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Khan, Adnan M. "Algorithms for breast cancer grading in digital histopathology images." Thesis, University of Warwick, 2014. http://wrap.warwick.ac.uk/66024/.
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Histological analysis of tissue biopsies by an expert pathologist is considered gold standard for diagnosing many cancers, including breast cancer. Nottingham grading system, which is the most widely used criteria for histological grading of breast tissues, consists of three components: mitotic count, nuclear atypia and tubular formation. In routine histological analysis, pathologists perform grading of breast cancer tissues by manually examining each tissue specimen against the three components, which is a laborious and subjective process and thus can suffer from low inter-observer agreement. With the advent of digital whole-slide scanning platforms, automatic image analysis algorithms can be used as a partial solution for these issues. The main goal of this dissertation is to develop frameworks that can aid towards building an automated or semi-automated breast cancer grading system. We present novel frameworks for detection of mitotic cells and nuclear atypia scoring in breast cancer histopathology images. Both of these frameworks can play a fundamental role in developing a computer-assisted breast cancer grading system. Moreover, the proposed image analysis frameworks can be adapted to grading and analysis of cancers of several other tissues such as lung and ovarian cancers. In order to deal with one of the fundamental problems in histological image analysis applications, we first present a stain normalisation algorithm that minimises the staining inconsistency in histological images. The algorithm utilises a novel image-specific colour descriptor which summarises the colour contents of a histological image. Stain normalisation algorithm is used in the remainder of the thesis as a preprocessing step. We present a mitotic cell detection framework mimicking a pathologist’s approach, whereby we first perform tumour segmentation to restrict our search for mitotic cells to tumour regions only, followed by candidate detection and evaluation in a statistical machine learning framework. We also employ a discriminative dictionary learning paradigm to learn the visual appearance of mitotic cells, that models colour, texture, and shape in a composite manner. Finally, we present a nuclear atypia scoring framework based on a novel image descriptor which summarises the texture heterogeneity, inherent in histological images in a compact manner. Classification is performed using a geodesic k-nearest neighbour classifier which explicitly exploits the structure of Riemannian manifold of the descriptor and achieves significant performance boost as compared to Euclidean counterpart.
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Hillergren, Pierre. "Towards non-invasive Gleason grading of prostate cancer using diffusion weighted MRI." Thesis, Umeå universitet, Institutionen för fysik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-172808.
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Prostate cancer is one of the most common cancer diagnosis in men. This project aimed to help in characterization and treatment planning of prostate cancer by producing a Gleason grading probability based on apparent diffusion coefficient (ADC). In a study, from which this project received the patient data, the patients were first imaged using magnetic resonance imaging (MRI) in a 3T positron emission tomography MRI (PET/MRI) scanner. The prostates were surgically removed and placed in a patient specific mold. While inside the mold, the prostates were imaged using the same scanner, producing ex-vivo images of the prostates. Lastly the prostates were cut in histopathology slices and Gleason graded by a pathologist. To get correlation between ADC and Gleason grade all images needed to be correctly related to each other. This was done by three image registrations, which was the main part of this project. The histopathology slices were first registered to the ex-vivo images of the prostate, and then to the in-vivo T2-weighted images. The in-vivo T2w images were matched to images depicting the diffusion of water in the prostates, known as ADC-maps. The ADC-values were collected and matched to their possible Gleason grade. Information from 149 images were used, which came from 22 different patients. 3D pixels, known as voxels, with a corresponding Gleason grade annotation measured a lower average ADC-value. These voxels also showed more variation with a larger standard deviation. Furthermore, these voxels measured a larger range of ADC-values compared to voxels without a corresponding Gleason grade, but the probability of a Gleason grade was mainly seen for ADC-values below 1200 mm2/s. Filtering the ADC-map before collecting the information showed less spread in measurements, and larger total probability of Gleason grade annotation for lower ADC-values. To test the validity of the result a movement of the Gleason grade map was used to simulate registration errors. No large impact was observed for small movements but more obvious change for large. The results indicate this method as promising in predicting regions with a probability for Gleason grade of 3 or 4, however it was less accurate in separating the two. Gleason 5 showed very low probability, mainly as a result of the low sample size since only two patients had such tumors. Further research with better optimized filtering is recommended in the future.
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Chaudry, Qaiser Mahmood. "Improving cancer subtype diagnosis and grading using clinical decision support system based on computer-aided tissue image analysis." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/47745.
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This research focuses towards the development of a clinical decision support system (CDSS) based on cellular and tissue image analysis and classification system that improves consistency and facilitates the clinical decision making process. In a typical cancer examination, pathologists make diagnosis by manually reading morphological features in patient biopsy images, in which cancer biomarkers are highlighted by using different staining techniques. This process is subjected to pathologist's training and experience, especially when the same cancer has several subtypes (i.e. benign tumor subtype vs. malignant subtype) and the same cancer tissue biopsy contains heterogeneous morphologies in different locations. The variability in pathologist's manual reading may result in varying cancer diagnosis and treatment.
This Ph.D. research aims to reduce the subjectivity and variation existing in traditional histo-pathological reading of patient tissue biopsy slides through Computer-Aided Diagnosis (CAD). Using the CAD, quantitative molecular profiling of cancer biomarkers of stained biopsy images are obtained by extracting and analyzing texture and cellular structure features. In addition, cancer sub-type classification and a semi-automatic grade scoring (i.e. clinical decision making) for improved consistency over a large number of cancer subtype images can be performed. The CAD tools do have their own limitations and in certain cases the clinicians, however, prefer systems which are flexible and take into account their individuality when necessary by providing some control rather than fully automated system. Therefore, to be able to introduce CDSS in health care, we need to understand users' perspectives and preferences on the new information technology. This forms as the basis for this research where we target to present the quantitative information acquired through the image analysis, annotate the images and provide suitable visualization which can facilitate the process of decision making in a clinical setting.
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Tutac, Adina Eunice. "[Formal representation and reasoning for microscopic medical image-based prognosis] : [application to breast cancer grading]." Besançon, 2010. http://www.theses.fr/2010BESA2025.
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Cette thèse aborde l'aide du pronostic basée sur l'image et les ontologies médicales, en utilisant la représentation des connaissances et le raisonnement pour les très grandes images microscopiques. Une application médicale particulière dans laquelle une assistance de type pronostic est nécessaire est la graduation du cancer du sein. Même si cela est considéré comme un outil d'évaluation essentiel dans la pratique de pathologie moderne les principaux problèmes posés par la procédure manuelle de pronostic sont: la nécessité des connaissances, attention et temps. D'autre part, le manque de reprédentation sémantique formelle standardisée pour aider l'indexation et la classification de la terminologie, ainsi que l'utilisation d'un mécanisme d'inférence pour assister le graduation représentent des problématiques clé du domaine. Dans ce sens, cette étude propose une représentation formelle qualitative pour la graduation du cancer du sein ainsi qu'une ontologie d'application Brest cancer Grading Ontology (BCGO) pour décrire les connaissances d'une manière cohérente. Une autre question que nous adressons en proposant l'ontologie, est le fossé sémantique entre les concepts sémantiques de haut niveau et les caractéristiques de l'image de bas niveau. En plus, nous proposonsun soutien de théorie spatiale pour la représentation des relations spatiales entre les concepts spécifiques à la graduation du cancer du sein. L'ontologie BCGO est intégré dans une plateforme microscopique cognitive virtuelle MICO, pour l'exploitation visuelle, l'indexation et l'extration sémantique des l'images microscopiques<br>This thesis addresses ontology-driven prognosis assistance using knowledge representation and reasoning for very large microscopic medical images. One particular medical application in which prognosis assistance is needed is the breast cancer grading. Althrough this is considered the key assessment tool in prognosis of modern pathology pratice, the main problems of the manual procedure are: time constraint, the need of knowledge and attention. More over, the lack of formal standardized semantic representation for the indexing and classification of terminology and the lack of an inference mechanism to assist the grading are key issues of the domain. To this end, we propose a qualitativ ontological representation of breast cancer grading, an application ontology entlited Breast Cancer Grading Ontology (BCGO) based on OWL-DL and SWRL formalisms. Using this approach, the thesis also tackles the semantic gap between the high-level semantic concepts and the low-level image features. Additionally, we propose a spatial theory support for the representation of the spatial relations between the spatial concepts of the breast cancer grading. This ontology is integrated into a cognitive microscope framework MICO, guiding the image exploration, semantic indexing and retrieval of the microscopic images
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KONDO, TATSUHEI, HIDEO KAMEI, and KEISUKE TERABE. "Histopathological Study on the Prognosis of pT2 Gastric Cancer." Nagoya University School of Medicine, 1986. http://hdl.handle.net/2237/17488.
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Naqvi, Shabbar. "Modelling FTIR spectral sata with Type-I and Type-II fuzzy sets for breast cancer grading." Thesis, University of Nottingham, 2014. http://eprints.nottingham.ac.uk/14321/.
