1,720,965 research outputs found
From Pixels to Diagnosis: Applications of X-ray Virtual Histology in Clinical Pathology
No full textHistopathology is the medical discipline that studies the signs and characteristics of human disease processes in biological tissues. In the field of clinical diagnostics, the histopathological examination is a fundamental step in the process of defining the diagnosis, prognosis, and treatment plan. Despite the advancement of technology and the production of increasingly accurate and robust results, the two-dimensional information obtained through histopathology remains constrained by the sectioning plane. In contrast, X-ray virtual histology (XVH) represents an emerging imaging technique that produces high-resolution three-dimensional insights at the microscopic level, thereby overcoming the two-dimensional limitation of conventional histology. By leveraging the intrinsic characteristics of X-rays to capture comprehensive microarchitectural information, XVH eliminates the necessity for physical sectioning of the biological specimen, thereby preserving its structural integrity.
This thesis aims to apply synchrotron-based XVH to two of the most aggressive and heterogeneous cancer types, which are melanoma skin cancer and non-small cell lung cancer (NSCLC). The need for superior image resolution and contrast provided by synchrotron light is essential for detecting subtle morphological variations within tumors. These capabilities are of particular significance for the investigation of infiltrative characteristics that drive tumor invasion, a process that may require further examination to gain a comprehensive understanding of its underlying mechanisms. In this work, the invasive phenotypes of melanoma, such as melanocytic nests and pagetoid spread, were translated from histopathology to XVH for the first time. Moreover, three-dimensional reconstruction of some adverse prognostic factors in NSCLC, such as spread through air spaces (STAS), pleural invasion, and lympho-vascular invasion, demonstrates the superiority of XVH over other experimental techniques in terms of image quality and diagnostic potential. To effectively manage and analyze the large datasets generated by XVH, an important contribution of this thesis lies in the integration of advanced deep learning algorithms for the automated segmentation and classification of tumor tissues. This approach enhances the identification of critical features such as cellular architecture, tumor boundaries, and vasculature, thereby streamlining the interpretation of complex histological data. In addition to synchrotron-based imaging, this thesis also provides a preliminary exploration of the potential of laboratory-based X-ray virtual histology systems. By qualitatively comparing the performance of two phase-contrast X-ray imaging laboratories in Trieste, Italy, this study anticipates their potential to broaden access to XVH technology in both clinical and research environments where synchrotron resources are not readily available.
The overarching objective of this thesis is to advance the technical development of X-ray virtual histology while also enhancing its clinical relevance through close collaboration with medical professionals. This work aims to highlight the promising potential of X-ray virtual histology in cancer diagnostics and research by serving as a critical bridge between the technical advancements pursued by engineers and physicists and the clinical insights provided by medical doctors. Through this interdisciplinary approach, the thesis facilitates the translation of this innovative imaging technology into practical medical applications.Histopathology is the medical discipline that studies the signs and characteristics of human disease processes in biological tissues. In the field of clinical diagnostics, the histopathological examination is a fundamental step in the process of defining the diagnosis, prognosis, and treatment plan. Despite the advancement of technology and the production of increasingly accurate and robust results, the two-dimensional information obtained through histopathology remains constrained by the sectioning plane. In contrast, X-ray virtual histology (XVH) represents an emerging imaging technique that produces high-resolution three-dimensional insights at the microscopic level, thereby overcoming the two-dimensional limitation of conventional histology. By leveraging the intrinsic characteristics of X-rays to capture comprehensive microarchitectural information, XVH eliminates the necessity for physical sectioning of the biological specimen, thereby preserving its structural integrity.
This thesis aims to apply synchrotron-based XVH to two of the most aggressive and heterogeneous cancer types, which are melanoma skin cancer and non-small cell lung cancer (NSCLC). The need for superior image resolution and contrast provided by synchrotron light is essential for detecting subtle morphological variations within tumors. These capabilities are of particular significance for the investigation of infiltrative characteristics that drive tumor invasion, a process that may require further examination to gain a comprehensive understanding of its underlying mechanisms. In this work, the invasive phenotypes of melanoma, such as melanocytic nests and pagetoid spread, were translated from histopathology to XVH for the first time. Moreover, three-dimensional reconstruction of some adverse prognostic factors in NSCLC, such as spread through air spaces (STAS), pleural invasion, and lympho-vascular invasion, demonstrates the superiority of XVH over other experimental techniques in terms of image quality and diagnostic potential. To effectively manage and analyze the large datasets generated by XVH, an important contribution of this thesis lies in the integration of advanced deep learning algorithms for the automated segmentation and classification of tumor tissues. This approach enhances the identification of critical features such as cellular architecture, tumor boundaries, and vasculature, thereby streamlining the interpretation of complex histological data. In addition to synchrotron-based imaging, this thesis also provides a preliminary exploration of the potential of laboratory-based X-ray virtual histology systems. By qualitatively comparing the performance of two phase-contrast X-ray imaging laboratories in Trieste, Italy, this study anticipates their potential to broaden access to XVH technology in both clinical and research environments where synchrotron resources are not readily available.
The overarching objective of this thesis is to advance the technical development of X-ray virtual histology while also enhancing its clinical relevance through close collaboration with medical professionals. This work aims to highlight the promising potential of X-ray virtual histology in cancer diagnostics and research by serving as a critical bridge between the technical advancements pursued by engineers and physicists and the clinical insights provided by medical doctors. Through this interdisciplinary approach, the thesis facilitates the translation of this innovative imaging technology into practical medical applications
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Unveiling tumor invasiveness: enhancing cancer diagnosis with phase-contrast microtomography for 3D virtual histology
Full text linkMalignant diseases are characterized by a critical trait known as invasiveness, where tumor cells tend to spread from the primary tissue layer into surrounding healthy tissues and distant organs. Presently, histopathology offers essential insights for diagnosing, classifying, predicting outcomes, and guiding patient-specific treatments. However, histology offers two-dimensional data from chosen cutting planes. Although 3D histological volumes can be generated through serial sectioning or whole slide imaging, this method is laborious, may introduce processing artefacts, and lacks isotropic spatial resolution. These limitations pose a considerable challenge to accurate diagnoses, particularly when dealing with micro-infiltrating carcinomas. These lesions, characterized by minute infiltrations, demand a three-dimensional representation for comprehensive visualization, essential for precise identification and assessment. Emerging X-ray-based virtual histology technology offers three-dimensional visualization of soft-tissue specimens, enabling virtual slicing in any direction or at any point. This approach can assist in guiding tissue sectioning for optimal representation of tumor cross sections during histological analysis.Micro-infiltrating carcinomas from the breast, cervix, and thyroid were imaged using X-ray phase-contrast microtomography (PhC-μCT) at the Elettra synchrotron facility in Trieste, Italy. Comparative assessment of histological and CT slices by pathologists revealed that PhC-μCT aids in classifying lesions by highlighting distinct tissue components and, notably, identifying tissue invasion. Reviewing a volume image allows pathologists to trace the entire lesion, identifying invasion sites that might be overlooked in individual or serial histological sections. Consequently, this proposed method could complement pathologists’ tools, potentially enhancing diagnoses by minimizing under-staging and reducing false negative results
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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