7 resultados para Bicircular four body problem

em DigitalCommons@The Texas Medical Center


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The motion of lung tumors during respiration makes the accurate delivery of radiation therapy to the thorax difficult because it increases the uncertainty of target position. The adoption of four-dimensional computed tomography (4D-CT) has allowed us to determine how a tumor moves with respiration for each individual patient. Using information acquired during a 4D-CT scan, we can define the target, visualize motion, and calculate dose during the planning phase of the radiotherapy process. One image data set that can be created from the 4D-CT acquisition is the maximum-intensity projection (MIP). The MIP can be used as a starting point to define the volume that encompasses the motion envelope of the moving gross target volume (GTV). Because of the close relationship that exists between the MIP and the final target volume, we investigated four MIP data sets created with different methodologies (3 using various 4D-CT sorting implementations, and one using all available cine CT images) to compare target delineation. It has been observed that changing the 4D-CT sorting method will lead to the selection of a different collection of images; however, the clinical implications of changing the constituent images on the resultant MIP data set are not clear. There has not been a comprehensive study that compares target delineation based on different 4D-CT sorting methodologies in a patient population. We selected a collection of patients who had previously undergone thoracic 4D-CT scans at our institution, and who had lung tumors that moved at least 1 cm. We then generated the four MIP data sets and automatically contoured the target volumes. In doing so, we identified cases in which the MIP generated from a 4D-CT sorting process under-represented the motion envelope of the target volume by more than 10% than when measured on the MIP generated from all of the cine CT images. The 4D-CT methods suffered from duplicate image selection and might not choose maximum extent images. Based on our results, we suggest utilization of a MIP generated from the full cine CT data set to ensure a representative inclusive tumor extent, and to avoid geometric miss.

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We assessed the effects of hypoxic-ischemic encephalopathy (HIE) and whole-body hypothermia therapy on auditory brain stem evoked responses (ABRs) and distortion product otoacoustic emissions (DPOAEs). We performed serial assessments of ABRs and DPOAEs in newborns with moderate or severe HIE, randomized to hypothermia ( N = 4) or usual care ( N = 5). Participants were five boys and four girls with mean gestational age (standard deviation) of 38.9 (1.8) weeks. During the first week of life, peripheral auditory function, as measured by the DPOAEs, was disrupted in all nine subjects. ABRs were delayed but central transmission was intact, suggesting a peripheral rather than a central neural insult. By 3 weeks of age, peripheral auditory function normalized. Hypothermia temporarily prolonged the ABR, more so for waves generated higher in the brain stem but the effects reversed quickly on rewarming. Neonatal audiometric testing is feasible, noninvasive, and capable of enhancing our understanding of the effects of HIE and hypothermia on auditory function.

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Many persons in the U.S. gain weight during young adulthood, and the prevalence of obesity has been increasing among young adults. Although obesity and physical inactivity are generally recognized as risk factors for coronary heart disease (CHD), the magnitude of their effect on risk may have been seriously underestimated due to failure to adequately handle the problem of cigarette smoking. Since cigarette smoking causes weight loss, physically inactive cigarette smokers may remain relatively lean because they smoke cigarettes. We hypothesize cigarette smoking modifies the association between weight gain during young adulthood and risk of coronary heart disease during middle age, and that the true effect of weight gain during young adulthood on risk of CHD can be assessed only in persons who have not smoked cigarettes. Specifically, we hypothesize that weight gain during young adulthood is positively associated with risk of CHD during middle-age in nonsmokers but that the association is much smaller or absent entirely among cigarette smokers. The purpose of this study was to test this hypothesis. The population for analysis was comprised of 1,934 middle-aged, employed men whose average age at the baseline examination was 48.7 years. Information collected at the baseline examinations in 1958 and 1959 included recalled weight at age 20, present weight, height, smoking status, and other CHD risk factors. To decrease the effect of intraindividual variation, the mean values of the 1958 and 1959 baseline examinations were used in analyses. Change in body mass index ($\Delta$BMI) during young adulthood was the primary exposure variable and was measured as BMI at baseline (kg/m$\sp2)$ minus BMI at age 20 (kg/m$\sp2).$ Proportional hazards regression analysis was used to generate relative risks of CHD mortality by category of $\Delta$BMI and cigarette smoking status after adjustment for age, family history of CVD, major organ system disease, BMI at age 20, and number of cigarettes smoked per day. Adjustment was not performed for systolic blood pressure or total serum cholesterol as these were regarded as intervening variables. Vital status was known for all men on the 25th anniversary of their baseline examinations. 705 deaths (including 319 CHD deaths) occurred over 40,136 person-years of experience. $\Delta$BMI was positively associated with risk of CHD mortality in never-smokers, but not in ever-smokers (p for interaction = 0.067). For never-smokers with $\Delta$BMI of stable, low gain, moderate gain, and high gain, adjusted relative risks were 1.00, 1.62, 1.61, and 2.78, respectively (p for trend = 0.010). For ever-smokers, with $\Delta$BMI of stable, low gain, moderate gain, and high gain, adjusted relative risks were 1.00, 0.74, 1.07, and 1.06, respectively (p for trend = 0.422). These results support the research hypothesis that cigarette smoking modifies the association between weight gain and CHD mortality. Current estimates of the magnitude of effect of obesity and physical inactivity on risk of coronary mortality may have been seriously underestimated due to inadequate handling of cigarette smoking. ^

