Mechanical circulatory support is required by a large percentage of patients who undergo heart transplant and serves as a destination therapy for end-stage heart failure patients who are ineligible for transplant. However, clinicians are currently unable to predict the up to 40% of patients who develop right heart failure after receiving left ventricular assist devices. If identified pre-operatively, these patients could receive planned biventricular support which has been shown to improve outcomes. Unfortunately, pre-operative hemodynamic parameters, echocardiographic measures, and clinical risk scores have shown limited effectiveness in identifying these patients. The hypothesis of this project is that load-independent measures of ventricular function and assessment of ventricular-arterial coupling are necessary to improve prediction of right heart function and failure in patients receiving left ventricular assist devices. To investigate this hypothesis, we will develop and validate novel CT-based techniques which allow for comprehensive and simultaneous assessment of the right ventricle and pulmonary arteries in a single heartbeat. By acquiring these novel measures along with gold-standard estimates in clinical patients, we will validate whether measures of ventricular-arterial coupling can be obtained with cineCT. Furthermore, acquiring multi-modality images in clinical patients undergoing left ventricular assist device implantation will allow for assessment of whether measures of ventricular-arterial coupling provide clinically predictive information regarding post-implantation right ventricular function (and failure). The proposal includes a training plan designed to address gaps in the applicant?s technical and professional experiences and help launch his independent research career. Specifically, the training includes: didactic coursework in biostatistics, patient-oriented research, and grant writing, training in navigating the academic work environment, mentorship in multi-modality imaging and pulmonary vascular physiology, clinical exposure to the management and treatment of heart failure patients, exposure to potential graduate students through teaching of imaging-focused coursework, and increased exposure to the international research community via publications and attendance and presentations at annual meetings. UC San Diego is the optimal environment for this award. In addition to support by world-class facilities and collaborators in the Bioengineering, Radiology, and Cardiology departments, the applicant and research proposal will have a very high probability of success given the benefit of and access to campus-wide resources such as the Altman Clinical and Translational Research Institute and Institute for Engineering in Medicine.

Public Health Relevance

Although mechanical circulatory support is required by a large percentage of patients who undergo heart transplant and serves as a destination therapy for end-stage heart failure patients who are ineligible for transplant, clinicians are currently unable to predict which patients will develop right heart failure after receiving left ventricular assist devices. We hypothesize that abnormal right ventricular-pulmonary arterial coupling represents a sensitive and specific parameter defining those patients whose right ventricle would fail following insertion of a left ventricular assist device and in this research, we seek to develop and validate novel CT- based measures of right ventricular and pulmonary vascular function such that right ventricular-pulmonary arterial coupling can be measured in a single heartbeat. We will assess whether these advanced measures of function predict post-LVAD right heart function and can identify patients who will develop right ventricular failure so that that biventricular assistance can be provided earlier to patients.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Scientist Development Award - Research & Training (K01)
Project #
5K01HL143113-02
Application #
9748935
Study Section
Special Emphasis Panel (ZHL1)
Program Officer
Wang, Wayne C
Project Start
2018-08-01
Project End
2023-07-31
Budget Start
2019-08-01
Budget End
2020-07-31
Support Year
2
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of California, San Diego
Department
Engineering (All Types)
Type
Schools of Arts and Sciences
DUNS #
804355790
City
La Jolla
State
CA
Country
United States
Zip Code
92093