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Breast cancer is one of the most frequently occurring cancers amongst women throughout the world. After the diagnosis of the disease, monitoring its progression is important in predicting the chances of long term survival of patients. The Nottingham Prognostic Index (NPI) is one of the most common indices used to categorise the patients into different groups depending upon the severity of the disease. One of the key factors of this index is cancer grade which is determined by pathologists who examine cell samples under a microscope. This manual method has a higher chance of false classification and may lead to incorrect treatment of patients. There is a need to develop automated methods that employ advanced computational methods to help pathologists in making a decision regarding the classification of breast cancer grade. Fourier transform infra-red spectroscopy (FTIR) is one of the relatively new techniques that has been used for diagnosis of various cancer types with advanced computational methods in the literature. In this thesis we examine the use of advanced fuzzy methods with the FTIR spectral data sets to develop a model prototype that can help clinicians with breast cancer grading. Initial work is focussed on using the commonly used clustering algorithms k-means and fuzzy c-means with principal component analysis on different cancer spectral data sets to explore the complexities within them. After that, a novel model based on Type-II fuzzy logic is developed for use on a complex breast cancer FTIR spectral data set that can help clinicians classify breast cancer grades. The data set used for the purpose consists of multiple cases of each grade. We consider two types of uncertainty, one within the spectra of a single case of a grade (intra -case) and other when comparing it with other cases of same grade (inter-case). Features have been extracted in terms of interval data from various peaks and troughs. The interval data from the features has been used to create Type-I fuzzy sets for each case. After that the Type-I fuzzy sets are combined to create zSlices based General Type-II fuzzy sets for each feature for each grade. The created benchmark fuzzy sets are then used as prototypes for classification of unseen spectral data. Type-I fuzzy sets are created for unseen spectral data and then compared against the benchmark prototype Type-II fuzzy sets for each grade using a similarity measure. The best match based on the calculated similarity scores is assigned as the resultant grade. The novel model is tested on an independent spectral data set of oral cancer patients. Results indicate that the model was able to successfully construct prototype fuzzy sets for the data set, and provide in-depth information regarding the complexities of the data set as well as helping in classification of the data.
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Jiménez, Garay Gabriel Alexandro. "Deep Learning for Semantic Segmentation versus Classification in Computational Pathology: Application to mitosis analysis in Breast Cancer grading." Master's thesis, Pontificia Universidad Católica del Perú, 2019. http://hdl.handle.net/20.500.12404/13969.
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Existing computational pathology approaches did not allow, yet, the emergence of effective/efficient computer-aided tools used as a second opinion for pathologists in the daily practice. Focusing on the case of computer-based qualification for breast cancer diagnosis, the present article proposes two deep learning architectures to efficiently and effectively detect and classify mitosis in a histopathological tissue sample. The first method consisted of two parts, entailing a preprocessing of the digital histological image and a free-handcrafted-feature Convolutional Neural Network (CNN) used for binary classification. Results show that the methodology proposed can achieve 95% accuracy in testing with an F1-score of 94.35%, which is higher than the results from the literature using classical image processing techniques and also higher than the approaches using handcrafted features combined with CNNs. The second approach was an end-to-end methodology using semantic segmentation. Results showed that this algorithm can achieve an accuracy higher than 95% in testing and an average Dice index of 0.6 which is higher than the results from the literature using CNNs (0.9 F1-score). Additionally, due to the semantic properties of the deep learning approach, an end-to-end deep learning framework is viable to perform both tasks: detection and classification of mitosis. The results showed the potential of deep learning in the analysis of Whole Slide Images (WSI) and its integration to computer-aided systems. The extension of this work to whole slide images is also addressed in the last two chapters; as well as, some computational key points that are useful when constructing a computer-aided-system inspired by the described technology.<br>Trabajo de investigación
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Tay, ChiangHau. "Algorithms for Tissue Image Analysis using Multifractal Techniques." Thesis, University of Canterbury. Computer Science and Software Engineering, 2012. http://hdl.handle.net/10092/7268.
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Histopathological classification and grading of biopsy specimens play an important role in early cancer detection and prognosis. Nottingham Grading System (NGS) is one of the standard grading procedures used in breast cancer assessment, where three parameters, Mitotic Count (MC), Nuclear Pleomorphism (NP), and Tubule Formation (TF) are used for prognostic information. The grading takes into account the deviations in cellular structures and appearance between tumour and normal cells, using measures such as density, size, colour, and regularity. Cell structures in tissue images are also known to exhibit multifractal characteristics.
This research focused on the multifractal properties of several graded biopsy specimens and analysed the dependency and variation of the fractal parameters with respect to the scores pre-assigned by pathologists. The effectiveness of using multifractal techniques on breast cancer grading was measured with a set of quantitative evaluations for MC, NP, and TF criteria. The developed method for MC scoring has obtained 82.87% true positive rate on detecting mitotic cells. Furthermore, the overall positive classification rates for NP and TF analysis were 67.38% and 71.82%, respectively, while obtaining 30.26% of false classification rate for NP analysis and 27.17% for TF analysis. The results have shown that multifractal formalism is a feasible and novel method that could be used for automatic grading of biopsy sections.
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ALFARANO, GABRIELE. "INTERFERON REGULATORY FACTOR 1 (IRF1) LINKS IMMUNOLOGICAL AND METABOLIC TRAITS TO HISTOLOGICAL GRADE IN PANCREATIC CANCER." Doctoral thesis, Università degli Studi di Milano, 2019. http://hdl.handle.net/2434/607574.
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Pancreatic Ductal Adenocarcinoma (PDAC) is the most frequent neoplasia of the exocrine pancreas with a 5-years overall survival of less than 5% . Poor response to treatments can be attributed, at least in part, to the pervasive heterogeneity of this type of cancer, whose histological differentiation grade ranges from a well differentiated to a poorly differentiated phenotype . My lab previously dissected the transcriptional and epigenetic networks underlying PDAC grading. By using cell line models mimicking different PDAC grades, transcriptional data highlighted an interferon-related signature as peculiar of low-grade PDACs. This project aims at investigating the links between this interferon-related signature and the epithelial phenotype of well-differentiated PDACs. The role of Interferon Regulatory Factor 1 (IRF1), a transcription factor critical for the interferon response, in PDAC differentiation will be investigated. By combining a loss-of-function strategy and RNA-seq this work aimed at defining the targets and the effects of IRF1 differential expression in the mentioned cell line model. Model reliability will also be confirmed via immunohistochemistry on tumour microarrays. The immunological and metabolic phenotypes regulated by IRF1 in well differentiated PDACs will further be analysed by the use of xenografts and cell culture based assays. It will be shown that IRF1 regulates multiple interferon related genes involved in antigen processing and presentation; its deletion affects stromal composition in xenografts. IRF1 deficient cells also rewire their metabolic networks, with changes in lipid composition and metabolite usage. Overall, we found that the transcription factor IRF1 pleiotropically controls a variety of phenotypical traits of low grade PDACs: from antigen processing and presentation pathways, to metabolism, which IRF1 deficiency rewired towards an increased respiratory and lipogenic profile.
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MILAN, MARTA. "INVOLVEMENT OF THE TRANSCRIPTION FACTOR MYRF IN SIGNALING FROM THE ENDOPLASMIC RETICULUM TO THE NUCLEUS IN PANCREATIC CANCER." Doctoral thesis, Università degli Studi di Milano, 2019. http://hdl.handle.net/2434/607575.
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Pancreatic ductal adenocarcinoma (PDAC) is one of the leading causes of cancer death worldwide. One reason for the poor prognosis is the high intra-tumor heterogeneity, with the coexistence of well- and poorly-differentiated cells in virtually all tumor cases. Thus, a better characterization of the circuitries regulating PDAC cell differentiation is required.
We found that MYRF, a poorly characterized transcription factor, is selectively expressed in well-differentiated PDAC cell lines. MYRF is synthetized as an endoplasmic reticulum (ER) membrane protein and self-cleaves after trimerization, releasing the N-terminal trimer that translocates into the nucleus and regulates transcription. We generated MYRF-KO PDAC cells and combined transcriptomic profiles and analyses of MYRF genomic occupancy to study its function. We retrieved the MYRF DNA binding motif from our ChIP-sequencing data and demonstrated that MYRF capability to bind this sequence and activate transcription is strictly dependent on its trimerization.
MYRF deletion resulted in the downregulation of cell replication-related genes and upregulation of ER stress-related genes. Consistently, MYRF loss resulted in an altered ER morphology and function, probably as a result of the overexpression of membrane and secreted proteins with complex folding, such as cysteine rich and highly glycosylated proteins.
Additionally, we found that MYRF creates a feed-forward loop with the transcription factors FOS and FOSB. In doing so, MYRF directly regulates the expression of these two transcription factors that in turn cooperate to generate the MYRF transcriptional outcome.
In conclusion, this work points to a role for MYRF as a key player in the communication between ER and nucleus, working as a sensor of proper ER function. MYRF appears to license cells for DNA replication and concomitantly to serve as a guardian against ER overload in highly secretory cancer cells.
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Irshad, Humayun. "Automated Mitosis Detection in Color and Multi-spectral High-Content Images in Histopathology : Application to Breast Cancer Grading in Digital Pathology." Thesis, Grenoble, 2014. http://www.theses.fr/2014GRENM007/document.
