3D simulation of scar formation post myocardial infarction using CT images
BACKGROUND: Myocardial infarction is a major contributor to death and disability worldwide. The key to reducing the devastating effects of myocardial infarction is to better understand the effects of the scar formations in the anterior left ventricle wall of the heart, and to one day restrict scar tissue growth. This study develops a method for simulating scar tissue growth post myocardial infarction on computed tomography (CT) heart images.
METHODS: In order to simulate scar tissue formations, I used CT images of mouse hearts and imported them into Slicer, a C++ coded, NIH-funded software designed for processing medical images in research studies. Canny edge detection was performed to segment the left ventricular wall and measure its thickness. A module was designed inside the Slicer frame work that outputs a series of images displaying scar tissue growth on the left ventricle based on user input of scar location and maximum size. These images were then displayed in a time simulation based on a nonlinear growth rate function derived from experimental data.
RESULTS: Binary threshold. Outside threshold, and Canny edge detection filters successfully segmented the wall of the left ventricle and measured its length. The module developed in Slicer demonstrated the ability to generate 3D images of scar tissue growth in the left ventricle. The scar growth was measured and found to be comparable to the input value for scar sizes smaller than thickness of the wall of the left ventricle. These images were displayed in a time simulation that matched an experimentally derived function for scar tissue growth rate.