Impact of aerobic training upon left ventricular morphology and function in pre-pubescent children

Current knowledge of the impact of training on left ventricular (LV) morphology and function in pre-pubescent children is limited. After ethical approval, 59 pre-pubescent children (mean +/- SD age 10.5 +/- 0.7 years) volunteered for the study. Twenty-five (11 girls) participated in a 12-week progressive, cycle-based aerobic exercise training programme (ET) of three 30-min sessions per week at 80% maximum heart rate (HR) and 34 (15 girls) as matched controls (CON). Pre- and post-training echocardiograms assessed LV structures and function such as LV internal dimension in diastole (LVIDd), LV mass, stroke volume (SV) and early to late LV filling velocity ratio (E:A). Peak VO2 was determined via a modified McMaster protocol. Mixed, two-way ANOVA and multiple linear regression were used to analyse peak VO2 and LV structural/functional data that had been allometrically scaled. A significant interaction for peak VO2 was observed (54 +/- 7 to 55 +/- 6 and 57 +/- 6 to 56 +/- 7 ml/lean body mass (LBM) per min in ET and CON, respectively). A small, but significant, main effect for time was observed for LVIDd over the intervention period (13.9 +/- 1.0 to 14.2 +/- 1.1 and 13.5 +/- 0.9 to 13.8 +/- 1.0 cm.LBM(-0.33) in ET and CON, respectively) that could be attributed to normal growth and development. Similar changes in SV (2.12 +/- 0.45 to 2.24 +/- 0.45 and 1.95 +/- 0.42 to 2.08 +/- 0.44 ml/LBM) and LV mass (2.59 +/- 0.55 to 2.79 +/- 0.69 and 2.45 +/- 0.60 to 2.61 +/- 0.65 g/LBM) were evident (main effect for time p < 0.05). The E:A ratio did not alter in either group. A decrease in resting HR in ET (p < 0.05) suggested a training effect. Multiple regression revealed that post-training resting HR was the only significant predictor of peak VO2 (R2 = 18.2% and 16.9% CON and ET respectively). These data suggest that training in pre-pubescent children does not influence LV morphology and function within the current population. Moreover, the association between LV structure/function and peak VO2 was small. Future work may wish to impose a greater training volume and assess cardiovascular responses in pre-pubescent children.     

仪器引导呼吸对高血压性心脏病患者左心功能的恢复作用分析

为了提升高血压性心脏病的临床诊疗恢复效果,进行仪器引导呼吸对高血压性心脏病患者左心功能恢复作用研究。详细制定临床恢复性指标,确定当前治疗仪的准入量,连入引导呼吸仪,以患者左心房为中心利用稳态程序进入扫描序列(SSPF),并保证患者进入慢性恢复状态。采用LVEDD测量法,对左心功能进行测量,确定恢复周期,实现患者左心功能恢复。实验表明,应用所提方法后,左心室GH值升高,左尖瓣脉冲异常平均值为6&44,最长治疗周期为7、8个月,恢复周期短且效果较好。     

Structural damage detection using imperialist competitive algorithm and damage function

In practical damage detection problems, experimental modal data is only available for a limited number of modes and in each mode, only a limited number of nodal points are recorded. In using modal data, the majority of the available damage detection solution techniques either require data for all the modes, or all the nodal data for a number of modes; neither of which may be practically available through experiments. In the present study, damage identification is carried out using only a limited number of nodal data of a limited number of modes. The proposed method uses the imperialist competitive optimization algorithm and damage functions. To decrease the number of design variables, several bilinear damage functions are defined to model the damage distribution. Damage functions with both variable widths and variable weights are proposed for increased accurately. Four different types of objective functions which use modal responses of damaged structure are investigated with the aim of finding the most suitable function. The efficiency of the proposed method is investigated using three benchmark numerical examples using both clean and noisy modal data. It is shown that by only using a limited number of modal data, the proposed method is capable of accurately detecting damage locations and reasonably accurately evaluate their extents. The proposed algorithm is most effective with noisy modal data, compared to other available solutions.     

Adaptive control of left ventricular bypass assist devices

This paper presents a computer-based adaptive control system for left ventricular bypass assist devices consisting of air driven diaphragm pumps. The system provides for 1) synchronization of pumping with ECG signals and 2) control of atrial pressure at desired levels. The system design includes an adaptive control algorithm which is a self-tuning PID-controller based on pole placement. The performance of the system has been demonstrated by in vitro experiments_ on a mock circulatory system. When there is an increase in atrial pressure, the system responds with an increase in stroke volume. Following major changes in the circulatory system, the control algorithm retunes itself and restores the system to the desired state.     

