944 resultados para Biomedical imaging and visualization


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Doppler Optical Coherence Tomography (DOCT) is a biomedical imaging technique that allows simultaneous structural imaging and flow monitoring inside biological tissues and materials with spatial resolution in the micrometer scale. It has recently been applied to the characterization of microfluidic systems. Structural and flow imaging of novel microfluidics platforms for cytotoxicologic applications were obtained with a real-time, Near Infrared Spectral Domain DOCT system. Characteristics such as flow homogeneity in the chamber, which is one of the most important parameters for cell culture, are investigated. OCT and DOCT images were used to monitor flow inside a specific platform that is based on microchannel division for a better flow homogeneity. In particular, the evolution of flow profile at the transition between the microchannel structure and the chamber is studied.

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Simbrain is a visually-oriented framework for building and analyzing neural networks. It emphasizes the analysis of networks which control agents embedded in virtual environments, and visualization of the structures which occur in the high dimensional state spaces of these networks. The program was originally intended to facilitate analysis of representational processes in embodied agents, however it is also well suited to teaching neural networks concepts to a broader audience than is traditional for neural networks courses. Simbrain was used to teach a course at a new university, UC Merced, in its inaugural year. Experiences from the course and sample lessons are provided.

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The scaphoid is the most frequently fractured carpal bone. When investigating fixation stability, which may influence healing, knowledge of forces and moments acting on the scaphoid is essential. The aim of this study was to evaluate cartilage contact forces acting on the intact scaphoid in various functional wrist positions using finite element modeling. A novel methodology was utilized as an attempt to overcome some limitations of earlier studies, namely, relatively coarse imaging resolution to assess geometry, assumption of idealized cartilage thicknesses and neglected cartilage pre-stresses in the unloaded joint. Carpal bone positions and articular cartilage geometry were obtained independently by means of high resolution CT imaging and incorporated into finite element (FE) models of the human wrist in eight functional positions. Displacement driven FE analyses were used to resolve inter-penetration of cartilage layers, and provided contact areas, forces and pressure distribution for the scaphoid bone. The results were in the range reported by previous studies. Novel findings of this study were: (i) cartilage thickness was found to be heterogeneous for each bone and vary considerably between carpal bones; (ii) this heterogeneity largely influenced the FE results and (iii) the forces acting on the scaphoid in the unloaded wrist were found to be significant. As major limitations, accuracy of the method was found to be relatively low, and the results could not be compared to independent experiments. The obtained results will be used in a following study to evaluate existing and recently developed screws used to fix scaphoid fractures.

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Reconstruction of shape and intensity from 2D x-ray images has drawn more and more attentions. Previously introduced work suffers from the long computing time due to its iterative optimization characteristics and the requirement of generating digitally reconstructed radiographs within each iteration. In this paper, we propose a novel method which uses a patient-specific 3D surface model reconstructed from 2D x-ray images as a surrogate to get a patient-specific volumetric intensity reconstruction via partial least squares regression. No DRR generation is needed. The method was validated on 20 cadaveric proximal femurs by performing a leave-one-out study. Qualitative and quantitative results demonstrated the efficacy of the present method. Compared to the existing work, the present method has the advantage of much shorter computing time and can be applied to both DXA images as well as conventional x-ray images, which may hold the potentials to be applied to clinical routine task such as total hip arthroplasty (THA).

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Since approximately two thirds of epileptic patients are non-eligible for surgery, local axonal fiber transections might be of particular interest for them. Micrometer to millimeter wide synchrotron-generated X-ray beamlets produced by spatial fractionation of the main beam could generate such fiber disruptions non-invasively. The aim of this work was to optimize irradiation parameters for the induction of fiber transections in the rat brain white matter by exposure to such beamlets. For this purpose, we irradiated cortex and external capsule of normal rats in the antero-posterior direction with a 4 mm×4 mm array of 25 to 1000 µm wide beamlets and entrance doses of 150 Gy to 500 Gy. Axonal fiber responses were assessed with diffusion tensor imaging and fiber tractography; myelin fibers were examined histopathologically. Our study suggests that high radiation doses (500 Gy) are required to interrupt axons and myelin sheaths. However, a radiation dose of 500 Gy delivered by wide minibeams (1000 µm) induced macroscopic brain damage, depicted by a massive loss of matter in fiber tractography maps. With the same radiation dose, the damage induced by thinner microbeams (50 to 100 µm) was limited to their paths. No macroscopic necrosis was observed in the irradiated target while overt transections of myelin were detected histopathologically. Diffusivity values were found to be significantly reduced. A radiation dose ≤ 500 Gy associated with a beamlet size of < 50 µm did not cause visible transections, neither on diffusion maps nor on sections stained for myelin. We conclude that a peak dose of 500 Gy combined with a microbeam width of 100 µm optimally induced axonal transections in the white matter of the brain.

