Variable selection in the functional linear concurrent model

We propose methods for variable selection in the context of modeling the association between a functional response and concurrently observed functional predictors. This data structure, and the need for such methods, is exemplified by our motivating example: a study in which blood pressure values are observed throughout the day, together with measurements of physical activity, location, posture, affect or mood, and other quantities that may influence blood pressure. We estimate the coefficients of the concurrent functional linear model using variational Bayes and jointly model residual correlation using functional principal components analysis. Latent binary indicators partition coefficient functions into included and excluded sets, incorporating variable selection into the estimation framework. The proposed methods are evaluated in simulations and real‐data analyses, and are implemented in a publicly available R package with supporting interactive graphics for visualization. Copyright © 2017 John Wiley & Sons, Ltd.     

力学虚拟人骨组织曲线曲面模型重建技术

目的以冷冻切片图像序列为数据源,重建骨组织曲线曲面模型。方法首先通过平移、旋转和缩放等几何变换对冷冻切片图像序列进行配准,再依次对每张冷冻切片图像进行分割处理;处理每张冷冻切片时,在分割对象的边界上交互选择少量的特征点,采用三次有理B样条将系列特征点拟合成封闭曲线,利用样条曲线控制点影响的局部性性质,调整曲线的控制多边形,使其与目标骨组织边界吻合。分割完成后的每条曲线以骨组织名称、方位和切片编号作为索引加入曲线数据库。结果提出从中国数字化可视人体数据集中获取骨组织曲面几何模型的完整技术路线,并建立完善的曲面数据库。结论从冷冻切片图像序列中重建骨组织曲线曲面模型的技术路线可行、有效。     

3D spatial compounding of ultrasound images using image-based nonrigid registration

Medical ultrasound images are often distorted enough to significantly limit resolution during compounding (i.e., summation of images from multiple views). A new, volumetric image registration technique has been used successfully to enable high spatial resolution in three-dimensional (3D) spatial compounding of ultrasound images. Volumetric ultrasound data were acquired by scanning a linear matrix array probe in the elevational direction in a focal lesion phantom and in a breast in vivo. To obtain partly uncorrelated views, the volume of interest was scanned at five different transducer tilt angles separated by 4° to 6°. Pairs of separate views were registered by an automatic procedure based on a mutual information metric, using global full affine and thin-plate spline warping transformations. Registration accuracy was analyzed automatically in the phantom data, and manually in vivo, yielding average registration errors of 0.31 mm and 0.65 mm, respectively. In the vicinity of the warping control points, registrations obtained with warping transformations were significantly more accurate than full affine registrations. Compounded images displayed the expected reduction in speckle noise and increase in contrast-to-noise ratio (CNR), as well as better delineation of connective tissues and reduced shadowing. Compounding also revealed some apparent low contrast lobulations that were not visible in the single-sweep images. Given expected algorithmic and hardware enhancements, nonrigid, image-based registration shows great promise for reducing tissue motion and refraction artifacts in 3D spatial compounding.     

利用三次样条差值法抑制脉搏波基线漂移

目的脉搏波检测过程中,必须克服由于呼吸运动和身体移位会导致脉搏信号的基线漂移。本文提出一种基于三次样条差值的脉搏波基线漂移抑制方法。方法选择脉搏波的各个起始点为给定点,根据各个给定点的数值利用三次样条插值拟合出基线。然后用脉搏波在各个采样时间点上的采样值减去对应时间点上的基线函数数值,得到去基线的脉搏波波形。结果通过实际测量实验表明,脉搏波去基线后,基线比较平稳,波形比较稳定。结论三次样条差值法能有效抑制脉搏波的基线漂移,并且能够很好地应用在脉搏波实时检测中。     

半参数回归模型及模拟实例分析

目的 放宽经典线性模型中的解释变量的线性假定和探讨半参数回归分析模型。方法 利用最小惩罚二乘原理构造加权惩罚平方和,通过广义交互有效得分函数自动选择光滑参数值,用直接法求解方程组。结果 用SAS程序实现了半参数回归分析。得到了回归系数向量和样条函数的最小惩罚二乘估计,模拟实例表明,半参数回归模型较传统的线性模型有较强的适应性。结论 半参数回归模型是经典线性模型和非参数回归模型的一个混合体。可作为回归分析的一种新技术得到广泛应用。     

