Heteroskedasticity-robust estimation of means

The properties of the usual one-sample T-statistic under nonnormal universes are investigated using Edgeworth expansions, and the findings reinforce the observations made by many authors in the past;Sufficient conditions for combining two independent unbiased estimators of a common mean in order to obtain a uniformly better (in variance sense) unbiased estimator is given. An upper bound for the inefficiency of such an estimator is also presented using a Kantorovich inequality;Heteroskedasticity-robust test procedures for the one-sample and two-sample problems are developed. An unbiased estimator of the variance of the ordinary least squares estimator of the slope parameter of a heteroskedastic simple linear regression model without intercept is given and performance of this estimator is assessed using Monte-Carlo simulations

Nonrigid registration of three-dimensional ultrasound and magnetic resonance images of the carotid arteries

Atherosclerosis at the carotid bifurcation can result in cerebral emboli, which in turn can block the blood supply to the brain causing ischemic strokes. Noninvasive imaging tools that better characterize arterial wall, and atherosclerotic plaque structure and composition may help to determine the factors which lead to the development of unstable lesions, and identify patients at risk of plaque disruption and stroke. Carotid magnetic resonance (MR) imaging allows for the characterization of carotid vessel wall and plaque composition, the characterization of normal and pathological arterial wall, the quantification of plaque size, and the detection of plaque integrity. On the other hand, various ultrasound (US) measurements have also been used to quantify atherosclerosis, carotid stenosis, intima-media thickness, total plaque volume, total plaque area, and vessel wall volume. Combining the complementary information provided by 3D MR and US carotid images may lead to a better understanding of the underlying compositional and textural factors that define plaque and wall vulnerability, which may lead to better and more effective stroke prevention strategies and patient management. Combining these images requires nonrigid registration to correct the nonlinear misalignments caused by relative twisting and bending in the neck due to different head positions during the two image acquisition sessions. The high degree of freedom and large number of parameters associated with existing nonrigid image registration methods causes several problems including unnatural plaque morphology alteration, high computational complexity, and low reliability. Thus, a twisting and bending model was used with only six parameters to model the normal movement of the neck for nonrigid registration. The registration technique was evaluated using 3D US and MR carotid images at two field strengths, 1.5 and 3.0 T, of the same subject acquired on the same day. The mean registration error between the segmented carotid artery wall boundaries in the target US image and the registered MR images was calculated using a distance-based error metric after applying a twisting and bending model based nonrigid registration algorithm. An average registration error of 1.4 +/- 0.3 mm was obtained for 1.5 T MR and 1.5 +/- 0.4 mm for 3.0 T MR, when registered with 3D US images using the nonrigid registration technique presented in this paper. Visual inspection of segmented vessel surfaces also showed a substantial improvement of alignment with this nonrigid registration technique compared to rigid registration

Comparison of quality control methods for automated diffusion tensor imaging analysis pipelines

© 2019 Haddad et al. The processing of brain diffusion tensor imaging (DTI) data for large cohort studies requires fully automatic pipelines to perform quality control (QC) and artifact/outlier removal procedures on the raw DTI data prior to calculation of diffusion parameters. In this study, three automatic DTI processing pipelines, each complying with the general ENIGMA framework, were designed by uniquely combining multiple image processing software tools. Different QC procedures based on the RESTORE algorithm, the DTIPrep protocol, and a combination of both methods were compared using simulated ground truth and artifact containing DTI datasets modeling eddy current induced distortions, various levels of motion artifacts, and thermal noise. Variability was also examined in 20 DTI datasets acquired in subjects with vascular cognitive impairment (VCI) from the multi-site Ontario Neurodegenerative Disease Research Initiative (ONDRI). The mean fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were calculated in global brain grey matter (GM) and white matter (WM) regions. For the simulated DTI datasets, the measure used to evaluate the performance of the pipelines was the normalized difference between the mean DTI metrics measured in GM and WM regions and the corresponding ground truth DTI value. The performance of the proposed pipelines was very similar, particularly in FA measurements. However, the pipeline based on the RESTORE algorithm was the most accurate when analyzing the artifact containing DTI datasets. The pipeline that combined the DTIPrep protocol and the RESTORE algorithm produced the lowest standard deviation in FA measurements in normal appearing WM across subjects. We concluded that this pipeline was the most robust and is preferred for automated analysis of multisite brain DTI data