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Empirical evidence and theoretical studies suggest that the phenotype, i.e., cellular- and molecular-scale dynamics, including proliferation rate and adhesiveness due to microenvironmental factors and gene expression that govern tumor growth and invasiveness, also determine gross tumor-scale morphology. It has been difficult to quantify the relative effect of these links on disease progression and prognosis using conventional clinical and experimental methods and observables. As a result, successful individualized treatment of highly malignant and invasive cancers, such as glioblastoma, via surgical resection and chemotherapy cannot be offered and outcomes are generally poor. What is needed is a deterministic, quantifiable method to enable understanding of the connections between phenotype and tumor morphology. Here, we critically assess advantages and disadvantages of recent computational modeling efforts (e.g., continuum, discrete, and cellular automata models) that have pursued this understanding. Based on this assessment, we review a multiscale, i.e., from the molecular to the gross tumor scale, mathematical and computational "first-principle" approach based on mass conservation and other physical laws, such as employed in reaction-diffusion systems. Model variables describe known characteristics of tumor behavior, and parameters and functional relationships across scales are informed from in vitro, in vivo and ex vivo biology. We review the feasibility of this methodology that, once coupled to tumor imaging and tumor biopsy or cell culture data, should enable prediction of tumor growth and therapy outcome through quantification of the relation between the underlying dynamics and morphological characteristics. In particular, morphologic stability analysis of this mathematical model reveals that tumor cell patterning at the tumor-host interface is regulated by cell proliferation, adhesion and other phenotypic characteristics: histopathology information of tumor boundary can be inputted to the mathematical model and used as a phenotype-diagnostic tool to predict collective and individual tumor cell invasion of surrounding tissue. This approach further provides a means to deterministically test effects of novel and hypothetical therapy strategies on tumor behavior.

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Medical instrumentation used in diagnosis and treatment relies on the accurate detection and processing of various physiological events and signals. While signal detection technology has improved greatly in recent years, there remain inherent delays in signal detection/ processing. These delays may have significant negative clinical consequences during various pathophysiological events. Reducing or eliminating such delays would increase the ability to provide successful early intervention in certain disorders thereby increasing the efficacy of treatment. In recent years, a physical phenomenon referred to as Negative Group Delay (NGD), demonstrated in simple electronic circuits, has been shown to temporally advance the detection of analog waveforms. Specifically, the output is temporally advanced relative to the input, as the time delay through the circuit is negative. The circuit output precedes the complete detection of the input signal. This process is referred to as signal advance (SA) detection. An SA circuit model incorporating NGD was designed, developed and tested. It imparts a constant temporal signal advance over a pre-specified spectral range in which the output is almost identical to the input signal (i.e., it has minimal distortion). Certain human patho-electrophysiological events are good candidates for the application of temporally-advanced waveform detection. SA technology has potential in early arrhythmia and epileptic seizure detection and intervention. Demonstrating reliable and consistent temporally advanced detection of electrophysiological waveforms may enable intervention with a pathological event (much) earlier than previously possible. SA detection could also be used to improve the performance of neural computer interfaces, neurotherapy applications, radiation therapy and imaging. In this study, the performance of a single-stage SA circuit model on a variety of constructed input signals, and human ECGs is investigated. The data obtained is used to quantify and characterize the temporal advances and circuit gain, as well as distortions in the output waveforms relative to their inputs. This project combines elements of physics, engineering, signal processing, statistics and electrophysiology. Its success has important consequences for the development of novel interventional methodologies in cardiology and neurophysiology as well as significant potential in a broader range of both biomedical and non-biomedical areas of application.