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La gradation de lames de biopsie fournit des informations pronostiques essentielles pour le diagnostic et le traitement. La détection et le comptage manuel des mitoses est un travail fastidieux, sujet à des variations inter-et intra- observateur considérables. L'objectif principal de cette thèse de doctorat est le développement d'un système capable de fournir une détection des mitoses sur des images provenant de différents types de scanners rapides automatiques, ainsi que d'un microscope multispectral. L'évaluation des différents systèmes proposés est effectuée dans le cadre du projet MICO (MIcroscopie COgnitive, projet ANR TecSan piloté par notre équipe). Dans ce contexte, les systèmes proposés ont été testés sur les données du benchmark MITOS. En ce qui concerne les images couleur, notre système s'est ainsi classé en deuxième position de ce concours international, selon la valeur du critère F-mesure. Par ailleurs, notre système de détection de mitoses sur images multispectrales surpasse largement les meilleurs résultats obtenus durant le concours<br>Digital pathology represents one of the major and challenging evolutions in modernmedicine. Pathological exams constitute not only the gold standard in most of medicalprotocols, but also play a critical and legal role in the diagnosis process. Diagnosing adisease after manually analyzing numerous biopsy slides represents a labor-intensive workfor pathologists. Thanks to the recent advances in digital histopathology, the recognitionof histological tissue patterns in a high-content Whole Slide Image (WSI) has the potentialto provide valuable assistance to the pathologist in his daily practice. Histopathologicalclassification and grading of biopsy samples provide valuable prognostic information thatcould be used for diagnosis and treatment support. Nottingham grading system is thestandard for breast cancer grading. It combines three criteria, namely tubule formation(also referenced as glandular architecture), nuclear atypia and mitosis count. Manualdetection and counting of mitosis is tedious and subject to considerable inter- and intrareadervariations. The main goal of this dissertation is the development of a framework ableto provide detection of mitosis on different types of scanners and multispectral microscope.The main contributions of this work are eight fold. First, we present a comprehensivereview on state-of-the-art methodologies in nuclei detection, segmentation and classificationrestricted to two widely available types of image modalities: H&E (HematoxylinEosin) and IHC (Immunohistochemical). Second, we analyse the statistical and morphologicalinformation concerning mitotic cells on different color channels of various colormodels that improve the mitosis detection in color datasets (Aperio and Hamamatsu scanners).Third, we study oversampling methods to increase the number of instances of theminority class (mitosis) by interpolating between several minority class examples that lietogether, which make classification more robust. Fourth, we propose three different methodsfor spectral bands selection including relative spectral absorption of different tissuecomponents, spectral absorption of H&E stains and mRMR (minimum Redundancy MaximumRelevance) technique. Fifth, we compute multispectral spatial features containingpixel, texture and morphological information on selected spectral bands, which leveragediscriminant information for mitosis classification on multispectral dataset. Sixth, we performa comprehensive study on region and patch based features for mitosis classification.Seven, we perform an extensive investigation of classifiers and inference of the best one formitosis classification. Eight, we propose an efficient and generic strategy to explore largeimages like WSI by combining computational geometry tools with a local signal measureof relevance in a dynamic sampling framework.The evaluation of these frameworks is done in MICO (COgnitive MIcroscopy, ANRTecSan project) platform prototyping initiative. We thus tested our proposed frameworks on MITOS international contest dataset initiated by this project. For the color framework,we manage to rank second during the contest. Furthermore, our multispectral frameworkoutperforms significantly the top methods presented during the contest. Finally, ourframeworks allow us reaching the same level of accuracy in mitosis detection on brightlightas multispectral datasets, a promising result on the way to clinical evaluation and routine
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Garnier, Mickaël. "Modèles descriptifs de relations spatiales pour l'aide au diagnostic d'images biomédicales." Thesis, Paris 5, 2014. http://www.theses.fr/2014PA05S015/document.
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La pathologie numérique s’est développée ces dernières années grâce à l’avancée récente des algorithmes d’analyse d’images et de la puissance de calcul. Notamment, elle se base de plus en plus sur les images histologiques. Ce format de données a la particularité de révéler les objets biologiques recherchés par les experts en utilisant des marqueurs spécifiques tout en conservant la plus intacte possible l’architecture du tissu. De nombreuses méthodes d’aide au diagnostic à partir de ces images se sont récemment développées afin de guider les pathologistes avec des mesures quantitatives dans l’établissement d’un diagnostic. Les travaux présentés dans cette thèse visent à adresser les défis liés à l’analyse d’images histologiques, et à développer un modèle d’aide au diagnostic se basant principalement sur les relations spatiales, une information que les méthodes existantes n’exploitent que rarement. Une technique d’analyse de la texture à plusieurs échelles est tout d’abord proposée afin de détecter la présence de tissu malades dans les images. Un descripteur d’objets, baptisé Force Histogram Decomposition (FHD), est ensuite introduit dans le but d’extraire les formes et l’organisation spatiale des régions définissant un objet. Finalement, les images histologiques sont décrites par les FHD mesurées à partir de leurs différents types de tissus et des objets biologiques marqués qu’ils contiennent. Les expérimentations intermédiaires ont montré que les FHD parviennent à correctement reconnaitre des objets sur fonds uniformes y compris dans les cas où les relations spatiales ne contiennent à priori pas d’informations pertinentes. De même, la méthode d’analyse de la texture s’avère satisfaisante dans deux types d’applications médicales différents, les images histologiques et celles de fond d’œil, et ses performances sont mises en évidence au travers d’une comparaison avec les méthodes similaires classiquement utilisées pour l’aide au diagnostic. Enfin, la méthode dans son ensemble a été appliquée à l’aide au diagnostic pour établir la sévérité d’un cancer via deux ensembles d’images histologiques, un de foies métastasés de souris dans le contexte du projet ANR SPIRIT, et l’autre de seins humains dans le cadre du challenge CPR 2014 : Nuclear Atypia. L’analyse des relations spatiales et des formes à deux échelles parvient à correctement reconnaitre les grades du cancer métastasé dans 87, 0 % des cas et fourni des indications quant au degré d’atypie nucléaire. Ce qui prouve de fait l’efficacité de la méthode et l’intérêt d’encoder l’organisation spatiale dans ce type d’images particulier<br>During the last decade, digital pathology has been improved thanks to the advance of image analysis algorithms and calculus power. Particularly, it is more and more based on histology images. This modality of images presents the advantage of showing only the biological objects targeted by the pathologists using specific stains while preserving as unharmed as possible the tissue structure. Numerous computer-aided diagnosis methods using these images have been developed this past few years in order to assist the medical experts with quantitative measurements. The studies presented in this thesis aim at adressing the challenges related to histology image analysis, as well as at developing an assisted diagnosis model mainly based on spatial relations, an information that currently used methods rarely use. A multiscale texture analysis is first proposed and applied to detect the presence of diseased tissue. A descriptor named Force Histogram Decomposition (FHD) is then introduced in order to extract the shapes and spatial organisation of regions within an object. Finally, histology images are described by the FHD measured on their different types of tissue and also on the stained biological objects inside every types of tissue. Preliminary studies showed that the FHD are able to accurately recognise objects on uniform backgrounds, including when spatial relations are supposed to hold no relevant information. Besides, the texture analysis method proved to be satisfactory in two different medical applications, namely histology images and fundus photographies. The performance of these methods are highlighted by a comparison with the usual approaches in their respectives fields. Finally, the complete method has been applied to assess the severity of cancers on two sets of histology images. The first one is given as part of the ANR project SPIRIT and presents metastatic mice livers. The other one comes from the challenge ICPR 2014 : Nuclear Atypia and contains human breast tissues. The analysis of spatial relations and shapes at two different scales achieves a correct recognition of metastatic cancer grades of 87.0 % and gives insight about the nuclear atypia grade. This proves the efficiency of the method as well as the relevance of measuring the spatial organisation in this particular type of images
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Garnier, Mickaël. "Modèles descriptifs de relations spatiales pour l'aide au diagnostic d'images biomédicales." Electronic Thesis or Diss., Paris 5, 2014. http://www.theses.fr/2014PA05S015.
