128 research outputs found

    Bacteria-targeted infection imaging:Towards a faster diagnosis of bacterial infection

    Get PDF
    Bacteriële infecties vormen een veelvoorkomende en grote bedreiging voor de gezondheid van de mens. Ze zijn verantwoordelijk voor ernstige morbiditeit en mortaliteit onder patiënten. De definitieve diagnose van infectie kan alleen worden verkregen via microbiologische kweken en moleculaire detectietechnieken, wat vaak tijdrovend is. Bovendien is het soms niet mogelijk om geschikte biopten of kweekmateriaal te verkrijgen, waardoor het stellen van de juiste diagnose zeer uitdagend kan zijn. Deze problemen kunnen mogelijk omzeild worden met behulp van bacterie-specifieke beeldvormingstechnieken. Helaas zijn de huidige beeldvormende technieken om infectieziekten te diagnosticeren niet in staat om een bacteriële infectie te onderscheiden van een steriele ontsteking. Nieuwe beeldvormende technieken zijn daarom dringend nodig voor een snelle, nauwkeurige en bij voorkeur real-time diagnose van bacteriële infecties. Dit proefschrift beschrijft de ontwikkeling van nieuwe bacterie-gerichte beeldvormingstechnieken met een focus op het gebruik van fluorescente moleculen die specifiek aan bacteriën binden. De resultaten laten zien dat fluorescente beeldvorming van bacteriële infecties geschikt is voor toepassing op geëxplanteerde materialen, tijdens artroscopie of bronchoscopie, of intra-operatief. Samenvattend kan geconcludeerd worden dat bacterie-gerichte beeldvormingstechnieken goed toepasbaar zijn voor een snellere diagnose van bacteriële infecties.Bacterial infections occur frequently and are a major threat to human health, causing high morbidity and mortality all over the world. For adequate treatment of infections, a rapid and precise diagnosis is imperative. Presently, this is achieved via microbiological culture and molecular detection, which are often time-consuming processes. Moreover, it is not always possible to obtain appropriate material for culturing, which complicates the diagnostic process. Therefore, the PhD research described in this thesis was aimed at exploring imaging-based techniques for faster and preferably real-time diagnosis of infectious diseases, and for rapid distinction of bacterial infection from sterile inflammation. To this end, the development of new bacteria-targeted imaging modalities was reviewed with a special focus on bacteria-targeted imaging with fluorescent tracers. Subsequently, the possible use of different tracers for infection imaging was experimentally explored. The results show that imaging with fluorescent bacteria-targeted tracers can be readily applied to detect infection ex vivo, by arthroscopy or bronchoscopy, or intra-operatively. Altogether, it is concluded that bacteria-targeted fluorescence imaging approaches may allow faster, real-time diagnosis of bacterial infections