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Detector uniformity is a fundamental performance characteristic of all modern gamma camera systems, and ensuring a stable, uniform detector response is critical for maintaining clinical images that are free of artifact. For these reasons, the assessment of detector uniformity is one of the most common activities associated with a successful clinical quality assurance program in gamma camera imaging. The evaluation of this parameter, however, is often unclear because it is highly dependent upon acquisition conditions, reviewer expertise, and the application of somewhat arbitrary limits that do not characterize the spatial location of the non-uniformities. Furthermore, as the goal of any robust quality control program is the determination of significant deviations from standard or baseline conditions, clinicians and vendors often neglect the temporal nature of detector degradation (1). This thesis describes the development and testing of new methods for monitoring detector uniformity. These techniques provide more quantitative, sensitive, and specific feedback to the reviewer so that he or she may be better equipped to identify performance degradation prior to its manifestation in clinical images. The methods exploit the temporal nature of detector degradation and spatially segment distinct regions-of-non-uniformity using multi-resolution decomposition. These techniques were tested on synthetic phantom data using different degradation functions, as well as on experimentally acquired time series floods with induced, progressively worsening defects present within the field-of-view. The sensitivity of conventional, global figures-of-merit for detecting changes in uniformity was evaluated and compared to these new image-space techniques. The image-space algorithms provide a reproducible means of detecting regions-of-non-uniformity prior to any single flood image’s having a NEMA uniformity value in excess of 5%. The sensitivity of these image-space algorithms was found to depend on the size and magnitude of the non-uniformities, as well as on the nature of the cause of the non-uniform region. A trend analysis of the conventional figures-of-merit demonstrated their sensitivity to shifts in detector uniformity. The image-space algorithms are computationally efficient. Therefore, the image-space algorithms should be used concomitantly with the trending of the global figures-of-merit in order to provide the reviewer with a richer assessment of gamma camera detector uniformity characteristics.

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PURPOSE Abundant expression of somatostatin receptors (sst) is a characteristic of neuroendocrine tumors (NET). Thus, radiolabeled somatostatin analogs have emerged as important tools for both in vivo diagnosis and therapy of NET. The two compounds most often used in functional imaging with positron emission tomography (PET) are (68)Ga-DOTATATE and (68)Ga-DOTATOC. Both analogs share a quite similar sst binding profile. However, the in vitro affinity of (68)Ga-DOTATATE in binding the sst subtype 2 (sst2) is approximately tenfold higher than that of (68)Ga-DOTATOC. This difference may affect their efficiency in detection of NET lesions, as sst2 is the predominant receptor subtype on gastroenteropancreatic NET. We thus compared the diagnostic value of PET/CT with both radiolabeled somatostatin analogs ((68)Ga-DOTATATE and (68)Ga-DOTATOC) in the same patients with gastroenteropancreatic NET. PATIENTS AND METHODS Twenty-seven patients with metastatic gastroenteropancreatic NET underwent (68)Ga-DOTATOC and (68)Ga-DOTATATE PET/CT as part of the workup before prospective peptide receptor radionuclide therapy (PRRT). The performance of both imaging methods was analyzed and compared for detection of individual lesions per patient and for eight defined body regions. A region was regarded as positive if at least one lesion was detected in that region. In addition, radiopeptide uptake in terms of the maximal standardized uptake value (SUV(max)) was compared for concordant lesions and renal parenchyma. RESULTS Fifty-one regions were found positive with both (68)Ga-DOTATATE and (68)Ga-DOTATOC. Overall, however, significantly fewer lesions were detected with (68)Ga-DOTATATE in comparison with (68)Ga-DOTATOC (174 versus 179, p < 0.05). Mean (68)Ga-DOTATATE SUV(max) across all lesions was significantly lower compared with (68)Ga-DOTATOC (16.9 ± 6.8 versus 22.1 ± 12.0, p < 0.01). Mean SUV(max) for renal parenchyma was not significantly different between (68)Ga-DOTATATE and (68)Ga-DOTATOC (12.6 ± 2.6 versus 12.6 ± 2.7). CONCLUSIONS (68)Ga-DOTATOC and (68)Ga-DOTATATE possess similar diagnostic accuracy for detection of gastroenteropancreatic NET lesions (with a potential advantage of (68)Ga-DOTATOC) despite their evident difference in affinity for sst2. Quite unexpectedly, maximal uptake of (68)Ga-DOTATOC tended to be higher than its (68)Ga-DOTATATE counterpart. However, tumor uptake shows high inter- and intraindividual variance with unpredictable preference of one radiopeptide. Thus, our data encourage the application of different sst ligands to enable personalized imaging and therapy of gastroenteropancreatic NET with optimal targeting of tumor receptors.