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La pathologie numérique s’est développée ces dernières années grâce à l’avancée récente des algorithmes d’analyse d’images et de la puissance de calcul. Notamment, elle se base de plus en plus sur les images histologiques. Ce format de données a la particularité de révéler les objets biologiques recherchés par les experts en utilisant des marqueurs spécifiques tout en conservant la plus intacte possible l’architecture du tissu. De nombreuses méthodes d’aide au diagnostic à partir de ces images se sont récemment développées afin de guider les pathologistes avec des mesures quantitatives dans l’établissement d’un diagnostic. Les travaux présentés dans cette thèse visent à adresser les défis liés à l’analyse d’images histologiques, et à développer un modèle d’aide au diagnostic se basant principalement sur les relations spatiales, une information que les méthodes existantes n’exploitent que rarement. Une technique d’analyse de la texture à plusieurs échelles est tout d’abord proposée afin de détecter la présence de tissu malades dans les images. Un descripteur d’objets, baptisé Force Histogram Decomposition (FHD), est ensuite introduit dans le but d’extraire les formes et l’organisation spatiale des régions définissant un objet. Finalement, les images histologiques sont décrites par les FHD mesurées à partir de leurs différents types de tissus et des objets biologiques marqués qu’ils contiennent. Les expérimentations intermédiaires ont montré que les FHD parviennent à correctement reconnaitre des objets sur fonds uniformes y compris dans les cas où les relations spatiales ne contiennent à priori pas d’informations pertinentes. De même, la méthode d’analyse de la texture s’avère satisfaisante dans deux types d’applications médicales différents, les images histologiques et celles de fond d’œil, et ses performances sont mises en évidence au travers d’une comparaison avec les méthodes similaires classiquement utilisées pour l’aide au diagnostic. Enfin, la méthode dans son ensemble a été appliquée à l’aide au diagnostic pour établir la sévérité d’un cancer via deux ensembles d’images histologiques, un de foies métastasés de souris dans le contexte du projet ANR SPIRIT, et l’autre de seins humains dans le cadre du challenge CPR 2014 : Nuclear Atypia. L’analyse des relations spatiales et des formes à deux échelles parvient à correctement reconnaitre les grades du cancer métastasé dans 87, 0 % des cas et fourni des indications quant au degré d’atypie nucléaire. Ce qui prouve de fait l’efficacité de la méthode et l’intérêt d’encoder l’organisation spatiale dans ce type d’images particulier<br>During the last decade, digital pathology has been improved thanks to the advance of image analysis algorithms and calculus power. Particularly, it is more and more based on histology images. This modality of images presents the advantage of showing only the biological objects targeted by the pathologists using specific stains while preserving as unharmed as possible the tissue structure. Numerous computer-aided diagnosis methods using these images have been developed this past few years in order to assist the medical experts with quantitative measurements. The studies presented in this thesis aim at adressing the challenges related to histology image analysis, as well as at developing an assisted diagnosis model mainly based on spatial relations, an information that currently used methods rarely use. A multiscale texture analysis is first proposed and applied to detect the presence of diseased tissue. A descriptor named Force Histogram Decomposition (FHD) is then introduced in order to extract the shapes and spatial organisation of regions within an object. Finally, histology images are described by the FHD measured on their different types of tissue and also on the stained biological objects inside every types of tissue. Preliminary studies showed that the FHD are able to accurately recognise objects on uniform backgrounds, including when spatial relations are supposed to hold no relevant information. Besides, the texture analysis method proved to be satisfactory in two different medical applications, namely histology images and fundus photographies. The performance of these methods are highlighted by a comparison with the usual approaches in their respectives fields. Finally, the complete method has been applied to assess the severity of cancers on two sets of histology images. The first one is given as part of the ANR project SPIRIT and presents metastatic mice livers. The other one comes from the challenge ICPR 2014 : Nuclear Atypia and contains human breast tissues. The analysis of spatial relations and shapes at two different scales achieves a correct recognition of metastatic cancer grades of 87.0 % and gives insight about the nuclear atypia grade. This proves the efficiency of the method as well as the relevance of measuring the spatial organisation in this particular type of images
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Fourtouna, Argyro. "Function of the anterior gradient protein family in cancer." Thesis, University of Edinburgh, 2009. http://hdl.handle.net/1842/4302.
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Proteomic technologies verified Anterior Gradient 2, AGR-2, as a protein over-expressed in human cancers, including breast, prostate and oesophagus cancers, with the ability to inhibit the tumour suppressor protein p53. AGR-2 gene is a hormone responsive gene with an unexpected induction by the anti-cancer drug tamoxifen highlighting the proto-oncogenic role of this protein. Anterior Gradient-2 encodes one protein that gives rise to two forms· the full length and the mature one. Full length bears a leader sequence that leads the protein to secretion. Localization studies of both forms of AGR-2 were performed using fluorescence microscopy and subcellular fractionation, in order to determine in which compartment the protein functions. Localization mutants of the mature and full length protein determined the exact sequence required for certain localization patterns. Once localization was confirmed, the mechanism of how Anterior Gradient-2 localization within the cell can inhibit p53 was initiated. Furthermore, novel peptide aptamers that bound to the protein were cloned into GFP vectors and their effect on AGR-2 was investigated. AGR-3, another member of the family, was also examined in terms of localization and function in MCF-7 cells. Yeast two hybrid analysis has identified potential nuclear and cytoplasmic binding partners for AGR-2, essential for the upstream or downstream regulation of the AGR-2 pathway. In conclusion, we present data showing models of how the Anterior Gradient protein family might function as drug-resistance survival factor in cancer as well as a p53 inhibitor, suggesting a multi-potent role of its members when it comes to trafficking, cellular localization and activation or inhibition pathways in cancer.
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Gray, Terry Allan. "Structural and functional interrogation of Anterior Gradient-2." Thesis, University of Edinburgh, 2013. http://hdl.handle.net/1842/8825.
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Anterior Gradient-2 protein (AGR2) has recently been linked to the onset of several pathologies including asthma and inflammatory bowel disease. Most interestingly, it has been discovered to influence the transformation of cells and metastatic growth essential to cancer development, and has subsequently been linked to the development of resistance to anti-cancer therapeutics. AGR2 protein is overexpressed in a diverse range of human cancer types, and has been detected secreted into the extracellular milieu. Thus, AGR2 protein represents a compelling pro-oncogenic signalling intermediate in tumour emergence and endurance. This thesis presents an interdisciplinary approach including structural biology, cell biology and synthetic biology, and clinical studies to shed more light on the role of AGR2 in cancer development. Synthetic cell based reagents were developed to define the dominant pathways that are reprogrammed in a cell as a result of AGR2 synthesis. A cell panel was engineered incorporating the AGR2 (and mutants thereof) allele into the AGR2-null A375 cell line. These tools were then coupled to quantitative proteomics (SILAC) to unravel the mechanism whereby introduction of AGR2 alters cell phenotype, allowing identification of dominant pathways affected by AGR2 signalling. Using pathway analysis tools, the dominant pathway suppressed by wt-AGR2 expression highlighted the p53-signalling axis. DNA damage induced p53 stabilisation and p21 induction by cisplatin treatment confirmed the influence of AGR2 gene expression. Further data analysis identified the outlying protein expression changes identified by SILAC was the anti-viral cell cycle regulator TSG101 (tumour susceptibility gene 101), and confirmed by immunoblotting. Transfection and silencing studies of TSG101 confirmed that TSG101 attenuates p53 function. These data provide a mechanism to explain the most dominant pathways reprogrammed by AGR2 expression, incorporating ER stress response, proliferation markers and p53 pathway attenuation. Further advances were made in analysis of the function, regulation, and drugability of AGR2 protein. Assays were devised to define the subunit structure of AGR2 as a dimer unit; subsequent functional studies defined intrinsically disordered motifs that regulate stability of the dimer. A two-site sandwich microtiter assay (2SMTA) was designed to screen for self-peptides and mutations that regulate oligomer stability. These assays were used to identify the first biochemical property of AGR2 being that the dimer unit is required for maximal binding to the AAA+ protein, and well characterised AGR2 interactor, Reptin. In addition, based on this dimeric structure, a novel solution based dimerisation assay was developed to identify natural products that are able to disrupt the dimer suggesting that AGR2 itself can be targeted in principle with small molecules for therapeutic purposes.
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Ma, Yujia. "Biomimetic 3D scaffold for cancer research." Thesis, The University of Sydney, 2016. http://hdl.handle.net/2123/16048.
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Cancer is a leading cause of death around the world in recent years. Tissue engineering and Materials Science are important tools in cancer research in the fields of basic pathology, drug discovery and radiation oncology. This project involved the development of a biomimetic three-dimensional (3D) model based polycaprolactone (PCL) that was biocompatible and biodegradable for cancer cells. Such a scaffold would have significant advantages compared to traditional 2D models in mimicking the in vivo tumour microenvironment as tumours are 3D structures. An aliphatic composite scaffold concept was adopted and the scaffold composition was modified to improve cancer cell growth. The development of the synthetic scaffold (extracellular-matrix analogue) which demonstrated superior scaffold design flexibility as well as reproducibility was compared to naturally-derived counterparts. Bioactive glass is a synthetic biomaterial and commonly used in tissue replacement. Bioactive glass scaffold dopant was incorporated to enhance tissue formation and was a stimulant to improve cell growth in the polymeric scaffold. Bioactive glass 45S5 was incorporated into the scaffold by coating, infusion and coating with PCL sizing (extremely thin encapsulation). Pre-soaking of scaffolds by culture medium was a second promoting factor that was explored. In vitro cell growth (Melanoma and bowel cancer cell lines) on bioactive glass implanted scaffolds was compared to non-modified scaffold and scaffolds with collagen coating (natural material) and quantified with haemocytometry and protein assay. In composition modification, non-supplemented medium pre-soaking represented a promoting effect on cell adsorption. Advanced sized bioactive glass coated scaffold with non-supplemented medium pre-soaking demonstrated the highest capability in proliferating cells compared to other synthetic and natural modifications. Cell proliferating capability of bioactive glass was promoted 6folds by PCL sizing and non-supplemented medium pre-soaking, which was an innovative strategy for in vitro tumour modelling. Scaffold pore size was important for cell growth and an optimal pore size was determined by cell size according to cell type. Interconnectivity of the pore in the scaffold was also important for tumour cell migration. The second stage of the research involved the development of a novel porosity-graded FGM (functionally graded material) PCL scaffold, fabricated by compressing wedged shape scaffolds to a pellet with even thickness. Modules were fabricated by various methods such as carving, moulding and 3D printing with several materials from metal, polymer to gel. Optimization was conducted with the view of developing a scaffold with maximum cell capture and retention capability during cell seeding of the scaffold. The FGM system was novel in tissue engineering and cancer research. FGM system was particularly useful in facilitating in vitro 3D model design as well as for study of cellular behaviours in tumour development.