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Previous studies of normal children have linked body fat but not body fat distribution (BFD), to higher blood pressures, lipids, and insulin resistance (Berenson et al., 1988) BFD is a well-established risk factor for cardiovascular disease in adults (Björntorp, 1988). This study investigates the relation of BFD and serum lipids at baseline in children from Project HeartBeat!, a study of the growth and development of cardiovascular risk factors in 678 children in three cohorts measured initially at ages 8, 11, and 14 years. Initially, two of four indices of BFD were significantly related to the lipids: ratio of upper to lower body skinfolds (ln US:LS) and conicity (C Index). A factor analysis reduced the information in the serum lipids to two vectors: (1) total cholesterol + LDL-cholesterol and (2) HDL-cholesterol − triglycerides, which together accounted for 85% of the lipid variation. Using each serum lipid and vector as separate dependent variables, linear and quadratic regression models were constructed to examine the predictive ability of the two BFD variables, controlling for total body fat, gender, ethnicity (Black, non-Black) and maturation. Linear models provided an acceptable fit. Percent body fat (%BF) was a significant predictor in each and every lipid model, independent of age, maturation, or ethnicity (p ≤ 0.05). No BFD variable entered the equation for total or LDL-cholesterol, although there was a significant maturity by BFD interaction for LDL (ln US:LS was a significant predictor in more mature individuals). Both %BF and BFD (by way of Conicity) were significant predictors of HDL-cholesterol and triglycerides (p ≤ 0.01). All models were statistically significant at a high level (p ≤ 0.01), but adjusted R 2's for all models were low (0.05–0.15). Body fat distribution is a significant predictor of lipids in normal children, but secondarily to %BF, and for LDL-cholesterol in particular, the relation is dependent on maturity status. ^

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A variety of studies indicate that the process of athrosclerosis begins in childhood. There was limited information on the association of the changes in anthropometric variables to blood lipids in school age children and adolescents. Previous longitudinal studies of children typically with insufficient frequency of observation could not provide sound inference on the dynamics of change in blood lipids. The aims of this analysis are (1) to document the sex- and ethnic-specific trajectory and velocity curves of blood lipids (TC, LDL-C, HDL-C and TG); (2) to evaluate the relationship of changes in anthropometric variables, such as height, weight and BMI, to blood lipids from age 8 to 18 years. ^ Project HeartBeat! is a longitudinal study designed to examine the patterns of serial change in major cardiovascular risk factors. Cohort of three different age levels, 8, 11 and 14 years at baseline, with a total of 678 participants were enrolled. Each member of these cohorts was examined three times per year for up to four years. ^ Sex- and ethnic-specific trajectory and velocity curves of blood lipids; demonstrated the complex and polyphasic changes in TC, LDL-C, HDL-C and TG longitudinally. The trajectory curves of TC, LDL-C and HDL-C with age showed curvilinear patterns of change. The velocity change in TC, HDL-C and LDL-C showed U-shaped curves for non-Blacks, and nearly linear lines in velocity of TG for both Blacks and non-Blacks. ^ The relationship of changes in anthropometric variables to blood lipids was evaulated by adding height, weight, or BMI and associated interaction terms separately to the basic age-sex models. Height or height gain had a significant negative association with changes in TC, LDL-C and HDL-C. Weight or BMI gain showed positive associations with TC, LDL-C and TC, and a negative relationship with HDL-C. ^ Dynamic changes of blood lipids in school age children and adolescents observed from this analysis suggested that using fixed screening criteria under the current NCEP guidelines for all ages 2–19 may not be appropriate for this age group. The association of increasing BMI or weight to an adverse blood lipid profile found in this analysis also indicated that weight or BMI monitoring could be a future intervention to be implemented in the pediatric population. ^

