Computer Modeling of Congenital Heart Disease

The research proposed here is motivated by the need to support pediatric cardiologists in making image-based decisions in the assessment and management of congenital heart disease (CHD). In marked contrast to adult cardiology, which deals almost exclusively with the left ventricle (LV), the function of the RV is associated with a number of life-threatening conditions in pediatrics. These defects include Hypoplastic Left Heart Syndrome (HLHS), Congenitally Corrected Transposition of Great Arteries, Post operative Tetralogy of Fallot, and Double Outlet Right Ventricle.

In particular, a computer model that simulates both the myocardium and blood pool of the right ventricle (RV) is being investigated that can be used to measure clinically useful but diverse parameters of RV blood flow and wall behaviors that previously would require multiple analysis tools to acquire. The model is based on data from MRI studies of patients. Alternate measurement techniques such as ultrasound and catheter pressure measurements are needed to verify the efficacy of the model.

Through a retrospective chart review of CHD patients with defects associated with RV dysfunction, data will be obtained from CHOA over a five year period, June 1, 2001 through May 31, 2006. It will be collected from 10 children aged 0-18 years. Magnetic Resonance images, Ultrasound and catheterization measurements will be collected and analyzed.

Data from MR will be used primarily to determine RV volumetric data. This information will be used to determine RV shape at the different stages of systole and through diastole. The RV shapes are the input to the computer model. The computer model will determine relevant clinical measures such as ejection fraction, pressure measurements, strain rate, and wall thickening based solely on the MR image data. The ultrasound and catheter data will be used as independent sources of verification against the data determined from the computer model. Ultrasound data will be used to compare ejection fraction and wall behavior to the predictive model and catheter data will be used to compare pressure measurements.