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Identifier 000441852
Title Advances in non-linear imaging microscopy for tissue and in-vivo biological samples characterization
Alternative Title Εξελίξεις στη μη γραμμική απεικονιστική μικροσκοπία για το χαρακτηρισμό ιστών και βιολογικών δειγμάτων in-vivo
Author Τσαφάς, Βασίλειος-Γεράσιμος Α.
Thesis advisor Φωτάκης, Κωνσταντίνος
Reviewer Χαραλαμπίδης, Δημήτριος
Ταβερναράκης, Νεκτάριος
Abstract The use and development of spectroscopic techniques with emphasis on advanced microscopic methods for the timely and accurate diagnosis of diseases such as cancer or the need to understand some of the most important mechanisms of Biology, such as aging, based on observation and extraction of information at the cellular level is an interdisciplinary field of enormous research interest. Non-linear imaging microscopy is a reliable diagnostic tool for microscopic studies, as it is a minimally invasive technique with high resolution, while also providing the ability to simultaneously capture images through different non-linear signals such as: second and third harmonic generation (SHG / THG) or multiphoton excitation fluorescence (MPEF). During the present dissertation, studies were carried out that help the further development of the above techniques for the investigation of various biological problems. In addition, the creation of new data analysis algorithms and the implementation of artificial neural networks open new horizons in the fields of application of nonlinear microscopy. Specifically, the first of the above studies concerns the application of neural networks to THG images from human biopsy specimens for the accurate diagnosis of breast cancer at subcellular level. Although only the diagnosis of this type of cancer based on the imaging of unstained biopsies through THG was very innovative, it faced a key problem, the need for specialized staff to evaluate and separate the samples. THG mainly depicts optical inhomogeneities, lipids or cell membranes and the diagnosis is based on various characteristics of the cells such as their volume, their morphology and their emitted signal. However, locating cells in THG images is an extremely time consuming process and requires special experience, thus greatly limiting the use of this non-invasive diagnostic technique. The solution to this problem was given through the application of neural networks to categorize specific images. It is worth noting that the application of neural networks in THG images for the diagnosis of breast cancer was done for the first time and its success leads to the elimination of the need for specialized staff and the dramatic reduction of diagnostic time, thus bringing non-linear microscopy one step closer to clinical trials. The second study also concerns the diagnosis of breast cancer based on the above biopsies and non-linear microscopy, but this time the recorded non-linear signal was that of SHG. Tissues are rich in collagen fibers which is capable of emitting strong SHG signals. In recent years there have been several studies on the dependence of SHG on incoming polarization of radiation (PSHG) and on the quantified information obtained through it, such as the anisotropy parameter B. Through this parameter but also with the introduction of a new one (ratio parameter) it became possible to completely differentiate between all cancer stages of the biopsies we studied (from benign to third stage). The calculation of both of these parameters takes less than one second for each sample as it is based on the Fourier analysis of PSHG measurements. In addition, a biophysical model was proposed that interprets these results based on the mechanical strain applied to the collagen fibers during the various stages of cancer. In this dissertation, the capabilities of PSHG in combination with Fourier analysis were also used to study possible structural changes in the striated muscles of the model organism Caenorhabditis elegans (C. elegans) during aging. The results of this study indicate that the striated muscle structure of C. elegans changes as the age of the sample increases. As far as is known, this is the first time that differentiation of the PSHG results has been observed through Fourier analysis from in-vivo muscle as the sample age increases. The differentiation was based on the difference of the spectral phases of the recorded PSHG signals. In addition, through the newly introduced ratio parameter, this study showed that the hitherto usual assumption of cylindrical symmetry for the biophysical model of PSHG lacks in satisfactory and complete description of the recorded data compared to the triangular symmetry, which in turn is inferior to the most general case where the sample does not need to have any particular symmetry. The last part of this thesis was dedicated to highlight the prospect of non-linear microscopy for application in material studies with the aim of delivering innovative results. Νon-linear measurements were used to study Cultural Heritage art works. Specifically, a specially designed algorithm was developed, which through MPEF measurements determines with great accuracy the thickness of the protective varnish layer in a work of art, thus helping in the process of its restoration.
Language English
Subject Aging
Breast cancer
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Καρκίνος του μαστού
Issue date 2021-09-13
Collection   School/Department--School of Sciences and Engineering--Department of Physics--Doctoral theses
  Type of Work--Doctoral theses
Permanent Link https://elocus.lib.uoc.gr//dlib/2/f/e/metadata-dlib-1630401302-847330-11717.tkl Bookmark and Share
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