    Infrared hyperspectral imaging for point-of-care wound assessment

    Get PDF
    Wound healing assessment and management are both important in ensuring a correct healing sequence. Most of these assessment techniques involve simple observation with the naked eye, which causes two main issues: the parameters assessed are highly subjective, and they rely upon the knowledge and experience of a trained medical professional. Any failure or incorrect management can result in further complications and even fatality, therefore quantitative wound assessment techniques are the next step towards a more accessible and reliable wound management strategy. Current research in this field is focused on utilising non-invasive imaging techniques, mainly within the visible and infrared (IR) range, to identify the biological and chemical changes during the wound healing process. Any abnormalities can then be identified earlier to aid in the correct diagnosis and treatment of the wound. Technologies that utilise concepts of non-contact imaging, such as optical imaging and spectroscopy can be used to obtain spatial and spectral maps of biomarkers, which provide valuable information on the wound (e.g., precursors to improper healing or delineate viable and necrotic tissue). This work extends this research further by investigating two different imaging modalities, Negative Contrast Imaging (NCI), along with Spatial Frequency Domain Imaging (SFDI) for the applications of point of care wound assessment. Intelligent data analysis algorithms, in the form of k-means clustering and principal component analysis were applied to spectral data, collected from wound biopsies as part of a previous study, highlighting the ability to diagnose wound healing status from the contrast of spectral information, which is not reliant upon a subjective clinical diagnosis. These methods provided the motivation for a larger cell culture trauma study, in which the NCI was utilised to obtain spectral reflectance maps across a 2.5- 3.5 μm wavelength region of both healthy and traumatised human epidermal fibroblasts, induced via chemical assays. Using the same intelligent analysis tools, along with pre-processing methods including spectral derivatives, the resulting clusters can be utilised as a diagnostic tool for the assessment of cellular health and were quantifiable metrics were defined to compare the different analysis methods Near infrared (NIR) methodologies were also investigated, with two areas of SFDI identified for further advancements. Current SFDI acquisition and optical property parameter recovery is performed via a pixel-wise process, generating large amounts of data and a high computational burden for parameter recovery. Data reduction, through the application of Compressive Sensing (CS) at both the image acquisition and data analysis stages provided up to a 90% reduction in data, whilst maintaining <10% error in recovered absorption and reduced scattering optical maps. This pixel-wise methodology also affects the forward modelling and inverse problem (imaging), based upon the diffusion approximation or Monte-Carlo methods due to their pixel-independent nature. NIRFAST, an existing FEM based NIR modelling tool, was adapted to produce pixel-dependent forward modelling for heterogenic samples, providing a mechanism towards a pixel dependent SFDI image modelling and parameter recovery system

    Desarrollo de un modelo inverso luz-tejido aplicado al procesamiento de imágenes multiespectrales para la caracterización de la formación y seguimiento al tratamiento de úlceras cutáneas causadas por Leishmaniasis en hámsteres dorados

    Get PDF
    Latinoamérica junto a otros lugares del mundo cuentan con regiones tropicales, de las cuales emergen múltiples enfermedades. La Leishmaniasis cutánea (LC) es una de las patologías más comunes que atacan a las poblaciones de estas zonas, generando una úlcera y dejando marcas de por vida. El difícil acceso a una atención médica apropiada de las poblaciones afectadas plantea la necesidad de nuevos instrumentos y técnicas que faciliten el diagnóstico y seguimiento a tratamientos de esta enfermedad. El desarrollo de esta tesis de maestría es parte del proyecto de investigación “Desarrollo y evaluación de un sistema portátil no invasivo basado en imágenes multiespectrales para el diagnóstico y seguimiento de tratamiento de úlceras cutáneas causadas por Leishmaniasis” registrado en Colciencias con el código 57186. Esta tesis de maestría busca definir un modelo inverso de interacción luz-tejido, que permita entender los fenómenos que ocurren en la piel de hámsteres dorados debido a úlceras causadas por Leishmaniasis, así como los cambios en la úlcera una vez se aplica un tratamiento. Los modelos inversos de interacción luz-tejido buscan estimar el comportamiento de los componentes biológicos en un tejido blando como la piel. Para ello se parte de un modelo matemático directo, que para esta tesis de maestría se plantea como un modelo de 3 capas que incluya epidermis, dermis e hipodermis; a partir de firmas espectrales adquiridas sobre piel sana, borde de la úlcera y centro de la úlcera capturados desde hámsteres con LC, se buscará estimar los principales componentes de la piel, tanto durante la transición de la enfermedad como en la aplicación y seguimiento al tratamiento. Finalmente se realiza el seguimiento al tratamiento de 10 hámsteres con Leishmaniasis Brasiliensis concluyendo cuáles de los parámetros adquiridos por medio del modelo inverso, son de mayor utilidad para la diferenciación de los tejido

