2,032 research outputs found

    Detection of osteoporosis in lumbar spine [L1-L4] trabecular bone: a review article

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    The human bones are categorized based on elemental micro architecture and porosity. The porosity of the inner trabecular bone is high that is 40-95% and the nature of the bone is soft and spongy where as the cortical bone is harder and is less porous that is 5 to 15%. Osteoporosis is a disease that normally affects women usually after their menopause. It largely causes mild bone fractures and further stages lead to the demise of an individual. This analysis is on the basis of bone mineral density (BMD) standards obtained through a variety of scientific methods experimented from different skeletal regions. The detection of osteoporosis in lumbar spine has been widely recognized as a promising way to frequent fractures. Therefore, premature analysis of osteoporosis will estimate the risk of the bone fracture which prevents life threats. This paper focuses on the advanced technology in imaging systems and fracture probability analysis of osteoporosis detection. The various segmentation techniques are explored to examine osteoporosis in particular region of the image and further significant attributes are extracted using different methods to classify normal and abnormal (osteoporotic) bones. The limitations of the reviewed papers are more in feature dimensions, lesser accuracy and expensive imaging modalities like computed tomography (CT), magnetic resonance imaging (MRI), and DEXA. To overcome these limitations it is suggested to have less feature dimensions, more accuracy and cost-effective imaging modality like X-ray. This is required to avoid bone fractures and to improve BMD with precision which further helps in the diagnosis of osteoporosis

    Focal Spot, Spring 1994

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    https://digitalcommons.wustl.edu/focal_spot_archives/1066/thumbnail.jp

    Reference values of the distal sensory median and ulnar nerves among newly hired workers

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    2021 Fall.Includes bibliographical references.Carpal tunnel syndrome (CTS) is the most common entrapment neuropathy in the upper extremity and more common among workers in industrial occupations than in the general population (Atroshi et al., 1999; Mattioli et al., 2009; Palmer, Harris, & Coggon, 2007). Because of the high prevalence of CTS in certain industries, some employers have implemented post-offer pre-placement screening programs using nerve conduction studies (NCS) to identify those at higher risk of developing CTS. NCS are commonly used to identify the median neuropathy characteristic of CTS by assessing the nerve conduction speed of the median nerve. There have been a number of retrospective and prospective cohort studies that have examined the relationship between NCS indicating median neuropathy among workers and the subsequent development of CTS (Werner et al., 2001; Franzblau et al., 2004; Gell et al., 2005; Silverstein et al., 2010; Dale et al., 2014). These studies have indicated that workers with NCS indicating median neuropathy across the carpal tunnel who were initially asymptomatic for CTS, eventually developed CTS at a statistically significant greater rate than workers with normal nerve studies. Some employers have used NCS to identify workers at higher risk of developing CTS and placing them into low hand-intensive work tasks to reduce the high prevalence of work-related CTS. To identify workers at higher risk, their NCS results are often compared to population-based reference values. However, many of these published reference values are limited by their small samples sizes and unsuitable statistical methodologies (Dillingham et al., 2016). Further, some researchers have questioned whether population-based reference values are representative of working populations, especially those in industries with a high prevalence of abnormal NCS (Dale, Gardner, Buckner-petty, Strickland, & Evanoff, 2016; Salerno et al., 1998). The purpose of this dissertation research was to (1) establish reference values for NCS outcomes of the distal upper extremity from a large sample (N=17,630) of newly hired manufacturing workers using novel statistical methods more appropriate for nerve conduction data, (2) investigate comorbid conditions associated with nerve conduction outcomes, and (3) determine the sensitivity and specificity of CTS symptoms for identifying workers with median mononeuropathy

