Three-Dimensional In Vivo Imaging of the Murine Liver: A Micro-Computed Tomography-Based Anatomical Study

Various murine models are currently used to study acute and chronic pathological processes of the liver, and the efficacy of novel therapeutic regimens. The increasing availability of high-resolution small animal imaging modalities presents researchers with the opportunity to precisely identify and describe pathological processes of the liver. To meet the demands, the objective of this study was to provide a three-dimensional illustration of the macroscopic anatomical location of the murine liver lobes and hepatic vessels using small animal imaging modalities. We analysed micro-CT images of the murine liver by integrating additional information from the published literature to develop comprehensive illustrations of the macroscopic anatomical features of the murine liver and hepatic vasculature. As a result, we provide updated three-dimensional illustrations of the macroscopic anatomy of the murine liver and hepatic vessels using micro-CT. The information presented here provides researchers working in the field of experimental liver disease with a comprehensive, easily accessable overview of the macroscopic anatomy of the murine liver

Scanning Electron Microscopy of Corrosion Casting in Medicine

The aims of this review are: 1. to provide a bibliography of the publications that have used the corrosion casting technique; 2. to describe the advantages and limitations of the methodology; 3. to illustrate possible applications in the field of medicine, and 4. to highlight the significance of this method in the teaching of medical students. Thus, this paper is primarily focused on the scanning electron microscopical examination of vascular corrosion casts. The unsurpassed three-dimensionality of the corrosion casting technique compared to any other means stands out in particular. This can be especially useful when complex vascular-anatomical relationships are present. This applies not only to the portrayal of the modes of branching and varying vascular densities but also to regulatory arrangements, such as sphincters and arteriovenous anastomoses. Between 1966 and 1990, a total of 549 publications were found in the Medline literature data bank, containing the key words corrosion casting , microvascular cast , or vascular cast (as of August, 1990). Of those publications, most dealt with applications to experimental animals. By contrast, only 142 reports were mainly or partially concerned with human investigational material. The normal vascular system of nearly all organs, insofar as this is of direct medical relevance, has been largely resolved. In our opinion, one of the most important potential applications of the corrosion casting technique lies in the investigation of gastrointestinal, renal or hepatic ailments, which coincide with the reconstruction or rarefication of the vascular bed, e.g., in ulcers, ileitis terminalis, colitis ulcerosa, cirrhosis or glomerulonephritis

Segmentation and Deformable Modelling Techniques for a Virtual Reality Surgical Simulator in Hepatic Oncology

Liver surgical resection is one of the most frequently used curative therapies. However, resectability is problematic. There is a need for a computer-assisted surgical planning and simulation system which can accurately and efficiently simulate the liver, vessels and tumours in actual patients. The present project describes the development of these core segmentation and deformable modelling techniques. For precise detection of irregularly shaped areas with indistinct boundaries, the segmentation incorporated active contours - gradient vector flow (GVF) snakes and level sets. To improve efficiency, a chessboard distance transform was used to replace part of the GVF effort. To automatically initialize the liver volume detection process, a rotating template was introduced to locate the starting slice. For shape maintenance during the segmentation process, a simplified object shape learning step was introduced to avoid occasional significant errors. Skeletonization with fuzzy connectedness was used for vessel segmentation. To achieve real-time interactivity, the deformation regime of this system was based on a single-organ mass-spring system (MSS), which introduced an on-the-fly local mesh refinement to raise the deformation accuracy and the mesh control quality. This method was now extended to a multiple soft-tissue constraint system, by supplementing it with an adaptive constraint mesh generation. A mesh quality measure was tailored based on a wide comparison of classic measures. Adjustable feature and parameter settings were thus provided, to make tissues of interest distinct from adjacent structures, keeping the mesh suitable for on-line topological transformation and deformation. More than 20 actual patient CT and 2 magnetic resonance imaging (MRI) liver datasets were tested to evaluate the performance of the segmentation method. Instrument manipulations of probing, grasping, and simple cutting were successfully simulated on deformable constraint liver tissue models. This project was implemented in conjunction with the Division of Surgery, Hammersmith Hospital, London; the preliminary reality effect was judged satisfactory by the consultant hepatic surgeon

CT Scanning

Since its introduction in 1972, X-ray computed tomography (CT) has evolved into an essential diagnostic imaging tool for a continually increasing variety of clinical applications. The goal of this book was not simply to summarize currently available CT imaging techniques but also to provide clinical perspectives, advances in hybrid technologies, new applications other than medicine and an outlook on future developments. Major experts in this growing field contributed to this book, which is geared to radiologists, orthopedic surgeons, engineers, and clinical and basic researchers. We believe that CT scanning is an effective and essential tools in treatment planning, basic understanding of physiology, and and tackling the ever-increasing challenge of diagnosis in our society

High Resolution Maps of the Vasculature of An Entire Organ

The structure of vascular networks represents a great, unsolved problem in anatomy. Network geometry and topology differ dramatically from left to right and person to person as evidenced by the superficial venation of the hands and the vasculature of the retinae. Mathematically, we may state that there is no conserved topology in vascular networks. Efficiency demands that these networks be regular on a statistical level and perhaps optimal. We have taken the first steps towards elucidating the principles underlying vascular organization, creating the rst map of the hierarchical vasculature (above the capillaries) of an entire organ. Using serial blockface microscopy and fluorescence imaging, we are able to identify vasculature at 5 μm resolution. We have designed image analysis software to segment, align, and skeletonize the resulting data, yielding a map of the individual vessels. We transformed these data into a mathematical graph, allowing computationally efficient storage and the calculation of geometric and topological statistics for the network. Our data revealed a complexity of structure unexpected by theory. We observe loops at all scales that complicate the assignment of hierarchy within the network and the existence of set length scales, implying a distinctly non-fractal structure of components within

A comparative evaluation for liver segmentation from spir images and a novel level set method using signed pressure force function

Thesis (Doctoral)--Izmir Institute of Technology, Electronics and Communication Engineering, Izmir, 2013Includes bibliographical references (leaves: 118-135)Text in English; Abstract: Turkish and Englishxv, 145 leavesDeveloping a robust method for liver segmentation from magnetic resonance images is a challenging task due to similar intensity values between adjacent organs, geometrically complex liver structure and injection of contrast media, which causes all tissues to have different gray level values. Several artifacts of pulsation and motion, and partial volume effects also increase difficulties for automatic liver segmentation from magnetic resonance images. In this thesis, we present an overview about liver segmentation methods in magnetic resonance images and show comparative results of seven different liver segmentation approaches chosen from deterministic (K-means based), probabilistic (Gaussian model based), supervised neural network (multilayer perceptron based) and deformable model based (level set) segmentation methods. The results of qualitative and quantitative analysis using sensitivity, specificity and accuracy metrics show that the multilayer perceptron based approach and a level set based approach which uses a distance regularization term and signed pressure force function are reasonable methods for liver segmentation from spectral pre-saturation inversion recovery images. However, the multilayer perceptron based segmentation method requires a higher computational cost. The distance regularization term based automatic level set method is very sensitive to chosen variance of Gaussian function. Our proposed level set based method that uses a novel signed pressure force function, which can control the direction and velocity of the evolving active contour, is faster and solves several problems of other applied methods such as sensitivity to initial contour or variance parameter of the Gaussian kernel in edge stopping functions without using any regularization term