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Confavreux, Antoine. "Optimisation des conditions de migration et de détachement de lignées cancéreuses du cancer du sein en vue de leur tri fonctionnel." Thesis, Lyon 1, 2014. http://www.theses.fr/2014LYO10209/document.
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Cette thèse concerne l'étude des propriétés de migration et de détachement de lignées cancéreuses du cancer du sein de type mésenchyme, très métastatique et invasif (MDA-MB-231), ou au contraire de type épithélial et peu invasif (MCF-7). Des techniques de vidéomicroscopie et d'analyse d'images automatisées ont été utilisées afin de tirer des informations sur la dynamique cellulaire sur de grandes populations. Nos expériences sur la migration aléatoire des cellules MDA-MB-231 montrent que les propriétés de déplacement de celles-ci sont liées à la fois à la composition de leur milieu environnant, mais aussi à la nature et la quantité de protéines d'adhésion. Nous avons notamment mis en évidence un comportement biphasique de la distance migrée au cours du temps en fonction de la densité de protéines adsorbées sur des surfaces pour deux types de protéines d'adhésion (collagène type IV et fibronectine). Selon le type de protéines d'adhésion, nous avons également mis en évidence un phénotype cellulaire très différent en termes de forme, d'adhésion et de mode de déplacement. Nous avons ensuite utilisé ces résultats pour mettre en place un protocole de migration dirigée de cellules cancéreuses dans un gradient chimiotactique généré par un système microfluidique. Ainsi, en faisant varier les paramètres du système (protéines de surface, concentration maximale en chimioattractants, …), nous avons pu caractériser les bonnes conditions d'obtention de la migration dirigée. Pour finir, nous avons montré la faisabilité d'un tri cellulaire entre cellules de type mésenchyme et épithéliales en utilisant la chimiotaxie à partir de ces systèmes<br>This thesis investigates migration and detachement properties of different types of breast cancer cell lines : metastatic, invasive MDA-MB-231 and epithelial, low-invasive MCF-7 celles. Videomicroscopy and image analysis techniques were used to obtain dynamic information for large cell populations. Random migration assays performed on MDA-MB-231 cells reveal that their migration properties are related to both medium and surface (substrate adhesion protein type and quantity) conditions. A biphasic behavior for the migrated distance through time was observed to be dependent on the density of adsorbed protein (collagen type IV or fibronectin) on the substrate. Cell shape, detachement and moving properties were also computed as a function of the surface protein characteristics. These results were then used to perform directed migration assays in a chemotactic gradient generated in a microfluidic chamber. Optimal conditions for directed migration of cells were determined by varying the parameters of the system such as gradient maximum concentration, substrate adhesion protein… Lastly, it was experimentally proved that it is possible to separate cancer epithelial cell lines from mesenchymal ones by using chemotactic microfluidic chambers
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DISO, DANIELE. "Impatto del grading istologico sulla sopravvivenza nei pazienti sottoposti a resezione radicale per cancro del polmone." Doctoral thesis, Università degli Studi di Roma "Tor Vergata", 2009. http://hdl.handle.net/2108/208573.
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Cowan, Nigel Christopher. "The development of CT urography for investigating haematuria." Thesis, University of Oxford, 2013. http://ora.ox.ac.uk/objects/uuid:284084de-2a71-4e35-8342-41f039b03df1.
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This thesis addresses the three principal questions concerning the development of CT urography for investigating haematuria and each question is the subject of a separate chapter. The questions are: What is the reasoning behind using CT urography? What is the optimum diagnostic strategy using CT urography? What are the problems with using CT urography and how may solutions be provided? Haematuria can signify serious disease such as urinary tract stones, renal cell cancer, upper tract urothelial cancer (UTUC) and bladder cancer (BCa). CT urography is defined as contrast enhanced CT examination of kidneys, ureters and bladder. The technique used here includes unenhanced, nephrographic and excretory-phases for optimized diagnosis of stones, renal masses and urothelial cancer respectively. The reasoning behind using excretory-phase CT urography for investigating haematuria is based on results showing its high diagnostic accuracy for UTUC and BCa. Patients with haematuria are classified as low risk or high risk for UTUC and BCa, by a risk score, determined by the presence/absence of risk factors: age > 50 years, visible or nonvisible haematuria, history of smoking and occupational exposure. The optimum diagnostic strategy for patients at high risk for urothelial cancer, uses CT urography as a replacement test for ultrasonography and intravenous urography and as a triage test for flexible and rigid cystoscopy, resulting in earlier diagnosis and potentially improving prognosis. For patients at low risk, ultrasonography, unenhanced and nephrographic-phase CT urography are proposed as initial imaging tests. Problems with using CT urography include false positive results for UTUC, which are eliminated by retrograde ureteropyelography-guided biopsy, an innovative technique, for histopathological confirmation of diagnosis. Recommendations for the NHS and possible future developments are discussed. CT urography, including excretory-phase imaging, is recommended as the initial diagnostic imaging test before cystoscopy for patients with haematuria at high risk for urothelial cancer.
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Polge, Géraldine. "Etude de la faisabilité d'un système de cartographie de dose par stimulation optique et application à la radiothérapie à haut gradient de dose." Montpellier 2, 2001. http://www.theses.fr/2001MON20190.
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Shehu, Erald [Verfasser], and A. [Akademischer Betreuer] Cato. "The expression and function of human Anterior Gradient Homolog 3 in Prostate Cancer / Erald Shehu. Betreuer: A. Cato." Karlsruhe : KIT-Bibliothek, 2013. http://d-nb.info/1047383594/34.
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Sonesson, Hannah. "Immunhistokemi - Utvärdering av antikropp mot pHH3 som potentiell markör för mitos vid diagnostisering av duktal bröstcancer." Thesis, Linnéuniversitetet, Institutionen för kemi och biomedicin (KOB), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-68413.
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Duktal bröstcancer är den vanligaste formen av invasiva brösttumörer. Graderingssystemet för bröstcancer har definierats av Elston och Ellis och är baserat på tre parametrar. En av dessa är räkning av antal mitoser på preparat färgade med Hematoxylin och Eosin (HE). Som ett komplement vid bedömning av bröstcancer analyseras Ki67, en proliferationsmarkör, med hjälp av immunhistokemi (IHC). Fosfohiston H3 (pHH3) är ett histonprotein som finns i cellkärnan. Proteinet tros vara en specifik markör för mitos eftersom den är fosforylerad enbart under M-fasen och i slutet av G2-fasen. Syftet med studien var att utvärdera pHH3 som potentiell markör för mitos vid diagnostiseringen av duktal bröstcancer. Syftet var även att jämföra metoden med räkning av antal mitoser och Ki67-positiva celler, samt att studera den interindividuella skillnaden vid bedömningen av preparaten. Materialet bestod av 20 sektorresektat med invasiv duktal bröstcancer. Preparaten färgades med IHC och bedömdes mikroskopiskt. Celler som var positiva för pHH3 och Ki67 samt antal mitoser räknades, av tre läkare. Ett medelvärde för varje patientfall och metod beräknades från läkarnas bedömningar. Metodernas variationskoefficienter och dess medelvärden beräknades. Variationskoefficienterna uppvisade medelvärden på 0,21 för Ki67 +/- 0,10 SD, 0,33 för pHH3 +/- 0,14 SD och 0,46 för mitosräkning +/- 0,34 SD. Korrelationskoefficienterna för metoderna och respektive läkare uppvisade en spridning. Korrelationerna uppvisade medelvärden på r = 0,78 för Ki67 och pHH3, r = 0,74 för Ki67 och mitos samt r = 0,83 för pHH3 och mitos. Enligt studien verkar antipHH3 vara ett bra komplement vid bedömning av duktal bröstcancer. Dock krävs tydliga kriterier för vad som ska räknas som en pHH3-positiv cell. Intervariabiliteten verkar bli mindre med anti-pHH3 än vid räkning av mitoser, som är mer tidskrävande. Minst intervariabilitet ses vid bedömning av anti-Ki67 som en proliferationsmarkör.<br>Ductal carcinoma of the breast is the most common form of invasive breast tumours. The grading system for breast cancer is defined by Elston and Ellis and is based on three criterions. One of these criterions is the mitotic count in pathological sections of breast carcinomas stained with Hematoxylin Eosin. A common method often applied as a complement in diagnosis of breast carcinoma is immunohistochemical staining with use of antibodies directed against Ki67, a proliferation marker. Phosphohistone H3 is a histone protein that is located in the cell nucleus. The protein is believed to be a specific marker for mitosis since it only is phosphorylated during mitosis, and to some extent at the end of the G2-phase. The purpose of this study was to evaluate pHH3 as a potential marker for mitosis when diagnosing ductal breast cancer. The purpose was also to compare the method to mitotic figuring and the count of Ki67-positive cells, and to study the inter-individual variability when assessing the histological sections. The material consisted of 20 biopsies containing invasive ductal breast cancer. The sections were stained using IHC and all sections were evaluated microscopically. Cells positive for pHH3, Ki67 and mitotic cells were quantified, by three doctors. From the doctors results an average value was determined for each case and method. To be able to compare the methods the coefficient of variation was calculated. The average value of the coefficient of variation was determined for each method and also the standard deviation (SD). The coefficient of variation showed average values of 0,21 for Ki67 +/- 0,10 SD, 0,33 for pHH3 +/- 0,14 SD and 0,46 for mitotic figuring +/- 0,34 SD. The correlation coefficients for the methods and each doctor showed dispersion. The correlations showed average values of r = 0,78 for Ki67 and pHH3, r = 0,74 for Ki67 and mitosis and r = 0,83 for pHH3 and mitosis. According to this study it seems as though anti-pHH3 could complement the other methods. However explicit criteria which defines a threshold value of which cells should be considered pHH3-positive needs to be established. The inter-individual differences seem to decrease using antipHH3 compared with mitotic counting, which is more time consuming. Although the minimum difference can be seen when assessing anti-Ki67 as a proliferation marker.
