Non-Invasive Mapping of Intraventricular Flow Patterns in Patients Treated with Left Ventricular Assist Devices

ORAL

Abstract

In heart failure patients, left ventricular (LV) assist devices (LVADs) decrease mortality and improve quality of life. We hypothesize echo color Doppler velocimetry (echo-CDV), an echocardiographic flow mapping modality, can non-invasively characterize the effect of LVAD support, optimize the device, thereby decreasing the stoke rate present in these patients. We used echo-CDV to image LV flow at baseline LVAD speed and during a ramp test in LVAD patients (Heartmate II, N$=$10). We tracked diastolic vortices and mapped blood stasis and cumulative shear. Compared to dilated cardiomyopathy (DCM) patients without LVADs, the flow had a less prominent diastolic vortex ring, and transited directly from mitral valve to cannula. Residence time and shear were significantly lower compared to healthy controls and DCMs. Aortic regurgitation and a large LV vortex presence or a direct mitral jet towards the cannula affected blood stasis region location and size. Flow patterns, residence time and shear depended on LV geometry, valve function and LVAD speed in a patient specific manner. This new methodology could be used with standard echo, hemodynamics and clinical information to find the flow optimizing LAVD setting minimizing stasis for each patient.

Authors

  • Marissa Miramontes

    Mechanical Engineering, UCSD

  • Lorenzo Rossini

    Mechanical Engineering, UCSD

  • Oscar Braun

    UCSD Medical Center

  • Michela Brambatti

    UCSD Medical Center

  • Shone Almeida

    UCSD Medical Center

  • Adam Mizeracki

    UCSD Medical Center

  • Pablo Martinez-Legazpi

    Hospital Gregorio Marañón

  • Yolanda Benito

    Hospital Gregorio Marañón

  • Javier Bermejo

    Hospital Gregorio Marañón

  • Andrew Kahn

    University of California, San Diego, UCSD Medical Center, UCSD

  • Eric Adler

    UCSD Medical Center

  • Juan C. del Álamo

    University of California at San Diego, Mechanical Engineering, UCSD