Congenital heart disease (CHD) affects approximately 1.2% of children and is the leading cause of birth defect- related deaths. Single ventricle heart disease (SVHD) is a severe form of CHD, with high morbidity and mortality. These patients require multiple palliative surgeries, culminating with a total cavopulmonary anastomosis. Despite considerable improvement in the survival of patients with SVHD, there is increasing morbidity and mortality over time. It remains unclear why some SVHD patients fail their surgical repairs while others remain relatively well. Clinicians often rely on 2-dimensional (2D) images acquired from echocardiograms, catheterizations, or cardiovascular magnetic resonance (CMR) exams to assess SVHD patients and qualitatively choose the optimal surgical repair. The 2D images, however, lead to a suboptimal understanding of the complex 3D spatial relationships and hemodynamics, and limit efficient decision making. To address this deficiency, a free-breathing sequence is developed to acquire 3D cine CMR images of the heart and great vessels in 10 minutes. The 3D block of data will be used to generate a patient-specific pulsatile heart model. This heart model will be used to simulate the patient cardiovascular system with a lumped- parameter model. The lumped-parameter model will be used to simulate different surgical repairs and quantitatively choose the most optimal repair for each patient. We expect that this platform rationalizes surgeons' decisions for the best surgical approach and improves the survival rate of patients with SVHD.

Public Health Relevance

We seek to understand why some children with single ventricle heart disease fail after surgical procedures. Currently, images from echocardiography, catheterizations, and cardiovascular magnetic resonance are being used to qualitatively choose the best surgical approach for these patients. In this project, we aim to quantitatively determine the most optimal surgical repair for each patient by simulating different surgical repairs and comparing the post-surgical hemodynamics.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
1R01HL149807-01
Application #
9861910
Study Section
Imaging Guided Interventions and Surgery Study Section (IGIS)
Program Officer
Evans, Frank
Project Start
2020-01-03
Project End
2024-11-30
Budget Start
2020-01-03
Budget End
2020-11-30
Support Year
1
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Boston Children's Hospital
Department
Type
DUNS #
076593722
City
Boston
State
MA
Country
United States
Zip Code
02115