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Longitudinal principal components analyses on a combination of four subcutaneous skinfolds (biceps, triceps, subscapular and suprailiac) were performed using data from the London Longitudinal Growth Study. The main objectives were to discover at what age during growth sex differences in body fat distribution occur and to see if there is continuity in body fatness and body fat distribution from childhood into the adult status (18 years). The analyses were done for four age sectors (3mon-3yrs, 3yrs-8yrs, 8yrs-18yrs and 3yrs-18yrs). Longitudinal principal component one (LPC1) for each age interval in both sexes represents the population mean fat curve. Component two (LPC2) is a velocity of fatness component. Component three (LPC3) in the 3mon-3yrs age sector represents infant fat wave in both sexes. In the next two age sectors component three in males represents peaks and shifts in fat growth (change in velocity), while in females it represents body fat distribution. Component four (LPC4) in the same two age sectors is a reversal in the sexes of the patterns seen for component three, i.e., in males it is body fat distribution and in females velocity shifts. Components five and above represent more complicated patterns of change (multiple increases and decreases across the age interval). In both sexes there is strong tracking in fatness from middle childhood to adolescence. In males only there is also a low to moderate tracking of infant fat with middle to late childhood fat. These data are strongly supported in the literature. Several factors are known to predict adult fatness among the most important being previous levels of fatness (at earlier ages) and the age at rebound. In addition we found that the velocity of fat change in middle childhood was highly predictive of later fatness (r $\approx -$0.7), even more so than age at rebound (r $\approx -$0.5). In contrast to fatness (LPC1), body fat distribution (LPC3-LPC4) did not track well even though significant components of body fat distribution occur at each age. Tracking of body fat distribution was higher in females than males. Sex differences in body fat distribution are non existent. Some sex differences are evident with the peripheral-to-central ratios after age 14 years. ^

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Purpose. This project was designed to describe the association between wasting and CD4 cell counts in HIV-infected men in order to better understand the role of wasting in progression of HIV infection.^ Methods. Baseline and prevalence data were collected from a cross-sectional survey of 278 HIV-infected men seen at the Houston Veterans Affairs Medical Center Special Medicine Clinic, from June 1, 1991 to January 1, 1994. A follow-up study was conducted among those at risk, to investigate the incidence of wasting and the association between wasting and low CD4 cell counts. Wasting was described by four methods. Z-scores for age-, sex-, and height-adjusted weight; sex-, and age-adjusted mid-arm muscle circumference (MAMC); and fat-free mass; and the ratio of extra-cellular mass (ECM) to body-cell mass (BCM) $>$ 1.20. FFM, ECM, and BCM were estimated from bioelectrical impedance analysis. MAMC was calculated from triceps skinfold and mid-arm circumference. The relationship between wasting and covariates was examined with logistic regression in the cross-sectional study, and with Poisson regression in the follow-up study. The association between death and wasting was examined with Cox's regression.^ Results. The prevalence of wasting ranged from 5% (weight and ECM:BCM) to almost 14% (MAMC and FFM) among the 278 men examined. The odds of wasting, associated with baseline CD4 cell count $<$200, was significant for each method but weight, and ranged from 4.6 to 12.7. Use of antiviral therapy was significantly protective of MAMC, FFM and ECM:BCM (OR $\approx$ 0.2), whereas the need for antibacterial therapy was a risk (OR 3.1, 95% CI 1.1-8.7). The average incidence of wasting ranged from 4 to 16 per 100 person-years among the approximately 145 men followed for 160 person-years. Low CD4 cell count seemed to increase the risk of wasting, but statistical significance was not reached. The effect of the small sample size on the power to detect a significant association should be considered. Wasting, by MAMC and FFM, was significantly associated with death, after adjusting for baseline serum albumin concentration and CD4 cell count.^ Conclusions. Wasting by MAMC and FFM were strongly associated with baseline CD4 cell counts in both the prevalence and incidence study and strong predictors of death. Of the two methods, MAMC is convenient, has available reference population data, may be the most appropriate for assessing the nutritional status of HIV-infected men. ^