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BACKGROUND: Meningomyelocele (MM) is a common human birth defect. MM is a disorder of neural development caused by contributions from genes and environmental factors that result in the NTD and lead to a spectrum of physical and neurocognitive phenotypes. METHODS: A multidisciplinary approach has been taken to develop a comprehensive understanding of MM through collaborative efforts from investigators specializing in genetics, development, brain imaging, and neurocognitive outcome. Patients have been recruited from five different sites: Houston and the Texas-Mexico border area; Toronto, Canada; Los Angeles, California; and Lexington, Kentucky. Genetic risk factors for MM have been assessed by genotyping and association testing using the transmission disequilibrium test. RESULTS: A total of 509 affected child/parent trios and 309 affected child/parent duos have been enrolled to date for genetic association studies. Subsets of the patients have also been enrolled for studies assessing development, brain imaging, and neurocognitive outcomes. The study recruited two major ethnic groups, with 45.9% Hispanics of Mexican descent and 36.2% North American Caucasians of European descent. The remaining patients are African-American, South and Central American, Native American, and Asian. Studies of this group of patients have already discovered distinct corpus callosum morphology and neurocognitive deficits that associate with MM. We have identified maternal MTHFR 667T allele as a risk factor for MM. In addition, we also found that several genes for glucose transport and metabolism are potential risk factors for MM. CONCLUSIONS: The enrolled patient population provides a valuable resource for elucidating the disease characteristics and mechanisms for MM development.

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Purpose: To evaluate the clinical impact of the Varian Exact Couch on dose and volume coverage to targets and critical structures and tumor control probability (TCP) for 6-MV IMRT and Arc Therapy. Methods: Five clinical prostate patients were planned with both, 6-MV 8-field IMRT and 6-MV 2-field RapidArc using the Eclipse treatment planning system (TPS). These plans neglected treatment couch attenuation, as is standard clinical practice. Dose distributions were then recalculated in Eclipse with the inclusion of the Varian Exact Couch (imaging couch top) and the rails in varying configurations. The changes in dose and coverage were evaluated using the DVHs from each plan iteration. We used a tumor control probability (TCP) model to calculate losses in tumor control resulting from not accounting for the couch top and rails. We also verified dose measurements in a phantom. Results: Failure to account for the treatment couch and rails resulted in clinically unacceptable dose and volume coverage losses to the target for both IMRT and RapidArc. The couch caused average dose losses (relative to plans that ignored the couch) to the prostate of 4.2% and 2.0% for IMRT with the rails out and in, respectively, and 3.2% and 2.9% for RapidArc with the rails out and in, respectively. On average, the percentage of the target covered by the prescribed dose dropped to 35% and 84% for IMRT (rails out and in, respectively) and to 18% and 17% for RapidArc (rails out and in, respectively). The TCP was also reduced by as much as 10.5% (6.3% on average). Dose and volume coverage losses for IMRT plans were primarily due to the rails, while the imaging couch top contributed most to losses for RapidArc. Both the couch top and rails contribute to dose and coverage losses that can render plans clinically unacceptable. A follow-up study we performed found that the less attenuating unipanel mesh couch top available with the Varian Exact couch does not cause a clinically impactful loss of dose or coverage for IMRT but still causes an unacceptable loss for RapidArc. Conclusions: Both the imaging couch top and rails contribute to dose and coverage loss to a degree that, if included, would prevent the plan from meeting clinical planning criteria. Therefore, the imaging and mesh couch tops and rails should be accounted for in Arc Therapy and the imaging couch and rails only in IMRT treatment planning.

