Hemodynamic changes preceding the interictal EEG spike in patients with focal epilepsy investigated using simultaneous EEG-fMRI

EEG-fMRI is a non-invasive technique that allows the investigation of epileptogenic networks in patients with epilepsy. Lately, BOLD changes occurring before the spike were found in patients with generalized epilepsy. The study of metabolic changes preceding spikes might improve our knowledge of spike generation. We tested this hypothesis in patients with idiopathic and symptomatic focal epilepsy.Eleven consecutive patients were recorded at 3 T: five with idiopathic focal and 6 with symptomatic focal epilepsy. Thirteen spike types were analyzed separately. Statistical analysis was performed using the timing of spikes as events, modeled with HRFs peaking between − 9 s and + 9 s around the spike. HRFs were calculated the most focal BOLD response. Eleven of the thirteen studies showed prespike BOLD responses. Prespike responses were more focal than postspike responses. Three studies showed early positive followed by later negative BOLD responses in the spike field. Three had early positive BOLD responses in the spike field, which remained visible in the later maps. Three others had positive BOLD responses in the spike field, later propagating to surrounding areas. HRFs peaked between − 5 and + 6 s around the spike timing. No significant EEG changes could be identified prior to the spike.BOLD changes prior to the spike frequently occur in focal epilepsies. They are more focal than later BOLD changes and strongly related to the spike field. Early changes may result from increased neuronal activity in the spike field prior to the EEG spike and reflect an event more localized than the spike itself.     

Spatio-temporal information analysis of event-related BOLD responses

A new approach for analysis of event-related fMRI (BOLD) signals is proposed. The technique is based on measures from information theory and is used both for spatial localization of task-related activity, as well as for extracting temporal information regarding the task-dependent propagation of activation across different brain regions. This approach enables whole brain visualization of voxels (areas) most involved in coding of a specific task condition, the time at which they are most informative about the condition, as well as their average amplitude at that preferred time. The approach does not require prior assumptions about the shape of the hemodynamic response function (HRF) nor about linear relations between BOLD response and presented stimuli (or task conditions). We show that relative delays between different brain regions can also be computed without prior knowledge of the experimental design, suggesting a general method that could be applied for analysis of differential time delays that occur during natural, uncontrolled conditions. Here we analyze BOLD signals recorded during performance of a motor learning task. We show that, during motor learning, the BOLD response of unimodal motor cortical areas precedes the response in higher-order multimodal association areas, including posterior parietal cortex. Brain areas found to be associated with reduced activity during motor learning, predominantly in prefrontal brain regions, are informative about the task typically at significantly later times.     

Linear aspects of transformation from interictal epileptic discharges to BOLD fMRI signals in an animal model of occipital epilepsy

Epileptic disorders manifest with seizures and interictal epileptic discharges (IEDs). The hemodynamic changes that accompany IEDs are poorly understood and may be critical for understanding epileptogenesis. Despite a known linear coupling of the neurovascular elements in normal brain tissues, previous simultaneous electroencephalography (EEG)-functional magnetic resonance imaging (fMRI) studies have shown variable correlations between epileptic discharges and blood oxygenation level-dependent (BOLD) response, partly because most previous studies assumed particular hemodynamic properties in normal brain tissue. The occurrence of IEDs in human subjects is unpredictable. Therefore, an animal model with reproducible stereotyped IEDs was developed by the focal injection of penicillin into the right occipital cortex of rats anesthetized with isoflurane. Simultaneous EEG-fMRI was used to study the hemodynamic changes during IEDs. A hybrid of temporal independent component analysis (ICA) of EEG and spatial ICA of fMRI data was used to correlate BOLD fMRI signals with IEDs. A linear autoregression with exogenous input (ARX) model was used to estimate the hemodynamic impulse response function (HIRF) based on the data from simultaneous EEG-fMRI measurement. Changes in the measured BOLD signal from the right primary visual cortex and bilateral visual association cortices were consistently coupled to IEDs. The linear ARX model was applied here to confirm that a linear transform can be used to study the correlation between BOLD signal and its corresponding neural activity in this animal model of occipital epilepsy.     

Independent component analysis of short-time Fourier transforms for spontaneous EEG/MEG analysis

Analysis of spontaneous EEG/MEG needs unsupervised learning methods. While independent component analysis (ICA) has been successfully applied on spontaneous fMRI, it seems to be too sensitive to technical artifacts in EEG/MEG. We propose to apply ICA on short-time Fourier transforms of EEG/MEG signals, in order to find more “interesting” sources than with time-domain ICA, and to more meaningfully sort the obtained components. The method is especially useful for finding sources of rhythmic activity. Furthermore, we propose to use a complex mixing matrix to model sources which are spatially extended and have different phases in different EEG/MEG channels. Simulations with artificial data and experiments on resting-state MEG demonstrate the utility of the method.     