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Koslav, Maria B. "Development of a machine vision based oyster meat sorter." Thesis, Virginia Polytechnic Institute and State University, 1989. http://hdl.handle.net/10919/53225.
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Oyster meats are currently sorted by hand using volume as the sorting parameter. Hand grading is inaccurate, time consuming and costly. Previous research on physical properties of oyster meats showed a high correlation between projected area of oyster meats and their volume thus allowing the use of projected area measurements as a sorting criterion. A machine vision based oyster meat sorting machine was developed to mechanize the sorting process. The machine consists of a dark conveyor belt transporting singulated oysters through a grading station and then along a row of fast acting water jet valves which separates the stream of oysters into 3 classes. The vision system consists of a monochrome television camera, flash light illumination to "freeze" the images, a digitizer/transmitter and a Personal Computer as an image processing unit. Software synchronizes the flash light and digitization of images and calculates projected area of each meat using the planimeter method. The grading results are sent to a valve control board which actuates the spray valves. The sorting rate is 37 oyster meats/min with a sorting accuracy of 87.5%. A description of the design work, adjustment and l calibration procedures and a final sorting test is included.<br>Master of Science
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Flewellen, James Lewis. "Development of Clinically-Viable Applications of MR Elastography." Thesis, University of Canterbury. Physics and Astronomy, 2008. http://hdl.handle.net/10092/1980.
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Magnetic Resonance Elastography is a method of imaging the elasticity of soft tissues through measurement of small motions induced into a sample. It shows great promise in the detection of a wide variety of pathologies, especially tumours. An imaging protocol was developed to acquire MR elastography data for use in a clinical setting. A 3D gradient echo sequence was modified to allow for the detection of harmonic motion and tested on silicone phantoms and ex-vivo muscle and brain samples. The time for acquiring a high resolution, quantitative dataset of 3D motions was about 45 minutes. Our imaging method included motion encoding along all three coordinate axes and at several time points along the motion cycle. This time could be easily be reduced by more than half for future clinical use, while still retaining full quantitative data. A modified EPI sequence shows promise for even faster acquisition. The ability to detect the mechanical anisotropy of brain and muscle tissue in ex-vivo samples was also investigated. Initial results from the muscle data indicate a change in shear wavelength is observed for actuation along orthogonal axes. This is a strong indicator of anisotropy detection. Further work needs to be done to improve results from the brain sample as preliminary results are inconclusive.
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Chick, Joel. "Proteomic analysis of liver membranes through an alternative shotgun methodology." Phd thesis, Australia : Macquarie University, 2009. http://hdl.handle.net/1959.14/42528.
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Thesis (PhD)--Macquarie University, Division of Environmental & Life Sciences, Dept. of Chemistry & Biomolecular Sciences, 2009.<br>Bibliography: p. 200-212.<br>Introduction -- Shotgun proteomic analysis of rat liver membrane proteins -- A combination of immobilised pH gradients improve membrane proteomics -- Affects of tumor-induced inflammation on membrane proteins abundance in the mouse liver -- Affects of tumor-induced inflammation on biochemical pathways in the mouse liver -- General discussion -- References.<br>The aim of this thesis was to develop a proteomics methodology that improves the identification of membrane proteomes from mammalian liver. Shotgun proteomics is a method that allows the analysis of proteins from cells, tissues and organs and provides comprehensive characterisation of proteomes of interest. The method developed in this thesis uses separation of peptides from trypsin digested membrane proteins by immobilised pH gradient isoelectric focusing (IPG-IEF) as the first dimension of two dimensional shotgun proteomics. In this thesis, peptide IPG-IEF was shown to be a highly reproducible, high resolution analytical separation that provided the identification of over 4,000 individual protein identifications from rat liver membrane samples. Furthermore, this shotgun proteomics strategy provided the identification of approximately 1,100 integral membrane proteins from the rat liver. The advantages of using peptide IPG-IEF as a shotgun proteomics separation dimension in conjunction with label-free quantification was applied to a biological question: namely, does the presence of a spatially unrelated benign tumor affect the abundance of mouse liver proteins. IPG-IEF shotgun proteomics provided comprehensive coverage of the mouse liver membrane proteome with 1,569 quantified proteins. In addition, the presence of an Englebreth-Holm-Swarm sarcoma induced changes in abundance of proteins in the mouse liver, including many integral membrane proteins. Changes in the abundance of liver proteins was observed in key liver metabolic processes such as fatty acid metabolism, fatty acid transport, xenobiotic metabolism and clearance. These results provide compelling evidence that the developed shotgun proteomics methodology allows for the comprehensive analysis of mammalian liver membrane proteins and detailed some of the underlying changes in liver metabolism induced by the presence of a tumor. This model may reflect changes that could occur in the livers of cancer patients and has implications for drug treatments.<br>Mode of access: World Wide Web.<br>609 p. ill. (some col.)
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Jeleń, Łukasz. "Computerized cancer malignancy grading of fine needle aspirates." Thesis, 2009. http://spectrum.library.concordia.ca/976607/1/NR63367.pdf.
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According to the World Health Organization, breast cancer is a leading cause of death among middle-aged women. Precise diagnosis and correct treatment significantly reduces the high number of deaths caused by breast cancer. Being successful in the treatment strictly relies on the diagnosis. Specifically, the accuracy of the diagnosis and the stage at which a cancer was diagnosed. Precise and early diagnosis has a major impact on the survival rate, which indicates how many patients will live after the treatment. For many years researchers in medical and computer science fields have been working together to find the approach for precise diagnosis. For this thesis, precise diagnosis means finding a cancer at as early a stage as possible by developing new computer aided diagnostic tools. These tools differ depending on the type of cancer and the type of the examination that is used for diagnosis. This work concentrates on cytological images of breast cancer that are produced during fine needle aspiration biopsy examination. This kind of examination allows pathologists to estimate the malignancy of the cancer with very high accuracy. Malignancy estimation is very important when assessing a patients survival rate and the type of treatment. To achieve precise malignancy estimation, a classification framework is presented. This framework is able to classify breast cancer malignancy into two malignancy classes and is based on features calculated according to the Bloom-Richardson grading scheme. This scheme is commonly used by pathologists when grading breast cancer tissue. In Bloom-Richardson scheme two types of features are assessed depending on the magnification. Low magnification images are used for examining the dispersion of the cells in the image while the high magnification images are used for precise analysis of the cells' nuclear features. In this thesis, different types of segmentation algorithms were compared to estimate the algorithm that allows for relatively fast and accurate nuclear segmentation. Based on that segmentation a set of 34 features was extracted for further malignancy classification. For classification purposes 6 different classifiers were compared. From all of the tests a set of the best preforming features were chosen. The presented system is able to classify images of fine needle aspiration biopsy slides with high accuracy
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Yang, Ching-chieh, and 楊清傑. "Clinical Significance of Tumor Regression Grading after Preoperative Chemoradiotherapy for Rectal Cancer." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/00840578966320078102.
