Unit:
Τομέας Βασικών Ιατρικών ΕπιστημώνLibrary of the School of Health Sciences
Author:
Iliopoulou Ioanna
Dissertation committee:
Κωνσταντίνος Πάντος, Αναπληρωτής Καθηγητής, Ιατρική Σχολή, ΕΚΠΑ, Επιβλέπων
Ευάγγελος Γεωργίου, Καθηγητής, Ιατρική Σχολή, ΕΚΠΑ
Ιορδάνης Μουρούζης, Επίκουρος Καθηγητής, Ιατρική Σχολή, ΕΚΠΑ
Δημήτριος Κουτσούρης, Καθηγητής, Σχολή Ηλεκτρολόγων Μηχανικών, Τμήμα Βιοϊατρικής Μηχανικής, Εθνικό Μετσόβιο Πολυτεχνείο
Πέτρος Καρακίτσος, Καθηγητής, Ιατρική Σχολή, ΕΚΠΑ
Γρηγόριος Σιβολαπενκο, Καθηγητής, Τμήμα Φαρμακευτικής, Πανεπιστήμιο Πατρών
Αικατερίνη Τυλιγάδα, Αναπληρώτρια Καθηγήτρια, Ιατρική Σχολή, ΕΚΠΑ
Original Title:
Υπολογιστική μοντελοποίηση της ιστικής επιδιόρθωσης μετά από έμφραγμα του μυοκαρδίου σε πειραματόζωα
Translated title:
Computational modelling of cardiac tissue repair after induced myocardial infraction in animals
Summary:
Cardiovascular disease is one of the leading causes of death in the western world.
Respectively, a great part of research focuses on the disease prognosis, diagnosis and
treatment of cardiovascular disease. In particular, research has focused on the
cardiovascular disease in men since they have dismal prognosis when compared to
women. During research for cardiovascular disease and myocardial infarction, it has been
observed that patients that received thyroxine replacement therapy had better prognosis
as compared to patients that did not. Based on this observation, the question that came up
was whether thyroxine supplementation could be used as a complementary treatment in
the treatment of cardiovascular disease and myocardial infarction.
The present work deals with this subject by using an in vivo model. This model utilized a
rat experimental model where wistar rats have undergone surgical infarction and at the
same time thyroxine was provided as supplemental treatment. Collected data have been
analyzed with classical statistical methods as well as we have implemented machine
learning algorithms such as hierarchical clustering, k-means and neural networks, in order
to discover novel mechanistic roles of thyroxine in myocardial infarction.
To the best of our knowledge this is a novel project, since studies on this subject are
scarse. The expected results from our study is a more in-depth understanding of the role
of thyroxine in cardiovascular disease and myocardial infarction.
In the present study, we have attempted to create a novel in vivo model for the
investigation of thyroxine and myocardial infarction. Factors studied included, thyroxine
administration, operation type (sham operation) and coronary artery ligation (CAL) and
time, since mice were studied for a total period of 2, 4 and 13 weeks. Our results showed
that thyroxine has beneficial inpact on the mechanical and hemodynamical properties of
the cardiac muscle. In particular, it appeared that scar size and scar weight were
successfully fitted with respect to end-diastolic and end-systolic diameters, wall tension
index and sphericity index. We were able to confirm our results with numerous methods
since both the classical as well as machine learning methodologies lead us to similar
conclusions.
Further studies are required in order to gain more knowledge on the topic of the role of
thyroxine in myocardial infarction.
Keywords:
Cardiac Tissue Repair, Myocardial Infraction, Computational Modelling, Thyroxine
Number of index pages:
17