Cardiac material markers from tagged MR images

Tagged magnetic resonance imaging (MRI) has shown great promise in non-invasive analysis of heart motion. To replace implanted markers as a gold standard, however, tagged MRI must be able to track a sparse set of material points, so-called material markers, with high accuracy. This paper presents a new method for generating accurate motion estimates over a sparse set of material points using standard, parallel-tagged MR images. Each tracked point is located at the intersection of three tag surfaces, each of which is estimated using a thin-plate spline. The intersections are determined by an iterative alternating projections algorithm for which a proof of convergence is provided. The resulting data sets are compatible with applications developed to exploit implanted marker data. One set of these material markers from a normal human volunteer is examined in detail using several methods to visualize the markers. Numerical results that include additional studies are also discussed. Finally, an error analysis is presented using a computer-simulated left ventricle for which material markers are tracked with an RMS error of approximately 0.2 mm for typical imaging parameters and noise levels.     

2型糖尿病患者发生慢性肾脏病的危险因素及与肥胖的相关性研究

目的研究2型糖尿病(T2DM)患者发生慢性肾脏病(CKD)的危险因素,并着重分析肥胖与CKD发生的关系。方法纳入2009年1月至2019年6月在南京鼓楼医院就诊的18至75岁诊断为T2DM的患者,收集一般资料包括性别、年龄、体重指数(BMI)、收缩压、舒张压、糖尿病病程以及实验室指标包括血红蛋白(Hb)、白蛋白、丙氨酸转氨酶(ALT)、天冬氨酸氨基转移酶(AST)、总胆红素(TBIL)、尿酸、空腹血糖(FPG)、糖化血红蛋白(HbA1c)、甘油三酯(TG)、总胆固醇(TC)、低密度脂蛋白胆固醇(LDL-C)、高密度脂蛋白胆固醇(HDL-C)、尿白蛋白/肌酐比值和估算的肾小球滤过率。肥胖定义为BMI≥28 kg/m²,超重定义为24 kg/m²≤BMI<28 kg/m²。根据是否合并CKD,将研究对象分为合并CKD组和不合并CKD组。在不合并CKD的T2DM患者中,选取至少随访一次,随访时间超过12个月且随访数据完整的患者,按是否发生CKD分为发生CKD组和未发生CKD组。两组间各指标的比较采用t检验、非参数检验以及χ²检验。采用单因素及多因素logistic回归分析法分析T2DM患者发生CKD的危险因素,采用Cox比例风险模型分析随访的T2DM患者CKD发生的危险因素。采用限制性立方样条(RCS)拟合Cox回归模型来评估不同的BMI截点与CKD的关系。结果共纳入3194例T2DM患者,其中合并CKD组620例,不合并CKD组2574例。与不合并CKD组相比,合并CKD组T2DM患者BMI明显增高(P=0.005)。单因素logistic回归分析结果显示,性别、肥胖、收缩压、舒张压、Hb、白蛋白、TG、TC、FPG及HbA1c为T2DM患者发生CKD的影响因素(均P<0.05),将上述指标作为自变量,进行多因素logistic回归分析,结果显示,肥胖(OR=1.058,95%CI 1.079~2.018),收缩压增高(OR=1.027,95%CI 1.018~1.035),TG增加(OR=1.087,95%CI 1.008~1.171),FPG增高(OR=1.042,95%CI 1.003~1.083)是T2DM患者发生CKD的影响因素(均P<0.05)。不合并CKD组中随访时间超过12个月且随访数据完整的T2DM患者共753例,其中,发生CKD组182例,未发生CKD组571例。Cox比例风险模型分析结果显示,在校正年龄、糖尿病病程、收缩压、AST、TG及FPG后,超重为发生CKD的危险因素(OR=1.95,95%CI 1.05~3.61)。RCS拟合Cox回归模型结果显示,T2DM患者BMI与CKD发生风险呈非线性关系,BMI在28~31 kg/m²的T2DM患者CKD的发生风险增加(均P<0.05)。结论T2DM患者肥胖与CKD密切相关,肥胖的T2DM患者,特别是BMI在28~31 kg/m²,容易发展为CKD。     