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碩士<br>國立中山大學<br>生物科學系研究所<br>101<br>Preoperative chemoradiotherapy has been the standard treatment for locally advanced rectal cancer patients but there is no technique suggested to be used to predicate the outcome. Here, we use the tumor regression grading (TRG) and analyzed it with clinic-pathological parameters and survival rate. One hundred and seventy-two patients with rectal cancers were enrolled in this study from January 1998 to December 2008. All patients underwent preoperative chemoradiotherapy and curative surgery for rectal cancer (stages I-III) at our institute. TRG was retrospective reviwed on excised specimens from the patients after radical surgery. Preoperative concurrent chemoradiotherapy was given at a total dose of 45-50.4 Gy in 25 fractions over a period about 5.5 weeks, and a continuous infusion of 5-fluorouracil (300 mg/m2/day over 24 hours, 5 days per week for 5 weeks) was administered. Surgery was performed 4-6 weeks after completion of the preoperative chemoradiotherapy. Our result showed that subgroup of complete response (TRG 4), intermittent response (TRG 2-3), and minor or no response TRG (0-1) were found in 9.9%, 68.6%, and 21.5% of these resected specimens. Five-year overall survival (OS) after preoperative chemoradiotherapy and curative resection was 93% for TRG 4, 77% for grouped TRG 2-3, and 47% for grouped TRG 0-1 (P=.037). Patients with more tumor regression (4 vs. 2-3 vs. 01) also have better results for 5-year local-free (LFS), disease-free (DFS), and metastases free survival (MFS) (P = .004, P = .002, and P = .0001, respectively). But in multivariate analysis, the vascular invasion of pathologic specimens and TRG were the most important independent prognostic factors for LFS and DFS. In conclusion, higher TRG after preoperative chemoradiotherapy for rectal cancer closely contributed to better survival and local control. The TRG is considered to be a significant prognostic factor but it could not predict distant metastases.
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Li, Cheng-Yi, and 李政誼. "The Grading of Prostatic Cancer in Biopsy Image based on Two Stages Approach." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/90381765124010668801.
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碩士<br>朝陽科技大學<br>資訊管理系碩士班<br>100<br>Prostatic biopsies provide the information for the determined diagnosis of prostatic cancer. Computer-aid investigation of biopsies can reduce the loading of pathologists and also inter- and intra-observer variability as well. In this thesis, we proposed a two stages approach for prostatic cancer grading according to Gleason grading system. The first stage classified biopsy images into clusters based on their Skeleton-set (SK-set), so that images in the same cluster consist of the similar two-tone texture. In the second stage, we analyzed the fractal dimension of sub-bands derived from the images of prostatic biopsies. We adopted the Support Vector Machines as the classifier and used the leaving-one-out approach to estimate error rate. The present experimental results demonstrated 92.1% of accuracy for 50 medical cases and a set of 1000 pathological prostatic biopsy images.
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Basavanhally, Ajay. "Automated image-based detection and grading of lymphocytic infiltration in breast cancer histopathology." 2010. http://hdl.rutgers.edu/1782.2/rucore10001600001.ETD.000052094.
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Lin, Wei-chun, and 林韋群. "Prediction of Gleason grading for peripheral zone prostate cancer using multi-parametric magnetic resonance images." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/238qx3.
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碩士<br>國立交通大學<br>生醫工程研究所<br>105<br>Background: The clinical diagnosis of patients with prostate cancer relies on the physician’s judgment based on pathology texture of invasive biopsy. The decision of treatment options depends on the Gleason grade of biopsy and overall condition of the patient. So it is valuable to predict the histological grade using invasive slices from non-invasive medical images.
Methods: This study aims to predict whether the Gleason grading is higher than G4+3 or not from the magnetic resonance imaging (MRI) of peripheral zone prostate cancer to assist radiologists in finding lesions and provide treatment information. In this study, there are 46 patients consisting of 39 patients for training a mathematic model and 7 patients for testing the model. Each patient has three types of images, T2-weighted images, apparent diffusion coefficient, and diffusion-weighted images. A professional radiologist circles the lesion area and determines its Gleason grade for all the MRI images. For every lesion area, a number of subimages with the size of 25 * 25 were extracted. There were 145 training images and 20 test images for each type of images. We extracted 360 texture features from each image and there were 1080 features for a patent with three types of images. A set of informative features were selected by statistical analysis and an inheritable bi-objective combinatorial genetic algorithm with cooperation of support vector machine (SVM). A SVM-based model was established using the identified feature set for prediction of Gleason grade.
Results: A set of seven informative features of texture with cooperation of SVM was obtained. The prediction model achieved a training accuracy of 100% and a test accuracy of 80% where the test sensitivity and specificity were 66.6% and 90.9%, respectively.
Conclusion: The image calibration, image segmentation, feature extraction, feature selection, and parameter setting of SVM significantly affect the prediction performance. This study provides a detailed procedure of optimal feature selection and achieved a satisfactory result. Some test image with failed prediction reveals that the image has presented some significant cancer features or bleeding conditions resulting in an error judgment. The future work is to increase the number of training patients for advancing prediction performance.
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HUANG, BING-XUN, and 黃炳勳. "Relationship of the Queuine content of transfer ribonucleic acids to histopathological grading and survival in human lung cancer." Thesis, 1992. http://ndltd.ncl.edu.tw/handle/76989774843614746663.
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Vau, Nuno João Santos Sineiro de Oliveira. "Valor preditivo de marcadores de transição epitelial - mesenquimatosa, PTEN, ERG, Ki-67 e de estudo mutacional, na recorrência bioquímica de carcinoma da próstata tratado com cirurgia." Doctoral thesis, 2018. http://hdl.handle.net/10362/73895.
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Valor Preditivo de Marcadores de Transição Epitelial-‐Mesenquimatosa, PTEN, ERG, Ki67 e de Estudo Genético na Recorrência Bioquímica de Carcinoma da Próstata tratado com cirurgia
Introdução: O carcinoma da próstata apresenta uma elevada incidência e prevalência. A maioria dos carcinomas da próstata localizados são curáveis, com as opções terapêuticas disponíveis. Contudo, a recorrência da doença está associada a morbilidade, a mortalidade e a custos elevados. Como tal, é importante otimizar o tratamento da doença localizada. Uma das possibilidades para o fazer, passa por uma melhoria do nosso conhecimento, acerca dos factores preditivos. Um reconhecimento precoce de uma maior probabilidade de recorrência poderia levar a uma otimização da abordagem terapêutica dos tumores primários, nomeadamente através de estratégias que incluam intensificação terapêutica.
Material e Métodos: Numa amostra populacional constituída por doentes, com carcinoma da próstata localizado, e tratados com prostatectomia radical de intuito curativo, avaliámos o valor preditivo de factores clínicos, anatomopatológicos, imunohistoquímicos e genéticos. Utilizámos como “endpoint” a recorrência bioquímica (RBQ).
Resultados: Em 147 doentes, e após um seguimento, cuja mediana foi de 20 meses (4-‐55 meses), ocorreu RBQ em 15,6% dos casos. Na nossa amostra, o PSA pré-‐ operatório (p=0,02); o tipo de cirurgia (p=0,01); o score de Gleason da biópsia (p=0,004) e da lesão índice (P<0,001); a classificação de Epstein da biópsia (p=0,005), da peça (p=0,006), e da lesão índice (p<0,001); o número de fragmentos de biópsia envolvidos por tumor (p=0,05), a extensão do envolvimento tumoral nos fragmentos de biópsia, em milímetros (p=0,01) e percentualmente (p=0,02); a existência de áreas de diferenciação intraductal (p=0,003); a presença de padrão de terciário (p<0,001); a dimensão linear da lesão índice (p=0,005); a existência de margem cirúrgica positiva (p=0,05); a existência de extensão extraprostática (p=0,02); a invasão vascular (p=0,002); a invasão das vesículas seminais (p=0,01); o número de gânglios isolados em doentes submetidos a linfadenectomia (p=0,01); o estádio patológico referente ao tumor primário (p=0,02) e a pErda de expressão da caderina E (p<0,001), mostraram significância estatística relativamente à ocorrência de recorrência bioquímica. Por análise multivariável, apenas a existência de áreas de diferenciação intraductal (p=0,01), a classificação de Epstein da lesão índice (p<0,001), a invasão vascular (p=0,02) e o número de gânglios isolados em doentes submetidos a linfadenectomia (p=0,05), mantiveram a significância estatística, após ajuste para as outras variáveis. Os restantes biomarcadores associados à transição epitelial-‐mesenquimatosa (caderina N e vimentina), o PTEN, o Ki-‐67 e o ERG, na nossa amostra, e por análise univariável, não estão associados à ocorrência de RBQ. A expressão de SChLAP1, quer em tecido tumoral, quer em tecido não tumoral, também não está associado à ocorrência de RBQ.
Conclusões: O nosso trabalho confirma, na nossa população, o interesse preditivo de factores clínicos e anatomopatológicos normalmente associados a um comportamento biológico mais agressivo. Também sugere o interesse preditivo de alguns factores anatomopatológicos menos estudados. Por fim aponta para a possibilidade, de associação entre o fenómeno de transição epitelial e a ocorrência de RBQ.<br>Predictive value of epithelial-‐mesenchymal transition markers, PTEN, ERG, Ki67, and genetic analysis in biochemical recurrence of prostate cancer treated with surgery
Introduction: Prostate cancer is a contemporary health issue. It has a very high incidence and prevalence. The majority of patients with localized disease are cured with current standard therapeutic options. Nevertheless, disease recurrence is associated with morbidity, mortality and significant costs. It is, therefore, important to optimize therapeutic efficacy. One of the possibilities to achieve it, is through better understanding of predictive factors. Pinpointing in advance, the cases with worse prognosis, could allow a therapeutic adjustment, by adding adjuvant treatment.