    Mobile Wound Assessment and 3D Modeling from a Single Image

    Get PDF
    The prevalence of camera-enabled mobile phones have made mobile wound assessment a viable treatment option for millions of previously difficult to reach patients. We have designed a complete mobile wound assessment platform to ameliorate the many challenges related to chronic wound care. Chronic wounds and infections are the most severe, costly and fatal types of wounds, placing them at the center of mobile wound assessment. Wound physicians assess thousands of single-view wound images from all over the world, and it may be difficult to determine the location of the wound on the body, for example, if the wound is taken at close range. In our solution, end-users capture an image of the wound by taking a picture with their mobile camera. The wound image is segmented and classified using modern convolution neural networks, and is stored securely in the cloud for remote tracking. We use an interactive semi-automated approach to allow users to specify the location of the wound on the body. To accomplish this we have created, to the best our knowledge, the first 3D human surface anatomy labeling system, based off the current NYU and Anatomy Mapper labeling systems. To interactively view wounds in 3D, we have presented an efficient projective texture mapping algorithm for texturing wounds onto a 3D human anatomy model. In so doing, we have demonstrated an approach to 3D wound reconstruction that works even for a single wound image

    Integrated navigation and visualisation for skull base surgery

    Get PDF
    Skull base surgery involves the management of tumours located on the underside of the brain and the base of the skull. Skull base tumours are intricately associated with several critical neurovascular structures making surgery challenging and high risk. Vestibular schwannoma (VS) is a benign nerve sheath tumour arising from one of the vestibular nerves and is the commonest pathology encountered in skull base surgery. The goal of modern VS surgery is maximal tumour removal whilst preserving neurological function and maintaining quality of life but despite advanced neurosurgical techniques, facial nerve paralysis remains a potentially devastating complication of this surgery. This thesis describes the development and integration of various advanced navigation and visualisation techniques to increase the precision and accuracy of skull base surgery. A novel Diffusion Magnetic Resonance Imaging (dMRI) acquisition and processing protocol for imaging the facial nerve in patients with VS was developed to improve delineation of facial nerve preoperatively. An automated Artificial Intelligence (AI)-based framework was developed to segment VS from MRI scans. A user-friendly navigation system capable of integrating dMRI and tractography of the facial nerve, 3D tumour segmentation and intraoperative 3D ultrasound was developed and validated using an anatomically-realistic acoustic phantom model of a head including the skull, brain and VS. The optical properties of five types of human brain tumour (meningioma, pituitary adenoma, schwannoma, low- and high-grade glioma) and nine different types of healthy brain tissue were examined across a wavelength spectrum of 400 nm to 800 nm in order to inform the development of an Intraoperative Hypserpectral Imaging (iHSI) system. Finally, functional and technical requirements of an iHSI were established and a prototype system was developed and tested in a first-in-patient study

