复杂随机抽样数据的多重线性回归分析方法及其应用

目的：探讨综合权重在复杂随机抽样数据线性回归分析中的意义和作用。方法基于蒙特卡洛随机模拟思想,采用SAS中REG和SURVEYREG两个不同的多重线性回归分析过程,分别对同一批复杂随机抽样数据（ n＝6756）在不同随机抽样率条件下进行回归建模,对所得结果进行比较。结果在未考虑和考虑观测权重与抽样权重的多重线性回归模型拟合的结果中,自变量的偏回归系数、标准误及P值的大小均有所不同。结论在对基于不同抽样率的复杂随机抽样资料,尤其是分层随机抽样调查资料的回归建模中,采用多重线性回归模型拟合资料时,将调查数据的综合权重纳入统计分析,方能更准确、灵敏地进行回归系数的参数估计和对结果变量的统计预测。     

正常老年人视空间任务的fMRI研究

目的　探讨正常老年人进行fMRI实验的可行性及视空间任务的激活脑区。方法　对 11例正常老年志愿者进行视空间任务的fMRI实验 ,以SPM99作后处理显示激活脑区。结果　 11例被试的视空间任务均完成较好 ,激活区域主要集中在左侧顶内沟周围皮质、左前额叶的背外侧皮层和双侧枕叶 ,任务相关的特定区域为左侧顶上小叶。结论　老年人进行fMRI实验具有可行性 ,左侧顶上小叶为视空间信息加工的特异性脑区     

运动想象结合任务导向训练在脑卒中后手功能康复中作用的fMRI研究

<正>运动想象(motor imagery,MI)是基于镜像神经元理论的一种中枢康复干预,影像研究提示MI能激活想象动作对应的大脑皮层[1]和增强相关脑神经网络之间的功能连接[2],被认为是一种在脑卒中患者上肢康复中很有潜力的治疗方法[3]。然而,由于种种原因,如:患者想象内容难以监测、具体想象动作未在现实生活中进行强化和应用等[4],导致MI的临床疗效向实际转化的过程中困难重重。基于此,我科首次应用运动想象结合任     

首发抑郁症患者空间工作记忆的fMRI研究

目的：探讨首发抑郁症患者矩阵工作记忆任务的脑功能磁共振成像（fMRI）激活特征,为抑郁症空间工作记忆力的缺损机制提供影像学线索。材料和方法：12例首发抑郁症患者与12例健康对照者,配对进行矩阵工作记忆任务的脑fMRI扫描。以AFNI软件对fMRI数据定位定量分析。结果：①首发抑郁症患者组矩阵工作记忆0-back及2-back任务执行正确率均低于对照组（P〈0.05）;②矩阵工作记忆任务激活两组受试者的脑区为：右侧与左侧前额叶BA9/46、右侧与左侧顶叶BA7/40、右侧与左侧额叶BA6区及辅助运动区SMA（P〈0.05）;③患者组的上述前六个脑区激活强度分别为：0.21%、1.11%、2.61%、2.82%、1.23%与1.31%,低于对照组的2.60%、2.50%、4.96%、4.36%、2.94%与3.45%（P〈0.05）。两组间SMA区激活差异无统计学意义（P〉0.05）。结论：首发抑郁症患者矩阵空间工作记忆能力下降,双侧BA9/46、BA6与BA7/40区功能减弱是其空间工作记忆能力缺损的机制之一。     

Decomposition of inflow and blood oxygen level-dependent (BOLD) effects with dual-echo spiral gradient-recalled echo (GRE) fMRI

Image contrast with gradient-recalled echo sequences (GRE) used for fMRI can have both blood oxygen level-dependent (BOLD) and inflow components, and the latter is often undesirable. A dual-echo technique can be used to differentiate these mechanisms, because modulation of signal from inflow is common to both echoes, whereas susceptibility and diffusion-related signal losses are larger in the second echo. An efficient dual-echo interleaved spiral sequence was developed for use with a conventional scanner. It uses a κ-space trajectory that spirals out from the origin while the first echo is collected, then spirals back in while collecting the second echo. Decomposition of the data provides separate images of the inflow and T₂*-weighted components. Results demonstrate the decomposition with phantom experiments and with photic stimulation in normal volunteers.     

Investigation of Acupuncture-specific BOLD Signal Changes Using Multiband Acquisition and Deconvolution Analysis