    Bone Vibration Analysis as a Novel Screening Tool for Long Bone Fractures

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    The aim of this study is to reduce the number of X-ray scans taken to detect fractures, by developing a bone fracture screening system. When assessing a bone injury, doctors need to decide whether the injury has resulted in a fracture or a sprain so that they can provide appropriate treatments. The current way to differentiate between these is by an X-ray scan. In 2011, the 46,000 children attending Sheffield Children’s Hospital Emergency Department had 10,400 X-rays, mostly to help diagnose bone fractures. Roughly half the X-ray scans taken indicate that the injury is sprain. Unnecessary X-ray scan means raising costs and exposing patients to ionising radiation. Vibration analysis is a well-established technology for condition monitoring for defect detection in industries however; its use in the medical field is still evolving. In bone vibration analysis, periodic or aperiodic oscillations or oscillating signals are introduced, and subsequent responses are recorded followed by using mathematical methods to reach a conclusion. In this study, a computer-controlled mechanism induces a mild vibration and successive responses are recorded via a piezoelectric sensor. To demonstrate the method's feasibility, a preliminary study was carried out on five blocks of wood of different density, with the same dimensions. The tests indicated a significant reduction in the blocks' vibration frequency following their fracture. After obtaining National Health Services (NHS) Research Approval, appropriate number of bone vibration responses was recorded from adults’ wrists and children’s wrists and ankles who attended local hospitals following wrist or ankle injuries. Suitable signal processing and pattern recognition techniques were developed on the basis of vibration responses from bones at various stages to interpret the recorded signals. Data were acquired from healthy participants at a local school which were compared with the data acquired from hospital participants to verify the methods. Currently, this study differentiates around 80% of the injuries accurately. Additionally, both the data acquisition program and the device have been modified to improve the developed procedures. This study made some promising discoveries and the resulting techniques can be used for further explorations

    Focal Spot, Spring 1987

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    https://digitalcommons.wustl.edu/focal_spot_archives/1045/thumbnail.jp

    Bone fracture detection through X-ray using Edge detection Algorithms

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    Human beings are highly prone to bone fractures, to a great extent as an outcome of accidents or other factors such as bone cancer. Manual fracture detection takes a lengthy time and comes with a considerable chance of error. As a result, establishing a computer-based method to reduce fracture bone diagnosis time and risk of error is critical. The most common method for segmenting images based on sharp changes in intensity is edge detection. Sobel, Robert, Canny, Prewitt, and LoG (Laplacian of Gaussian) are some of the edge detection approaches that are examined for the study of bone fracture detection. The focal point of this paper is an endeavor to study, analyze and compare the Sobel, Canny, and Prewitt Techniques for detecting edges and identifying the fracture

    Focal Spot, Fall/Winter 1996

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    https://digitalcommons.wustl.edu/focal_spot_archives/1071/thumbnail.jp

    Mapping Trabecular Bone Fabric Tensor by in Vivo Magnetic Resonance Imaging

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    The mechanical competence of bone depends upon its quantity, structural arrangement, and chemical composition. Assessment of these factors is important for the evaluation of bone integrity, particularly as the skeleton remodels according to external (e.g. mechanical loading) and internal (e.g. hormonal changes) stimuli. Micro magnetic resonance imaging (µMRI) has emerged as a non-invasive and non-ionizing method well-suited for the repeated measurements necessary for monitoring changes in bone integrity. However, in vivo image-based directional dependence of trabecular bone (TB) has not been linked to mechanical competence or fracture risk despite the existence of convincing ex vivo evidence. The objective of this dissertation research was to develop a means of capturing the directional dependence of TB by assessing a fabric tensor on the basis of in vivo µMRI. To accomplish this objective, a novel approach for calculating the TB fabric tensor based on the spatial autocorrelation function was developed and evaluated in the presence of common limitations to in vivo µMRI. Comparisons were made to the standard technique of mean-intercept-length (MIL). Relative to MIL, ACF was identified as computationally faster by over an order of magnitude and more robust within the range of the resolutions and SNRs achievable in vivo. The potential for improved sensitivity afforded by isotropic resolution was also investigated in an improved µMR imaging protocol at 3T. Measures of reproducibility and reliability indicate the potential of images with isotropic resolution to provide enhanced sensitivity to orientation-dependent measures of TB, however overall reproducibility suffered from the sacrifice in SNR. Finally, the image-derived TB fabric tensor was validated through its relationship with TB mechanical competence in specimen and in vivo µMR images. The inclusion of trabecular bone fabric measures significantly improved the bone volume fraction-based prediction of elastic constants calculated by micro-finite element analysis. This research established a method for detecting TB fabric tensor in vivo and identified the directional dependence of TB as an important determinant of TB mechanical competence

    Design of a non-invasive device to measure bone strength recovery of distal radius fractures for use with HR-pQCT Imaging

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    Distal radius fractures are the most common bone injury in adults, with the majority occurring in postmenopausal women. Often these fractures result in painful healing defects, leading to extended treatment and even surgery. Currently, there is no clinical method to quantify the extent of bone healing beyond the limited capabilities of standard x-rays. The goal of this project is to develop a device, which can determine the strength of a healing fracture. This is achieved by applying a known bending load to the distal radius and measuring the displacement of the bone in High Resolution CT images. The device created was manufactured via 3D printing. Validation of device performance was performed using cadaver wrist models
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