Ιδρυματικό Αποθετήριο [SANDBOX]
Πολυτεχνείο Κρήτης
EN  |  EL

Αναζήτηση

Πλοήγηση

Ο Χώρος μου

A glycolysis-based In silico model for the solid tumor growth

Zervakis Michalis, Michail Kounelakis, Maria Papadogiorgaki, Panagiotis Koliou

Πλήρης Εγγραφή


URI: http://purl.tuc.gr/dl/dias/BCB92A51-4ADE-4980-BE56-1B720BA02637
Έτος 2014
Τύπος Δημοσίευση σε Περιοδικό με Κριτές
Άδεια Χρήσης
Λεπτομέρειες
Βιβλιογραφική Αναφορά M. Papadogiorgaki, M. Kounelakis, P. Koliou, M. Zervakis ,"A glycolysis based in-silico model for the solid tumor growth ,"Biom. and Health Infor.,vol19.no.3,pp.1106 - 1117,2014.doi:10.1109/JBHI.2014.2356254 https://doi.org/10.1109/JBHI.2014.2356254
Εμφανίζεται στις Συλλογές

Περίληψη

Cancer-tumor growth is a complex process depending on several biological factors, such as the chemical microenvironment of the tumor, the cellular metabolic profile, and its proliferation rate. Several mathematical models have been developed for identifying the interactions between tumor cells and tissue microenvironment, since they play an important role in tumor formation and progression. Toward this direction we propose a new continuum model of avascular glioma-tumor growth, which incorporates a new factor, namely, the glycolytic potential of cancer cells, to express the interactions of three different tumor-cell populations (proliferative, hypoxic, and necrotic) with their tissue microenvironment. The glycolytic potential engages three vital nutrients, i.e., oxygen, glucose, and lactate, which provide cells with the necessary energy for their survival and proliferation. Extensive simulations are performed for different evolution times and various proliferation rates, in order to investigate how the tumor growth is affected. According to medical experts, the experimental observations indicate that the model predicts quite satisfactorily the overall tumor growth as well as the expansion of each region separately. Following extensive evaluation, the proposed model may provide an essential tool for patient-specific tumor simulation and reliable prediction of glioma spatiotemporal expansion.

Υπηρεσίες

Στατιστικά