Methods: In a clinical cohort study, we evaluated the predictive impact of several clinical, pathological and molecular factors in the development of biochemical recurrence (BCR), in patients with localized prostate cancer treated with radical prostatectomy.
Results: A total of 147 patients were included in our study. The median follow-‐up time was 20 months. BCR occurred in 15.6% of the patients. In univariate analysis, pre-‐operative PSA (p=0.02); the type of surgery (p=0.01); the Gleason score both in biopsy (p=0.004) and in the index lesion (p<0.001); the Epstein grading system in the biopsy (p=0.005), in the entire tumor (p=0.006), and in the index lesion (p<0.001); the number of positive cores in the biopsy (p=0.05), the maximum length of cancer in any one biopsy core (p=0.01) and the greatest percentage of cancer in any biopsy core (p=0.02); the presence of intraductal differentiation in the prostatic specimen (p=0.003); the presence of a minor high-‐grade pattern (p<0.001); the index lesion dimension (p=0.005); positive surgical margin (p=0.05); the existence of extra prostatic extension (p=0.02); vascular invasion (p=0.002); seminal vesicle invasion (p=0.01); the total number of lymph nodes retrieved in patients submitted to lymphadenectomy (p=0.01); T stage (p=0.02) and loss of E-‐Cadherine, were all predictive factors for BCR. In multivariate analysis, only the presence of intraductal differentiation (p=0.01), Epstein grading system in the index lesion (p<0.001), vascular invasion (p=0.02) and the total number of lymph nodes (p=0.05) remained independently predictive of BCR. The remaining epithelial-‐mesenchymal transition markers (N-‐Cadherine and Vimentine), PTEN, Ki-‐67 and ERG, were not predictive factors for BCR. Neither was SChLAP1 expression, both in tumoral and non-‐tumoral tissue.
Conclusions: Our study, in this population, confirms the predictive impact of many well-‐established predictive factors. It also implies, that other less known pathological factors might also have predictive importance. Finally, it suggest the existence of a link between epithelial-‐mesenchymal transition and BCR.
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LIN, FONG-YI, and 林峯儀. "Use Microfluidic Chips to Study the Effect of Blue Light Intensity Gradient on Fibroblasts and Lung Cancer Cells." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/8vjpd4.
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碩士<br>輔仁大學<br>物理學系碩士班<br>107<br>Collective cell migration is an important process involving wound healing, tissue development and so on. Recently, it was demonstrated that light gradient generated by a 473-nm diode-pumped solid state laser and a spatial light modulator induced the migration of lung cancer A549 cells, which may relate to the concentration of reactive oxygen species (ROS). Generally, cell migration induced by light intensity gradient depends on cell type and wavelength of light. However, most of these studies were done under a static condition such as culture dishes, which is different from in vivo dynamic circulation. To best mimic the physiological condition and to increase the expandability, a microfluidic system, including a cell-culture chip and a concentration-gradient chip, was designed and integrated with an auto-control system. By passing blue LED light through these chips, we can study the effect of blue light gradient on the migration of NIH/3T3 fibroblasts and lung cancer A549 cells. The relationship between ROS and cell migration was also investigated.
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Jiang, Runqing. "Impact of Geometric Uncertainties on Dose Calculations for Intensity Modulated Radiation Therapy of Prostate Cancer." Thesis, 2007. http://hdl.handle.net/10012/3570.
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IMRT uses non-uniform beam intensities within a radiation field to provide patient-specific dose shaping, resulting in a dose distribution that conforms tightly to the planning target volume (PTV). Unavoidable geometric uncertainty arising from patient repositioning and internal organ motion can lead to lower conformality index (CI), a decrease in tumor control probability (TCP) and an increase in normal tissue complication probability (NTCP). The CI of the IMRT plan depends heavily on steep dose gradients between the PTV and organ at risk (OAR). Geometric uncertainties reduce the planned dose gradients and result in a less steep or “blurred” dose gradient. The blurred dose gradients can be maximized by constraining the dose objective function in the static IMRT plan or by reducing geometric uncertainty during treatment with corrective verification imaging. Internal organ motion and setup error were evaluated simultaneously for 118 individual patients with implanted fiducials and MV electronic portal imaging (EPI). The Gaussian PDF is patient specific and group standard deviation (SD) should not be used for accurate treatment planning for individual patients. Frequent verification imaging should be employed in situations where geometric uncertainties are expected. The dose distribution including geometric uncertainties was determined from integration of the convolution of the static dose gradient with the PDF. Local maximum dose gradient (LMDG) was determined via optimization of dose objective function by manually adjusting DVH control points or selecting beam numbers and directions during IMRT treatment planning. EUDf is a useful QA parameter for interpreting the biological impact of geometric uncertainties on the static dose distribution. The EUDf has been used as the basis for the time-course NTCP evaluation in the thesis. Relative NTCP values are useful for comparative QA checking by normalizing known complications (e.g. reported in the RTOG studies) to specific DVH control points. For prostate cancer patients, rectal complications were evaluated from specific RTOG clinical trials and detailed evaluation of the treatment techniques. Treatment plans that did not meet DVH constraints represented additional complication risk. Geometric uncertainties improved or worsened rectal NTCP depending on individual internal organ motion within patient.
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Figueiredo, Teresa Leonor Isabel Dulce Fiel de Vasconcelos. "A influência dos antecedentes pessoais e ginecológicos no cancro da mama : um contributo da análise do gradiente no estudo da eficácia do rastreio manográfico." Doctoral thesis, 2014. http://hdl.handle.net/10400.14/20711.
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A mortalidade por cancro da mama permanece elevada em Portugal, pelo que no último Plano Oncológico Nacional, encontram-se conjuntamente definidos como dos objetivos prioritários, a sua redução aos 5 anos e o aumento da sobrevivência. Neste contexto, os programas de rastreio, utilizando mamografia como teste base, têm sido implementados, há pelo menos duas décadas, a nível mundial e em Portugal, para atingir esses objetivos. No Algarve, o rastreio registou, na 1ª volta, taxas de adesão inferiores a 60 %. Este facto, levanta questões às entidades organizadoras e respetivas estruturas de suporte, relativamente às formas de monitorização e melhoria do desempenho. Com esta investigação, pretendemos avaliar os indicadores de rendimento e a efetividade do Programa de Rastreio do Cancro da Mama no Algarve, de base populacional, organizado entre as estruturas de saúde pública, coordenadas pela Administração Regional de Saúde (ARS), em parceria com a Associação Oncológica do Algarve (AOA).
Recorrendo a Variáveis designadas por: Ativas (indicadores do processo de rastreio), Ambientais (Antecedentes Ginecológicos, Avaliação da Lesão, etc.) e Suplementares (identificadoras das unidades amostrais), relativas a 948 mulheres rastreadas ao cancro da mama, num universo de 17.000 mulheres entre os 50 e os 69 anos de idade, propõe-se uma abordagem à Análise do Gradiente através da metodologia HJ-BIPLOT. A amostra referente ao estudo foi retirada do rastreio realizado no Algarve entre Janeiro de 2007 e Dezembro 2008. (Idade, Peso, Freguesia, etc.) (identificadoras das unidades amostrais).
Assim, mediante a construção de variáveis latentes, foi possível detetar grupos de mulheres rastreadas nos quais se identificaram, através de gradientes, não só as tendências como as similaridades/dissimilaridades entre diferentes grupos da amostra rastreada. De forma sintética, julgamos ter sido possível assinalar meios de aferir a eficácia do rastreio mamográfico e, contribuir para a melhoria e/ou aperfeiçoamento de futuras triagens do cancro da mama.<br>Mortality from breast cancer remains high in Portugal, so the last Plan National Oncology, are jointly defined as the priority objectives, its reduction to 5 years and increased survival. In this context, screening programs using mammography-based test, have been implemented for at least two decades, worldwide and in Portugal, to achieve these goals. In the Algarve, the screening registered in the first round adherence rates lower than 60%. This fact, presents challenges to the organizing entities and the respective supporting structures regarding the monitoring and the performance improvement. With this investigation we pretend to evaluate the performance indicators and the efficiency of the population-based screening program, organized midst public health structures coordinated by the Regional Health Administration (ARS) and in partnership with the Algarve Oncology Association (AOA).
Therefore, we propose an approach to the Gradient Analysis through the HJ-BIPLOT methodology that allows the construction of Variables designated as Active (indicators of the screening process), Environmental (Gynaecologic history, Injury Assessment, etc.) and Supplemental (identifying sampling units) of the 948 women screened for breast cancer (age, weight, Town, etc.) (identifying the sample units). The sample concerning the study was taken from the screening held at the Algarve between January 2007 and December 2008, in a universe of 17.000 women with ages between 50 and 69 years.
Thereby, by constructing latent variables, it was possible to detect groups of screened women, in which were identified, through gradients, not only trends as the similarities / dissimilarities between different sample groups screened. In syntactic form, we thus judge that it is had been possible to point out means of measuring the effectiveness of mammography screening and contribute to the improvement and/or enhancement of future trials of breast cancer.