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David A. Nordsletten

Publications and source records attributed to David A. Nordsletten.

2 recordsLinked to original sources

Comprehensive Analysis of Relative Pressure Estimation in Type B Aortic Dissection Utilizing 4D-Flow MRI

Magnetic resonance imaging (MRI) can estimate three-dimensional (3D) time-resolved blood velocity fields using 4D-flow MRI, providing rich relative pressure field information. Clinical alternatives---catheterization and Doppler echocardiography---provide one-dimensional pressure drops. While the accuracy of one-dimensional pressure drops from 4D-flow has been explored, the accuracy of 3D relative pressure field estimates requires further evaluation. This work analyzes three state-of-the-art relative pressure estimators: virtual Work-Energy Relative Pressure (vWERP), the Pressure Poisson Estimator (PPE), and the Stokes Estimator (STE). Spatiotemporal characteristics and noise sensitivity were determined in silico via comparison with CFD-derived relative pressure fields. Estimators were then validated using a type B aortic dissection (TBAD) flow phantom with varying tear geometry and twelve catheter pressure measurements. Finally, each estimator was evaluated across eight patient cases in a clinical feasibility analysis. Estimators were cross-compared and evaluated for coherence since no reference catheter pressure measurements were available. PPE outperformed STE in the in silico relative pressure analysis, while both outperformed vWERP in plane-to-plane assessment. High velocity gradients and low spatial resolution contributed most significantly to local variations in 3D relative pressure field errors. Low temporal resolution led to systematic underestimation of highly transient peak pressure events. In the flow phantom analysis, vWERP was the most accurate method, followed by STE and then PPE. Each relative pressure estimator was strongly correlated with ground truth relative pressure values, despite the tendency to underestimate peak relative pressure. Patient case results demonstrated that each relative pressure estimator could be feasibly integrated into a clinical workflow.

physics.flu-dyn↗

In Silico Evaluation of Cardiac Tissue-Engineered Patch Interventions

Myocardial infarction significantly degrades heart function, and current treatments can bring forth serious cost and complications including blood clots and infections. To improve the current state of treatment, researchers are developing tissue patches from induced-pluripotent stem cells that can be incorporated into the heart, improving organ function after a myocardial infarction. These tissue patches include surface patches, attached to the epicardium of the heart, and thick transmural patches that replace the infarcted region. However, little is known about the impact of cardiac tissue patches on pump function in a patient's heart. In addition, it is not clear what patch structural properties - such as active stress generation, muscle fiber alignment, or material stiffness - may best augment existing heart tissue. Computational modeling can be used to examine different implementations and patch properties, illuminating the mechanical impact of cardiac tissue patches in the beating heart. In this work, we computationally implement different cardiac tissue patches to understand benefits of particular patch types and properties. We find that in transmural cardiac tissue patches, both activation and fiber alignment improve function. A transmural patch generating 10% of healthy active stress can increase stroke volume by 18%, and higher generated active stress in a circumferential muscle fiber orientation can recover stroke volume by over 50%. Furthermore, we find that surface cardiac tissue patches can enhance heart function slightly despite limiting diastolic filling, especially when fibrotic thinning has occurred. These conclusions identify broad design goals for the engineering of cardiac tissue patches to improve heart function after a myocardial infarction.

physics.med-ph↗