A Computational Patient-Specific Model of Impella Support for Cardiogenic Shock

Principal Investigator: Farhad R. Nezami

Authors: Farhad R. Nezami, Farhan Khodaee, Zhongwei Qi, Scott. Corbett, Steven P. Keller, Elazer R. Edelman
Lay Abstract

Cardiogenic shock, most frequently caused by acute myocardial infarction (AKA heart attack), is a condition in which cardiac output is inadequate resulting in compromised blood supply for vital organs. An increasingly common treatment method is to augment/replace cardiac functionality via implantation of a ventricular assist device (VAD). One type of VAD, rotary blood pumps, has gained particular popularity due to its small size and longer operation lifetime. These temporary mechanical circulatory support devices employ a small rotating impeller to sustain partial blood flow until cardiac recovery occurs or a more permanent treatment can be implemented. By maintaining flow even under complete heart failure conditions, blood pumps sustain end-organ perfusion and prevent stagnation in the ventricles, reducing the likelihood of clot formation. Computational fluid dynamics (CFD) offers a powerful methodology with which to examine interactions between blood and VADs such as the Impella. In contrast to benchtop or animal experiments, CFD elicits results quickly and at low cost, enabling a variety of conditions and metrics to be evaluated in detail. This work examines the performance of Impella within a patient-specific aortic model to delineate how varying working condition of Impella may modulate vascular hemodynamics and biological responses.

Scientific Abstract

Inadequate cardiac output for patients with cardiogenic shock leads to hypoperfusion of the vital organs. Though percutaneous ventricular assist devices (PVAD) such as the Impella increasingly provide circulatory support, understanding of their hemodynamic impact remains limited. A patient-specific computational model of aorta flow with Impella support was developed. Physiologically validated aortic waveforms were used for virtual implantation of catheter, impeller, and surrounding cage. Total perfusion was set to 5 LPM while varying relative heart failure with progressively reduced native flow including fraction of Impella CP flow: 0 (baseline, without Impella), 30 and 70%. Hemodynamic patterns were captured solving for the turbulent flow and quantifiable features including velocity, turbulent kinetic energy, shear stress metrics, and vital organs perfusion. Aortic flow during Impella support demonstrated greater vorticity and turbulent energy with increasing PVAD support. End-organ perfusion was maintained in all scenarios even when flow became less pulsatile with increasing Impella contribution. Impella-induced flow alterations increased shear stress within the ascending aorta commensurate with that reported for other circulatory support devices. Our results illuminate the unique potential of computational approaches for mechanistic understanding and risk stratification of mechanical support therapies and demonstrated flow and perfusion patterns with support under different heart failure states.

Clinical Implications
Our research reveals the immense potential of computational approaches for mechanistic understanding of interplay between mechanical support devices and cardiovascular systems. Such engineering tools will enhance risk stratification and clinical decision making in associated therapies and reduce adverse clinical events.

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