Heteroskedasticity-robust estimation of means

The properties of the usual one-sample T-statistic under nonnormal universes are investigated using Edgeworth expansions, and the findings reinforce the observations made by many authors in the past;Sufficient conditions for combining two independent unbiased estimators of a common mean in order to obtain a uniformly better (in variance sense) unbiased estimator is given. An upper bound for the inefficiency of such an estimator is also presented using a Kantorovich inequality;Heteroskedasticity-robust test procedures for the one-sample and two-sample problems are developed. An unbiased estimator of the variance of the ordinary least squares estimator of the slope parameter of a heteroskedastic simple linear regression model without intercept is given and performance of this estimator is assessed using Monte-Carlo simulations.</p

Analysis and identification of symptoms and risk factors in a cohort of chronic hypertensive patients in a tertiary care hospital in Sri Lanka

Background: Hypertension (HT) is identified as a highly prevalent cardiovascular risk factor and also as a separate disease entity, leading to significant mortality and morbidity. The rate of HT is increasing worldwide with a faster rate identified in developing countries. Thus, it is important to evaluate epidemiological patterns of chronic HT in a developing country like Sri Lanka. Methodology: This is a cross-sectional descriptive study conducted at the Teaching Hospital Peradeniya, Sri Lanka, to assess symptoms and risk factors among patients with chronic HT. Results: In a cohort of 266 chronic hypertensives, the mean values for age of population, age of onset, and duration of HT, respectively, are 63, 45, and 8 years. At presentation, 24.8% were asymptomatic. The commonest presentation at diagnosis was dizziness accounting for 33.8% cases, followed by chest pain, headache, loss of consciousness, and shortness of breath accounting for 7.5%, 13.5%, 2.6%, and 4.5%, respectively. Approximately 36.5% of patients had a positive family history. Fathers of 7.1% patients, mothers of 19.2%, and both parents of 10.2% patients had HT. 38.7% of patients had one or more siblings with HT. 34.6% had diabetes mellitus. Conclusion: Symptoms of those with HT are mostly nonspecific and should be considered as possible warning signs prior to the development of sinister complications of the disease. Family history of HT with affected siblings, or one of the parents, was, observed in more than one-third of patients. Early screening and prevention of modifiable risk factors are important in these patients to prevent debilitating complications

Development of a PID based closed loop controller for shape memory alloy actuators

Shape Memory Alloy (SMA) spring actuator was designed and fabricated using commercially available NiTiNOL material by shape setting with the use of a special fixture. So, before applying the actuator to an application, a force characterization was conducted and force variation respect to uncontrolled temperature was analyzed. Due to the difference between force and temperature sensor's response time, a lag can occur between force and temperature measurements. Therefore, a more controlled technique was further implemented by developing a Proportional-Integral-Derivative (PID) based closed loop controller, together with a Graphical User Interface (GUI) which supports parameter control and sensor calibration. Finally, a force feedback controlling method also developed using the same PID technique for a force sensitive applications, where controlled forces need to be maintained by varying temperature of SMA accordingly.</p

Venous neointimal hyperplasia in polytetrafluoroethylene dialysis grafts

Venous neointimal hyperplasia in polytetrafluoroethylene dialysis graftsBackgroundVascular access dysfunction is the most important cause of morbidity and hospitalization in the hemodialysis population in the United States at a cost of $1 billion per annum. Venous neointimal hyperplasia (VNH) characterized by stenosis and subsequent thrombosis accounts for the overwhelming majority of pathology resulting in polytetrafluoroethylene (PTFE) dialysis graft failure. Despite the magnitude of the problem and the enormity of the cost ($1 billion), there are currently no effective therapies for the prevention or treatment of venous neointimal hyperplasia in PTFE dialysis grafts.MethodsTissue samples were collected from the graft-vein anastomosis of stenotic PTFE grafts during surgical revision. Specimens were graded using standard light microscopy and immunohistochemistry for the magnitude of neointimal hyperplasia and for the expression of specific cell types, cytokines, and matrix proteins.ResultsVNH was characterized by the (1) presence of smooth muscle cells/myofibroblasts, (2) accumulation of extracellular matrix components, (3) angiogenesis within the neointima and adventitia, and (4) presence of an active macrophage cell layer lining the PTFE graft material. Platelet-derived growth factor (PDGF), basic fibroblast growth factor (bFGF), and vascular endothelial growth factor (VEGF) were expressed by smooth muscle cells/myofibroblasts within the venous neointima, by macrophages lining both sides of the PTFE graft, and by vessels within the neointima and adventitia.ConclusionsOur results suggest that macrophages, specific cytokines (bFGF, PDGF, and VEGF), and angiogenesis within the neointima and adventitia are likely to contribute to the pathogenesis of VNH in PTFE dialysis grafts. Interventions aimed at these specific mediators and processes may be successful in reducing the very significant human and economic costs of vascular access dysfunction