Modeling arterial and left ventricular coupling for non-invasive measurements

The aim of the presented work has been the development of an algorithm for a non-invasive, portable, easy-to-use, and affordable device for measuring systemic cardiovascular parameters such as cardiac output and peripheral resistance. The data acquisition is based on a common oscillometric measurement using an occlusive blood pressure cuff, and no additional calibration is necessary. The novel algorithm introduced here combines several simulation techniques like neural networks or differential equations, which will be explained briefly. The determination of the hemodynamical parameters is based on the idea that the ejection work of the left ventricle is subject to an optimization principle. This kind of model needs no additional external calibration and opens therefore good perspectives for non-expert use in cardiovascular risk stratification and hypertension therapy optimization. To verify the approach we present some clinical results and a relevant discussion on it, followed by a view of future work.     

左心室超声图像分割及特征分析

针对M型左心室的剖面超声图像进行研究。采用基于区域灰度扩展的CV水平集方法,通过限制能量扩展的方向,去除了相关的干扰,有效地提取了左心室的内外膜。在准确地提取了心肌边界后,对左心室的相关特征进行了纹理变化分析。结果表明,心肌运动的过程中收缩期和舒张期的共生矩阵各特性参数、分形维等均有定量的差别,可将相关的纹理参数用于正常心肌与病变心肌的定量分析上,方便医生进行准确的病理判断。     

一种双水平集模型分割左心室膜的方法

针对目前左心室内外膜分割方法存在分割出的轮廓正则性差、分割心室膜模糊边缘不完全和分割效率低等问题。提出新双阱势函数和各向异性梯度矢量流（AGVF）改进水平集模型能量函数,用融合0水平集和◢k◣水平集的双水平集同时分割左心室内外膜的方法。首先,用改进Hough变化圆检测算法定位心室内外膜初始位置;然后利用双水平集模型同时分割内外膜。观察和对比分析实验结果,该方法能够分割出平滑的左心室内外膜轮廓;能够分割出符合临床定义的左心室内外膜轮廓,且分割MRI图像左心室内外膜轮廓重叠率平均提高到0.956 9。     

基于GVF模型与光流场的左心室容积计算

针对目前利用心脏核磁共振图像计算左心室容积存在的分割困难和计算量大的问题,提出了一种新的计算左心室容积的方法.首先采用基于梯度向量流的主动轮廓模型(GVF-snake)对左心室内膜进行分割获取初始轮廓线,再采用光流法跟踪得到心脏序列中后续帧图像的心腔内膜轮廓线,最后采用Simpson方法计算得到左心室容积.运用该方法得到的结果和用手工勾画心脏内膜轮廓得到的结果比较表明:GVF-snake与光流运动跟踪相结合的方法用于左心室容积的计算是可行的.     

Computer visualization of left ventricular geometry during the cardiac cycle.

Mathematical expressions regulating ventricular dimensions during the cardiac cycle have been defined. Classical, static images are limited in comparison with ventriculograms, are not intuitive for teaching, and do not effectively convey effects of hypertrophy or dilatation. Accordingly we developed Tachycardia, an interactive menu-driven graphics program. The program allows three-dimensional visualization of the kinetics of the thick-walled, ellipsoidal left ventricle (LV). The user may specify mass, ejection fraction, end-diastolic volume, major to minor axis ratio, and diastole to systole time ratio. Real-time animation of heart rates ranging from 50-150/min is achieved. A library contains animations representing the normal LV, including dilatation and concentric or eccentric hypertrophy. For comparison of differences in LV geometry among ventricles, multiple animations can be viewed simultaneously. We conclude that computerized animation provides an intuitive understanding of the dynamic geometry of the cardiac cycle. User definition of the visualization can provide clinical utility and teaching value.     

Three-dimensional echocardiographic reconstruction: qualitative and quantitative evaluation of ventricular function

Three-dimensional (3-D) images of the human left ventricle were reconstructed from 2-dimensional echocardiographic pictures. All images were recorded at held end-expiration from an optimal point where a high-quality parasternal long-axis view maximally visualizing the left ventricle could be obtained. Multiple short-axis views were obtained from the same reference point. Interactive computer techniques were used to reconstruct 3-D shells of endocardium and epicardium. End-diastolic and end-systolic outlines were superimposed after correcting for motion during the cardiac cycle to demonstrate wall motion. Images were displayed from different perspectives and regional wall thickness, thickening, and motion were then demonstrated using surface map displays. Volumes and derived indices of left ventricular function were calculated. The ejection fraction of normal patients was 69 +/- 9%, compared to 57 +/- 7% in infarct patients; the latter results correlated well with contrast angiography. 3-D echocardiographic reconstruction provides the observer with a spatial appreciation of left ventricular wall motion and thickness, as well as useful quantitative information. The system requires only a standard echocardiographic recorder and simple computer hardware.     