    Histological evaluation of surgical experiments in animal models

    Get PDF
    Introduction: The dissertation is based on six studies that focus on the application of quantitative histology in animal model experiments. It includes a presentation of virtual microscopy procedures and image field sampling strategies, mapping changes in the microscopic structure of ovine and porcine carotid segments and their comparison with human coronary arteries and internal thoracic arteries, vascularization assessment in a mouse model of lymphoma xenografts (PDX), the effect of hyperbaric oxygen therapy on type III collagen production and on vascularization in a skin wound in a Zucker Diabetic Fatty rat. Methods: The review article about virtual microscopy was focused on an example of sampling images from various areas of quantitative histology. In other studies, histologically processed sections were stained with a variety of methods for vascular wall construction, cell infiltration (orcein, picrosirius red, Verhoeff's hematoxylin and green trichrome, Gill's hematoxylin, alcian blue) and immunohistochemical antigen detection (α-smooth muscle actin, neurofilament protein, CD-31, von Willebrand factor). Using unbiased sampling and stereological methods, we quantified the area fraction of components (elastin, collagen, smooth muscle actin and chondroitin sulfate) using a stereological grid...Úvod: Dizertační práce je založena na šesti studiích, které se zaměřují na uplatnění kvantitativní histologie v hodnocení experimentů u zvířecích modelů. Zahrnuje představení postupů virtuální mikroskopie a strategií vzorkování obrazových polí, mapování změn mikroskopické struktury segmentů ovčích a prasečích krkavic a jejich porovnání s lidskými koronárními cévami a arteria thoracica interna, hodnocení vaskularizace u myšího modelu s xenografty lymfomů (PDX), vliv hyperbarické oxygenoterapie na tvorbu kolagenu typu III a na vaskularizaci v kožní ráně u Zucker Diabetic Fatty potkana. Metody: Přehledový článek o virtuální mikroskopii byl zaměřen na ukázku příkladu vzorkování snímků z různých oblastí kvantitativní histologie. V ostatních studiích byly histologicky zpracované řezy barvené škálou metod zaměřených na stavbu cévní stěny, a buněčné osídlení (orcein, pikrosiriová červeň, Verhoeffův hematoxylin a zelený trichrom, Gillův hematoxylin, alcianová modř) a imunohistochemickým průkazem antigenů (α-hladký svalový aktin, neurofilamentový protein, CD-31, von Willebrandův faktor). Pomocí nevychýleného vzorkování a stereologických metod jsme kvantifikovali plošné podíly složek (elastin, kolagen, hladkosvalový aktin a chondroitinsulfát) použitím stereologické bodové mřížky; dvourozměrnou hustotu...Ústav histologie a embryologieLékařská fakulta v PlzniFaculty of Medicine in Pilse

    Point-of-Care Detection Devices for Healthcare

    Get PDF
    With recent technological advances in multiple research fields such as materials science, micro-/nano-technology, cellular and molecular biology, bioengineering and the environment, much attention is shifting toward the development of new detection tools that not only address needs for high sensitivity and specificity but fulfil economic, environmental, and rapid point-of-care needs for groups and individuals with constrained resources and, possibly, limited training. Miniaturized fluidics-based platforms that precisely manipulate tiny body fluid volumes can be used for medical, healthcare or even environmental (e.g., heavy metal detection) diagnosis in a rapid and accurate manner. These new detection technologies are potentially applicable to different healthcare or environmental issues, since they are disposable, inexpensive, portable, and easy to use for the detection of human diseases or environmental issues—especially when they are manufactured based on low-cost materials, such as paper. The topics in this book (original and review articles) would cover point-of-care detection devices, microfluidic or paper-based detection devices, new materials for making detection devices, and others