Determination of the human spine curve based on laser triangulation

Background

The main objective of the present method was to automatically obtain a spatial curve of the thoracic and lumbar spine based on a 3D shape measurement of a human torso with developed scoliosis. Manual determination of the spine curve, which was based on palpation of the thoracic and lumbar spinous processes, was found to be an appropriate way to validate the method. Therefore a new, noninvasive, optical 3D method for human torso evaluation in medical practice is introduced.

Methods

Twenty-four patients with confirmed clinical diagnosis of scoliosis were scanned using a specially developed 3D laser profilometer. The measuring principle of the system is based on laser triangulation with one-laser-plane illumination. The measurement took approximately 10 seconds at 700 mm of the longitudinal translation along the back. The single point measurement accuracy was 0.1 mm. Computer analysis of the measured surface returned two 3D curves. The first curve was determined by manual marking (manual curve), and the second was determined by detecting surface curvature extremes (automatic curve). The manual and automatic curve comparison was given as the root mean square deviation (RMSD) for each patient. The intra-operator study involved assessing 20 successive measurements of the same person, and the inter-operator study involved assessing measurements from 8 operators.

Results

The results obtained for the 24 patients showed that the typical RMSD between the manual and automatic curve was 5.0 mm in the frontal plane and 1.0 mm in the sagittal plane, which is a good result compared with palpatory accuracy (9.8 mm). The intra-operator repeatability of the presented method in the frontal and sagittal planes was 0.45 mm and 0.06 mm, respectively. The inter-operator repeatability assessment shows that that the presented method is invariant to the operator of the computer program with the presented method.

Conclusions

The main novelty of the presented paper is the development of a new, non-contact method that provides a quick, precise and non-invasive way to determine the spatial spine curve for patients with developed scoliosis and the validation of the presented method using the palpation of the spinous processes, where no harmful ionizing radiation is present.     

Spline‐based procedures for dose‐finding studies with active control

In a dose‐finding study with an active control, several doses of a new drug are compared with an established drug (the so‐called active control). One goal of such studies is to characterize the dose–response relationship and to find the smallest target dose concentration d^*, which leads to the same efficacy as the active control. For this purpose, the intersection point of the mean dose–response function with the expected efficacy of the active control has to be estimated. The focus of this paper is a cubic spline‐based method for deriving an estimator of the target dose without assuming a specific dose–response function. Furthermore, the construction of a spline‐based bootstrap CI is described. Estimator and CI are compared with other flexible and parametric methods such as linear spline interpolation as well as maximum likelihood regression in simulation studies motivated by a real clinical trial. Also, design considerations for the cubic spline approach with focus on bias minimization are presented. Although the spline‐based point estimator can be biased, designs can be chosen to minimize and reasonably limit the maximum absolute bias. Furthermore, the coverage probability of the cubic spline approach is satisfactory, especially for bias minimal designs. © 2014 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.     

Adjusting for time‐dependent sensitivity in an illness‐death model,with application to mother‐to‐child transmission of HIV

In mother‐to‐child transmission of HIV, identifying infected infants relies on a diagnostic test with imperfect sensitivity that is administered at scheduled visits. Under this scenario, a participant's true state may be unknown at the start and end times of the study, and the detection of transitions into illness may be delayed or missed altogether. This could lead to biased estimates of the risk of transmission and covariate associations. When a test has imperfect sensitivity, but perfect specificity, the additional uncertainty can be captured as a random variable measuring delay in detection. The cumulative distribution then defines a time‐dependent sensitivity function that increases over time. We present a maximum likelihood based illness‐death model that accounts for imperfect sensitivity by including the delay as an exponential distribution. We specify transition rates as penalized B‐splines to allow for nonhomogeneity of risk and discuss the model under Markov and semi‐Markov assumptions. We apply this method to our motivating data set, a study of 1499 mother and infant pairs at three sites in Africa. Copyright © 2014 John Wiley & Sons, Ltd.