Computer assessment of left ventricular wall motion: the ALVEN expert system

The current limited success of computer-assisted analysis of left ventricular (LV) dynamics is due to three main reasons: there is a strong tendency to remain within the realm of mathematical modeling for LV dynamics, and it is not at all clear that this is an adequate approach; in places where mathematical models alone may be insufficient, current computer science research into more sophisticated schemes is not yet complete, and thus, more basic research is required, particularly into artificial intelligence, representations of knowledge, and interpretation control structures, before applications such as LV performance can be solved, a view also stated in M. Boehm and K. Hoehne (in "Digital Image Processing in Medicine" (K. Hoehne, Ed.), Springer-Verlag, New York/Berlin, 1981); there is a distinct lack of knowledge about LV dynamics, in conjunction with disagreements about what is important to model and what terminology is to be used. Although each of these issues is addressed, the first two issues are concentrated on. Furthermore, a language for the expression of definitions for terminology has been designed, and a system for LV dynamics interpretation has been implemented.     

Automatic classification of left ventricular wall segments in small animal ultrasound imaging

Multiple statistics show that heart diseases are one of the main causes of mortality in our highly developed societies today. These diseases lead to a change of the physiology of the heart, which gives useful information about characteristic and severity of the defect. A fast and reliable diagnosis is the base for successful therapy. As a first step towards recognition of such heart remodeling processes, this work proposes a fully automatic processing pipeline for regional classification of the left ventricular wall in ultrasound images of small animals. The pipeline is based on state-of-the-art methods from computer vision and pattern classification. The myocardial wall is segmented and its motion is estimated. A feature extraction using the segmented data is realized to automatically classify the image regions into normal and abnormal myocardial tissue. The performance of the proposed pipeline is evaluated and a comparison of common classification algorithms on ultrasound data of living mice before and after artificially induced myocardial infarction is given. It is shown that the results of this work, reaching a maximum accuracy of 91.46%, are an encouraging base for further investigation.     

An evaluation of a weightlifting belt and back injury prevention training class for airline baggage handlers

This study evaluated the efficacy of a commercially available weightlifting belt in relation to reduction of lumbar injury incident rate and severity of injuries over an 8-month period. The study used 642 baggage handlers working for a major airline company as participants. Four treatment groups were randomly selected: a group receiving the belt only, a group receiving a 1 h training class only, a group receiving both a belt and a 1 h training class, and a control group receiving nothing. Two treatment groups were added which contained participants who discontinued use of the belt prior to the end of an 8-month study period. Results indicated that there were no significant differences for total lumbar injury incident rate, restricted workday case injury incident rate, lost workdays and restricted workdays rate, and worker's compensation rates. There was, however, a marginal significant difference for lost workday case injury incident rate. Groups with participants who wore the belt for a while then discontinued its use had a higher lost day case injury incident rate than did either the group receiving training only or the control group. Compliance was an overriding factor as the belt questionnaire response indicated that 58% of participants in the belt groups discontinued use of the belt before the end of 8 months. Comments made on the survey forms indicated that the belt was too hot. Similarly, comments suggested that the belt rubbed, pinched, and bruised ribs. Based on these results, the weightlifting belt used for this study cannot be recommended for use in aid of lifting during daily work activities of baggage handlers. Results indicate that use of the belts may, in fact, increase the risk of injury when not wearing a belt following a period of wearing a belt. As industries are experimenting with the use of belts, it is recommended that great care be taken in any further evaluation and close attention directed towards injuries which occur when not wearing the belt following a period of wearing the belt (ie, off-the-job injuries).     

基于卷积神经网络的左心室超声图像特征点定位

针对传统级联卷积神经网络（CNN）在左心室超声图像中定位准确度较低的问题，提出一种融合更快速区域卷积神经网络（Faster-RCNN）模型提取区域的级联卷积神经网络，实现对超声图像中左心室心内膜和心外膜轮廓特征点的定位。首先，采用两级级联的方式改进传统级联卷积神经网络的网络结构，第一级网络利用一个改进的卷积网络粗略定位左心室心内膜和心外膜联合的特征点，第二级网络使用四个改进的卷积网络分别对心内膜特征点和心外膜特征点进行位置微调，之后定位输出左心室心内膜和心外膜联合的轮廓特征点位置；然后，将改进的级联卷积神经网络与目标区域提取融合，即利用Faster-RCNN模型提取包含左心室的目标区域并将目标区域送入改进的级联卷积神经网络；最后，由粗到细对左心室轮廓特征点进行定位。实验结果表明，与传统级联卷积神经网络相比，所提方法在左心室超声图像上的定位效果更好，更逼近真实值，在均方根误差的评价标准下，特征点定位准确度提升了32.6个百分点。     

基于HSPICE温度对长条形磁通门输出的影响

温度对磁通门的输出性能起着重要的影响。扩展了Jiles-Atherton模型来描述温度对磁通门输出的非线性磁滞特性。借助于HSPICE分析软件,建立仿真模型,在理论层面阐释了温度对长条形磁通门的影响,有别于用实验进行验证的工作。仿真结果很好的反映了温度的线性变化对长条形磁通门输出的非线性变化的影响,与实验吻合得很好,对磁通门的实际应用提供了有益的理论探索。