Time-dependent frequency decomposition of fluctuations in cardiovascular signals (heart rate [HR], blood pressure, and blood flow) provides noninvasive and quantitative evaluation of autonomic activity during transient and steady-state conditions. This method was applied during a change of position from supine to standing in patients with multiple sclerosis (MS) who experienced unexplained fatigue and in age-matched control subjects. No difference in response to standing, as reflected in the time domain parameters (mean HR, mean blood pressure, and mean blood flow), was observed between patients with MS and control subjects. Moreover, no difference was observed in very-low-frequency and low-frequency (related to sympathetic activity) content of HR, blood pressure, blood flow, or high-frequency content of HR (related to parasympathetic activity). The only spectral estimates that showed a significant difference between groups were the ratio of low-frequency to high-frequency content of HR and low-frequency content of HR normalized to total power. Both these parameters provide an estimate of the sympathovagal balance. A significant increase in these two estimates on standing was observed in control subjects only, indicating possible impairment of the sympathovagal balance response to standing in patients with MS who experienced fatigue. The authors observed a significant age dependence between close age subgroups, which occurred in the MS group only and was observed in some of the investigated spectral estimates that reflect vagal activity. Therefore, the authors assumed that age-related reduction in vagal activity occurred earlier in patients with MS who experienced fatigue. This reduction could also explain the lack of increase in the sympathovagal balance on standing. To validate this enhanced age dependence, further investigation should be performed in a larger group of subjects with a wider age range.
New nonlinear image processing techniques, in particular smoothing based on the understanding of the image, may create computerized tomography (CT) images of good quality using less radiation. Such techniques may be applied before the reconstruction and particularly after it. Current CT scanners use strong linear low-pass filters applied to the CT projections, reducing noise but also deteriorating the resolution of the image. The method in this study was to apply a weak low-pass filter on the projections, to perform the reconstruction, and only then to apply a nonlinear filter on the image. Various kinds of nonlinear filters were investigated based on the fact that the image is approximately piecewise constant. The filters were applied with many values of several parameters and the effects on the spatial resolution and the noise reduction were evaluated. The signal-to-noise ratio of a high-contrast phantom image processed were compared with the nonlinear filter, with the SNR of the phantom images obtained with the built-in CT linear filters in two scanning modes, the normal and the ultra high resolution modes. It was found that the nonlinear filters improve the SNR of the image, compared to the built-in filters, about three times for the normal mode and twice for the UHR scanning mode. The most successful filter on low-contrast phantom image was applied and it also seems to lead to promising results. These results seem to show that applying nonlinear filters on CT images might lead to better image quality than using the current linear filters.(ABSTRACT TRUNCATED AT 250 WORDS)
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