PurposeWe investigated the temporal dynamics of blood oxygen level-dependent (BOLD) signal responses during various stimuli, including real acupuncture, sham acupuncture, and palm scrubbing. For this purpose, deconvolution analysis was used to perform measurements using multi-band (MB) echo-planar imaging (EPI), which can improve time resolution, and to analyze brain responses without an expected reference function.MethodsWe devided 26 healthy right-handed adults into a group of 13 who received real acupuncture stimulation with manual manipulation and the other group of 13 who received sham acupuncture and palm scrubbing tactical stimulations. Data analysis was performed with a combination of analysis packages.ResultsWe found stimulus-specific impulse responses of the BOLD signal in various brain regions. During real acupuncture, activated areas were observed in the secondary somatosensory cortex (SII) and insula during stimulation and in the anterior cingulate cortex (ACC), supplementary motor area (SMA), and thalamus after the stimulation. During sham acupuncture, activated areas were observed in the SII, insula, and thalamus during simulation. During the scrubbing condition, activated areas were observed in the contralateral primary somatosensory cortex (SI), SII, insula, and thalamus during stimulation. In particular, during the real acupuncture condition, significantly delayed and long-sustained increased signals were observed in several brain regions, in contrast to the signals induced with sham acupuncture and palm scrubbing.CoclusionWe speculated that the delayed and long-sustained signal increases were caused by peripheral nociceptors, flare responses, and time-consuming processing in the central nervous system. We used deconvolution analysis with MB EPI and tent functions to identify the delayed increase in the BOLD signal in the area related to pain perception specifically observed in real acupuncture stimulation. We propose that the specific BOLD signal change observed in this study will lead to the elucidation of the mechanism underlying the therapeutic effect of acupuncture stimulation.     

B超、CT、MRI对卵巢癌早期无创诊断的多元线性回归模型及其临床意义

目的探讨建立肿瘤判别函数的方法及其在肿瘤早期诊断中的临床意义,提高B超、CT、Mill诊断的准确性和特异性。方法B超、CT、MRI、临床症状、实验室资料建立多元线性回归模型,并测试模型,该模型从定性到定量,期望能提高B超、CT、MRI诊断的准确性和特异性。结果影像学检查因其无创性、可重复性高,在卵巢癌的早期诊断中较其他手段具有明确的优势。多元线性回归模型的建立能使影像学检查从定性到定量,从而提高卵巢癌早期诊断的准确性。结论B超、CT、MRI对卵巢癌早期无创诊断的多元线性回归模型,能提高卵巢癌早期诊断的准确性。     

Motion Artifacts in fMRI: Comparison of 2DFT with PR and Spiral Scan Methods

Activation signals based on BOLD contrast changes consequent to neuronal stimulation typically produce cortical intensity differences of < 10% at 1.5T. Hemodynamically driven pulsation of the brain can cause highly pulsatile phase shifts, which in turn result in motion artifacts whose intensity is larger than the activation signals in 2DFT scan methods. This paper presents a theoretical and experimental comparison of the magnitude of such artifacts for 2DFT and two other methods using non-Cartesian k-space trajectories. It is shown that artifacts increase with TR for 2DFT methods, and that projection reconstruction (PR) and spiral methods have significantly reduced artifact intensities, because these trajectories collect low spatial frequencies with every view. The spiral technique is found to be superior in terms of efficiency and motion insensitivity.     

Wavelet statistics of functional MRI data and the general linear model

PURPOSE: To improve the signal-to-noise ratio (SNR) of functional magnetic resonance imaging (fMRI) data, an approach is developed that combines wavelet-based methods with the general linear model. MATERIALS AND METHODS: Ruttimann et al. (1) developed a wavelet-based statistical procedure to test wavelet-space partitions for significant wavelet coefficients. Their method is applicable for the detection of differences between images acquired under two experimental conditions using long blocks of stimulation. However, many neuropsychological questions require more complicated event-related paradigms and more experimental conditions. Therefore, in order to apply wavelet-based methods to a wide range of experiments, we present a new approach that is based on the general linear model and wavelet thresholding. RESULTS: In contrast to a monoresolution filter, the application of the wavelet method increased the SNR and showed a set of clearly dissociable activations. Furthermore, no relevant decrease of the local maxima was observed. CONCLUSION: Wavelet-based methods can increase the SNR without diminishing the signal amplitude, while preserving the spatial resolution of the image. The anatomical localization is strongly improved.     

Complex and magnitude‐only preprocessing of 2D and 3D BOLD fMRI data at 7 T

A challenge to ultra high field functional magnetic resonance imaging is the predominance of noise associated with physiological processes unrelated to tasks of interest. This degradation in data quality may be partially reversed using a series of preprocessing algorithms designed to retrospectively estimate and remove the effects of these noise sources. However, such algorithms are routinely validated only in isolation, and thus consideration of their efficacies within realistic preprocessing pipelines and on different data sets is often overlooked. We investigate the application of eight possible combinations of three pseudo‐complementary preprocessing algorithms – phase regression, Stockwell transform filtering, and retrospective image correction – to suppress physiological noise in 2D and 3D functional data at 7 T. The performance of each preprocessing pipeline was evaluated using data‐driven metrics of reproducibility and prediction. The optimal preprocessing pipeline for both 2D and 3D functional data included phase regression, Stockwell transform filtering, and retrospective image correction. This result supports the hypothesis that a complex preprocessing pipeline is preferable to a magnitude‐only pipeline, and suggests that functional magnetic resonance imaging studies should retain complex images and externally monitor subjects' respiratory and cardiac cycles so that these supplementary data may be used to retrospectively reduce noise and enhance overall data quality. Magn Reson Med, 2012. © 2011 Wiley Periodicals, Inc.