Cardiac malformations are the most common type of birth defect. Improvements in the management of complex congenital heart disease (CHD) have resulted in >90% of those born with CHD now able to survive into early adulthood. In the U.S. alone, there are more adults with CHD (~1 million individuals) than children. Many of these patients are at risk of ventricular dilatation and dysfunction especially those with a functional single ventricle. Predicting those patients who will develop maladaptive remodeling and when is difficult, but there is a wealth of potentially valuable information available in medical images, especially longitudinal MRI exams. The goal of this project is to identify new early markers of compensatory or maladaptive remodeling in CHD patients with single ventricle physiology using atlas-based MR image-derived parametric models of ventricular shape and biomechanics, and to deploy these models and data via the Cardiac Atlas Project (CAP) database. CAP is a worldwide consortium and online resource for integrating and sharing cardiac imaging examinations, together with parametric model-derived functional analyses and associated clinical information. Our multi-disciplinary team of experts in pediatric cardiology, medical imaging, computational modeling and medical informatics aims to extend this resource to patients with CHD and use the models to identify early geometric and biomechanical predictors of maladaptive remodeling and heart failure. The project will develop computational modeling tools to facilitate statistical analysis across population groups of regional heart shape and mechanical characteristics. The models and associated ontological schema will also facilitate data fusion between different imaging protocols and modalities. This project will be a collaboration with iDASH (Integrating Data for Analysis, Anonymization, and Sharing), a National Center for Biological Computing at UCSD, and will use and extend the data-sharing infrastructure developed by iDASH.
The specific aims are: (1) To create a database of 60 single ventricle pathologies including some with longitudinal follow-ups. Existing CAP and iDASH infrastructure will be extended to accommodate longitudinal data from CHD patients, to enable insights into the progression of disease and the onset of failure; (2) To identify shape correlates of mechanical dysfunction in single ventricle CHD by developing atlas-based image- derived statistical models of ventricular geometry, wall motion and changes over time; (3) To use the new atlas-based models of CHD to implement computational simulations of cardiac mechanics and fluid structure interactions in these pathologies to derive potential early markers of maladaptive remodeling. This work will have a significant impact on congenital cardiology by providing non-invasive analyses of regional shape, mechanics and bloodflow. If successful, the requirement for additional invasive procedures, which have increased risk of adverse events, could be substantially reduced. A web-accessible database will also facilitate education and training in cardiology, radiology, physiology and computational biology.

Public Health Relevance

Although surgical and other treatments for congenital heart disease have improved, there is a critical need for enhanced assessment and prediction of adverse conditions in these patients. This proposal will build on an existing technology for developing and deploying a web accessible biomechanical atlas of the heart with congenital disease for clinical and research purposes. This resource will help accelerate the translation of clinical and basic research into improved strategies for patient-specific and disease- specific care.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
5R01HL121754-04
Application #
9198566
Study Section
Modeling and Analysis of Biological Systems Study Section (MABS)
Program Officer
Burns, Kristin
Project Start
2014-01-01
Project End
2017-12-31
Budget Start
2017-01-01
Budget End
2017-12-31
Support Year
4
Fiscal Year
2017
Total Cost
$461,722
Indirect Cost
$134,303
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
Suinesiaputra, Avan; Ablin, Pierre; Alba, Xenia et al. (2018) Statistical shape modeling of the left ventricle: myocardial infarct classification challenge. IEEE J Biomed Health Inform 22:503-515
Gilbert, K; Pontre, B; Occleshaw, C J et al. (2018) 4D modelling for rapid assessment of biventricular function in congenital heart disease. Int J Cardiovasc Imaging 34:407-417
Gilbert, Kathleen; Forsch, Nickolas; Hegde, Sanjeet et al. (2018) Atlas-Based Computational Analysis of Heart Shape and Function in Congenital Heart Disease. J Cardiovasc Transl Res 11:123-132
Suinesiaputra, Avan; Sanghvi, Mihir M; Aung, Nay et al. (2018) Fully-automated left ventricular mass and volume MRI analysis in the UK Biobank population cohort: evaluation of initial results. Int J Cardiovasc Imaging 34:281-291
Timmermann, Viviane; Dejgaard, Lars A; Haugaa, Kristina H et al. (2017) An integrative appraisal of mechano-electric feedback mechanisms in the heart. Prog Biophys Mol Biol 130:404-417
Piras, Paolo; Teresi, Luciano; Puddu, Paolo Emilio et al. (2017) Morphologically normalized left ventricular motion indicators from MRI feature tracking characterize myocardial infarction. Sci Rep 7:12259
Zhang, Xingyu; Medrano-Gracia, Pau; Ambale-Venkatesh, Bharath et al. (2017) Orthogonal decomposition of left ventricular remodeling in myocardial infarction. Gigascience 6:1-15
Gilbert, K; Lam, H-I; Pontré, B et al. (2017) An interactive tool for rapid biventricular analysis of congenital heart disease. Clin Physiol Funct Imaging 37:413-420
Pontre, Beau; Cowan, Brett R; DiBella, Edward et al. (2017) An Open Benchmark Challenge for Motion Correction of Myocardial Perfusion MRI. IEEE J Biomed Health Inform 21:1315-1326
Herum, Kate M; Lunde, Ida G; McCulloch, Andrew D et al. (2017) The Soft- and Hard-Heartedness of Cardiac Fibroblasts: Mechanotransduction Signaling Pathways in Fibrosis of the Heart. J Clin Med 6:

Showing the most recent 10 out of 36 publications