Διδακτορικές Διατριβές

Μόνιμο URI για αυτήν τη συλλογήhttps://dspace.library.tuc.gr/handle/123456789/48

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Πλοήγηση Διδακτορικές Διατριβές ανά Συγγραφέα "Θεοδωρόπουλος Παναγιώτης"

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    In vivo molecular imaging of epithelial pre-cancers based on dynamic optical scattering modeling
    (Technical University of Crete, 2014) Papoutsoglou Georgios; Παπουτσογλου Γεωργιος; Balas Costas; Μπαλας Κωστας; Papageorgiou Markos; Παπαγεωργιου Μαρκος; Kalaitzakis Kostas; Καλαϊτζακης Κωστας; Stavrakakis Georgios; Σταυρακακης Γεωργιος; Zervakis Michalis; Ζερβακης Μιχαλης
    We present a novel biophotonic method and imaging modality for estimating and mapping neoplasia-specific functional and structural parameters of the cervical precancerous epithelium. Estimations were based on experimental data obtained from dynamic contrast-enhanced optical imaging of cervix, in vivo. The dynamic characteristics of the measured optical signal are governed by the epithelial transport effects of the biomarker. A compartmental, pharmacokinetic, model of the cervical neoplastic epithelium has been developed, which predicts the dynamic optical effects in all possible parameter value combinations. Nine biological parameters, both structural and func-tional, have been identified to be potentially correlated with the neoplasia growth and to be mani-fested to the measured data in a convoluted manner. We have performed Global Sensitivity Analy-sis for the purpose of identifying the subset of the input parameters that are the key determinants of the model’s output. We have for the first time shown that it is possible to estimate, from in vivo measured dynamic optical data, the following neoplasia related parameters: number of neoplastic layers, extracellular space dimensions, functionality of tight junctions and extracellular pH. Global optimization techniques showed that the estimations of our method are of adequate accuracy and precision. Particularly, the Differential Evolution algorithm converged to the set of the four, most identifiable, parameters with an error of roughly 1%. We show that the estimated, in two millions of pixels, values of the four parameters are quite consistent with information provided in the literature. Our results are unique in the sense that for the first time functional and microstructural parameter maps can be estimated and displayed together, thus maximizing the diagnostic information. The quantity and the quality of this information are unattainable by other invasive and non invasive methods. The findings of this thesis suggest strongly that our method can improve our understand-ing of the neoplasia development mechanisms and of tumor growth and metastasis physiology. Corollary, it may become a valuable diagnostic tool that will also facilitate the development and evaluation of new cancer therapies.