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Proton therapy has become an increasingly more common method of radiation therapy, with the dose sparing to distal tissue making it an appealing option, particularly for treatment of brain tumors. This study sought to develop a head phantom for the Radiological Physics Center (RPC), the first to be used for credentialing of institutions wishing to participate in clinical trials involving brain tumor treatment of proton therapy. It was hypothesized that a head phantom could be created for the evaluation of proton therapy treatment procedures (treatment simulation, planning, and delivery) to assure agreement between the measured dose and calculated dose within ±5%/3mm with a reproducibility of ±3%. The relative stopping power (RSP) and Hounsfield Units (HU) were measured for potential phantom materials and a human skull was cast in tissue-equivalent Alderson material (RLSP 1.00, HU 16) with anatomical airways and a cylindrical hole for imaging and dosimetry inserts drilled into the phantom material. Two treatment plans, proton passive scattering and proton spot scanning, were created. Thermoluminescent dosimeters (TLDs) and film were loaded into the phantom dosimetry insert. Each treatment plan was delivered three separate times. Each treatment plan passed our 5%/3mm criteria, with a reproducibility of ±3%. The hypothesis was accepted and the phantom was found to be suitable for remote audits of proton therapy treatment facilities.

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Cultural models of the domains healing and health are important in how people understand health and their behavior regarding it. The biomedicine model has been predominant in Western society. Recent popularity of holistic health and alternative healing modalities contrasts with the biomedical model and the assumptions upon which that model has been practiced. The holistic health movement characterizes an effort by health care providers and others such as nurses to expand the biomedical model and has often incorporated alternative modalities. This research described and compared the cultural models of healing of professional nurses and alternative healers. A group of nursing faculty who promote a holistic model were compared to a group of healers using healing touch. Ethnographic methods of participant observation, free listing and pile sort were used. Theoretical sampling in the free listings reached saturation at 18 in the group of nurses and 21 in the group of healers. Categories consistent for both groups emerged from the data. These were: physical, mental, attitude, relationships, spiritual, self management, and health seeking including biomedical and alternative resources. The healers had little differentiation between the concepts health and healing. The nurses, however, had more elements in self management for health and in health seeking for healing. This reflects the nurse's role in facilitating the shift in locus of responsibility between health and healing. The healers provided more specific information regarding alternative resources. The healer's conceptualization of health was embedded in a spiritual belief system and contrasted dramatically with that of biomedicine. The healer's models also contrasted with holistic health in the areas of holism, locus of responsibility, and dealing with uncertainty. The similarity between the groups and their dissimilarity to biomedicine suggest a larger cultural shift in beliefs regarding health care. ^

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We present a case of a ruptured abdominal aortic aneurysm (AAA) with ambiguous accessory findings on post-mortem computed-tomography (PMCT), post-mortem magnetic resonance (PMMR) imaging, and PMCT-angiography (PMCTA) suggestive of thoracic aortic dissection. The diagnosis of ruptured AAA was confirmed by autopsy; however, there was no aortic dissection. The imaging findings that mimicked the presence of aortic dissection might have been an atypical presentation of post-mortem clotting or sedimentation. This case is an ideal example to illustrate benefits, limitations, and challenges of post-mortem cross-sectional imaging. It serves as a reminder that both, training as well as correlation of imaging findings with autopsy are fundamental to improve our understanding of radiologic findings on post-mortem cross-sectional imaging.

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Post-mortem MR (PMMR) imaging is a powerful diagnostic tool with a wide scope in forensic radiology. In the past 20 years, PMMR has been used as both an adjunct and an alternative to autopsy. The role of PMMR in forensic death investigations largely depends on the rules and habits of local jurisdictions, availability of experts, financial resources, and individual case circumstances. PMMR images are affected by post-mortem changes, including position-dependent sedimentation, variable body temperature and decomposition. Investigators must be familiar with the appearance of normal findings on PMMR to distinguish them from disease or injury. Coronal whole-body images provide a comprehensive overview. Notably, short tau inversion–recovery (STIR) images enable investigators to screen for pathological fluid accumulation, to which we refer as “forensic sentinel sign”. If scan time is short, subsequent PMMR imaging may be focussed on regions with a positive forensic sentinel sign. PMMR offers excellent anatomical detail and is especially useful to visualize pathologies of the brain, heart, subcutaneous fat tissue and abdominal organs. PMMR may also be used to document skeletal injury. Cardiovascular imaging is a core area of PMMR imaging and growing evidence indicates that PMMR is able to detect ischaemic injury at an earlier stage than traditional autopsy and routine histology. The aim of this review is to present an overview of normal findings on forensic PMMR, provide general advice on the application of PMMR and summarise the current literature on PMMR imaging of the head and neck, cardiovascular system, abdomen and musculoskeletal system.