    System Designs for Diabetic Foot Ulcer Image Assessment

    Get PDF
    For individuals with type 2 diabetes, diabetic foot ulcers represent a significant health issue and the wound care cost is quite high. Currently, clinicians and nurses mainly base their wound assessment on visual examination of wound size and the status of the wound tissue. This method is potentially inaccurate for wound assessment and requires extra clinical workload. In view of the prevalence of smartphones with high resolution digital camera, assessing wound healing by analyzing of real-time images using the significant computational power of today’s mobile devices is an attractive approach for managing foot ulcers. Alternatively, the smartphone may be used just for image capture and wireless transfer to a PC or laptop for image processing. To achieve accurate foot ulcer image assessment, we have developed and tested a novel automatic wound image analysis system which accomplishes the following conditions: 1) design of an easy-to-use image capture system which makes the image capture process comfortable for the patient and provides well-controlled image capture conditions; 2) synthesis of efficient and accurate algorithms for real-time wound boundary determination to measure the wound area size; 3) development of a quantitative method to assess the wound healing status based on a foot ulcer image sequence for a given patient and 4) design of a wound image assessment and management system that can be used both in the patient’s home and clinical environment in a tele-medicine fashion. In our work, the wound image is captured by the camera on the smartphone while the patient’s foot is held in place by an image capture box, which is specially design to aid patients in photographing ulcers occurring on the sole of their feet. The experimental results prove that our image capture system guarantees consistent illumination and a fixed distance between the foot and camera. These properties greatly reduce the complexity of the subsequent wound recognition and assessment. The most significant contribution of our work is the development of five different wound boundary determination approaches based on different computer vision algorithms. The first approach employs the level set algorithm to determine the wound boundary directly based on a manually set initial curve. The second and third approaches are the mean-shift segmentation based methods augmented by foot outline detection and analysis. These two approaches have been shown to be efficient to implement (especially on smartphones), prior-knowledge independent and able to provide reasonably accurate wound segmentation results given a set of well-tuned parameters. However, this method suffers from the lack of self-adaptivity due to the fact that it is not based on machine learning. Consequently, a two-stage Support Vector Machine (SVM) binary classifier based wound recognition approach is developed and implemented. This approach consists of three major steps 1) unsupervised super-pixel segmentation, 2) feature descriptor extraction for each super-pixel and 3) supervised classifier based wound boundary determination. The experimental results show that this approach provides promising performance (sensitivity: 73.3%, specificity: 95.6%) when dealing with foot ulcer images captured with our image capture box. In the third approach, we further relax the image capture constraints and generalize the application of our wound recognition system by applying the conditional random field (CRF) based model to solve the wound boundary determination. The key modules in this approach are the TextonBoost based potential learning at different scales and efficient CRF model inference to find the optimal labeling. Finally, the standard K-means clustering algorithm is applied to the determined wound area for color based wound tissue classification. To train the models used in the last two approaches, as well as to evaluate all three methods, we have collected about 100 wound images at the wound clinic in UMass Medical School by tracking 15 patients for a 2-year period, following an IRB approved protocol. The wound recognition results were compared with the ground truth generated by combining clinical labeling from three experienced clinicians. Specificity and sensitivity based measures indicate that the CRF based approach is the most reliable method despite its implementation complexity and computational demands. In addition, sample images of Moulage wound simulations are also used to increase the evaluation flexibility. The advantages and disadvantages of three approaches are described. Another important contribution of this work has been development of a healing score based mechanism for quantitative wound healing status assessment. The wound size and color composition measurements were converted to a score number ranging from 0-10, which indicates the healing trend based on comparisons of subsequent images to an initial foot ulcer image. By comparing the result of the healing score algorithm to the healing scores determined by experienced clinicians, we assess the clinical validity of our healing score algorithm. The level of agreement of our healing score with the three assessing clinicians was quantified by using the Kripendorff’s Alpha Coefficient (KAC). Finally, a collaborative wound image management system between the PC and smartphone was designed and successfully applied in the wound clinic for patients’ wound tracking purpose. This system is proven to be applicable in clinical environment and capable of providing interactive foot ulcer care in a telemedicine fashion

    High Performance Functional Bio-based Polymers for Skin-contact Products

    Get PDF
    Beauty masks, diapers, wound dressings, wipes, protective clothes and biomedical products: all these high-value and/or large-volume products must be highly compatible with human skin and they should have specific functional properties, such as anti-microbial, anti-inflammatory and anti-oxidant properties. They are currently partially or totally produced using fossil-based sources, with evident issues linked to their end of life, as their waste generates an increasing environmental concern. On the contrary, biopolymers and active biomolecules from biobased sources could be used to produce new materials that are highly compatible with the skin and also biodegradable. The final products can be obtained by exploiting safe and smart nanotechnologies such as the extrusion of bionanocomposites and electrospinning/electrospray, as well as innovative surface modification and control methodologies. For all these reasons, recently, many researchers, such as those involved in the European POLYBIOSKIN project activities, have been working in the field of biomaterials with anti-microbial, anti-inflammatory and anti-oxidant properties, as well as biobased materials which are renewable and biodegradable. The present book gathered research and review papers dedicated to materials and technologies for high-performance products where the attention paid to health and environmental impact is efficiently integrated, considering both the skin-compatibility of the selected materials and their source/end of life
    corecore