Computational Methods for Identifying Hypertrophic Cardiomyopathy using 12-lead ECG

Hypertrophic cardiomyopathy (HCM) is a cardiovascular disease where the heart muscle is partially thickened and blood flow is - potentially fatally - obstructed. It is one of the leading causes of sudden cardiac death in young people. Electrocardiography (ECG) and Echocardiography (Echo) are the standard tests for identifying HCM and other cardiac abnormalities. The American Heart Association has recommended using a pre-participation questionnaire for young athletes instead of ECG or Echo tests due to considerations of cost and time involved in interpreting the results of these tests by an expert cardiologist. Initially we set out to develop a classifier for automated prediction of young athletes’ heart conditions based on the answers to the questionnaire. Classification results and further in-depth analysis using computational and statistical methods indicated significant shortcomings of the questionnaire in predicting cardiac abnormalities. Automated methods for analyzing ECG signals can help reduce cost and save time in the pre-participation screening process by detecting HCM and other cardiac abnormalities. Therefore, the main goal of this dissertation work is to identify HCM through computational analysis of 12-lead ECG. ECG signals recorded on one or two leads have been analyzed in the past for classifying individual heartbeats into different types of arrhythmia as annotated primarily in the MIT-BIH database. In contrast, we classify complete sequences of 12-lead ECGs to assign patients into two groups: HCM vs. non-HCM. The challenges and issues we address include missing ECG waves in one or more leads and the dimensionality of a large feature-set. We address these by proposing imputation and feature-selection methods. We develop heartbeat-classifiers by employing Random Forests and Support Vector Machines, and propose a method to classify full 12-lead ECGs based on the proportion of heartbeats classified as HCM. The results from our experiments show that the classifiers developed using our methods perform well in identifying HCM. Thus the two contributions of this thesis are the utilization of computational and statistical methods for discovering shortcomings in a current screening procedure and the development of methods to identify HCM through computational analysis of 12-lead ECG signals.

p53 Regulates the Formation of Lamellipodia and Circular Dorsal Ruffles Through Caldesmon and PTEN

Vascular smooth muscle cell migration is a significant contributor to many aspects of heart disease, and specifically atherosclerosis. Tissue damage in the arteries can result in the formation of a fatty streak. Smooth muscle cells (SMC) can then migrate to this site to form a fibrous cap, stabilizing the fatty plaque. Since cardiovascular disease is the leading cause of death in developed countries, this function of SMC is an essential area of study. The formation of lamellipodia and circular dorsal ruffles were studied in this project as indicators that cell migration is occurring. The roles of the proteins p53, Rac, caldesmon and PTEN were investigated with regards to these actin-based structures. The tumour suppressor p53 is often reported to cause apoptosis, senescence or cell cycle arrest when stress is placed on a cell, but has recently been shown to regulate cell migration as well. It was determined in this project that p53 could inhibit the formation of both lamellipodia and circular dorsal ruffles. It was also shown that this could occur directly through an inhibition of the GTPase Rac. Previous studies have shown that p53 can upregulate caldesmon, a protein which is known to bind to and stabilize actin filaments while inhibiting Arp2/3-mediated branching. It was confirmed that p53 could upregulate caldesmon, and that caldesmon could inhibit the formation of lamellipodia and circular dorsal ruffles. The phosphorylation of caldesmon by p21-associated kinase (PAK) or extracellular signal-related kinase (Erk) was shown to effectively reverse the ability of caldesmon to inhibit these structures. The role of phosphatase and tensin homologue deleted on chromosome 10 (PTEN) was also studied with regards to this signalling pathway. PTEN was shown to inhibit lamellipodia and circular dorsal ruffles through its lipid phosphatase activity. It was concluded that p53 can inhibit the formation of lamellipodia and circular dorsal ruffles in vascular SMC, and that this occurs through Rac, caldesmon and PTEN.