI-based CFD in a clinical setting. Therefore, CFD might be an attractive noninvasive alternative to diagnostic catheterization.

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