基于独立成分分析的精神分裂症患者动态脑功能网络分析新方法

目的 提出一种新的基于独立成分分析法进行动态脑功能网络分析的方法,并应用该方法探讨精神分裂症患者在动态全脑功能网络上的变异。方法 首先基于滑动时间窗方法计算正常被试和精神分裂症患者的动态全脑功能网络,然后使用组信息指导独立成分分析方法,提取每个被试的动态全脑功能网络的功能连接状态及相应的时间波动,比较正常被试和精神分裂症患者在功能连接状态上的差异。结果 两组的最重要功能连接状态的模式有相似性。正常被试在额叶、顶叶相关区域较精神分裂症患者具有更强的正功能连接;在小脑相关区域精神分裂症患者呈现出更多的正功能连接,而正常被试呈现出更多的负功能连接。结论 组信息指导独立成分分析方法可有效提取动态脑功能网络的功能连接状态,可揭示精神分裂症患者在动态脑功能网络的变异。     

利用独立成分分析技术和静息fMRI数据对脑功能区进行定位

目的 验证可否利用独立成分分析(ICA)技术和静息fMRI数据对脑功能区进行定位.方法 利用ICA方法,通过研究静息状态的脑功能联结来获取功能区的定位.静息数据的采集采用短TR,在低通滤波(截止频率0.08 Hz)后可以去除生理噪声的主要影响.在数据分析中,对ICA结果进行了可复制性分析,只保留可复制性较高的成分,之后将ICA结果与传统的"种子像素"方法获得的结果进行定量的一致性分析.结果 ICA能够在不设定"种子像素"的情况下从静息fMRI数据中分解出运动系统和初级视觉系统的功能联结图,并在所有被试上都与"种子像素"方法有较高一致性.ICA在同一数据中可以同时分解出上述两个系统的功能联结图. 结论 ICA克服了"种子像素"方法的主观性,稳定、准确地从静息fMRI数据中分解出了脑功能联结图.本研究支持初级功能系统内的联系要明显强于系统间的联系的假设,显示ICA方法具有良好的临床应用潜力.     

Group independent component analysis of language fMRI from word generation tasks

Language fMRI has been used to study brain regions involved in language processing and has been applied to pre-surgical language mapping. However, in order to provide clinicians with optimal information, the sensitivity and specificity of language fMRI needs to be improved. Type II error of failing to reach statistical significance when the language activations are genuinely present may be particularly relevant to pre-surgical planning, by falsely indicating low surgical risk in areas where no activations are shown. Furthermore, since the execution of language paradigms involves cognitive processes other than language function per se, the conventional general linear model (GLM) method may identify non-language-specific activations. In this study, we assessed an exploratory approach, independent component analysis (ICA), as a potential complementary method to the inferential GLM method in language mapping applications. We specifically investigated whether this approach might reduce type II error as well as generate more language-specific maps. Fourteen right-handed healthy subjects were studied with fMRI during two word generation tasks. A similarity analysis across tasks was proposed to select components of interest. Union analysis was performed on the language-specific components to increase sensitivity, and conjunction analysis was performed to identify language areas more likely to be essential. Compared with GLM, ICA identified more activated voxels in the putative language areas, and signals from other sources were isolated into different components. Encouraging results from one brain tumor patient are also presented. ICA may be used as a complementary tool to GLM in improving pre-surgical language mapping.     

全面性癫痫伴热性惊厥附加症GABRG2基因突变的筛查

目的:筛查全面性癫痫伴热性惊厥附加症(GEFS+)患者的GABRG2基因,并探讨GEFS+与GABRG2基因的关系。方法:收集49例患者及110例正常对照组血样,应用变性高效液相色谱技术对GABRG2基因的10个编码外显子及与mRNA剪接有关的内含子进行筛查,对发现异常洗脱峰者进行测序。结果:未发现GABRG2基因突变,但发现1个单核苷酸多态性(SNP)位点:Exon2-89T>A(rs2284782)。这个SNP位点在两组中基因型和等位基因频率的分布差异无统计学意义(P>0.05)。结论:GABRG2基因突变可能不是GEFS+患者主要的致病原因,SNP(rs2284782)在患者与正常对照者中分布无明显差异。     

健康老年人脑默认网络:独立成分分析联合相关分析的初步探讨

目的 初步探讨独立成分分析与相关分析对健康老年默认网络(DMN)提取的一致性。方法 利用3.0T MR及8通道头线圈获得18名健康老年受试者的静息态fMRI数据。采用SPM软件对静息态数据进行预处理,以GIFT软件行独立成分分析,AFNI软件行相关分析,对比两种方法获得的DMN。 结果 两种方法间,除海马结构外,健康老年受试者DMN的脑功能区组成较为一致。后扣带回作为静息态脑代谢活性最高的区域之一,与DMN的大多数组成脑区之间存在功能连接。结论 独立成分分析与相关分析对于DMN的提取存在一致性,二者结合可更加深入地探讨静息态脑功能机制。     

A unified framework for group independent component analysis for multi-subject fMRI data

Independent component analysis (ICA) is becoming increasingly popular for analyzing functional magnetic resonance imaging (fMRI) data. While ICA has been successfully applied to single-subject analysis, the extension of ICA to group inferences is not straightforward and remains an active topic of research. Current group ICA models, such as the GIFT [Calhoun, V.D., Adali, T., Pearlson, G.D., Pekar, J.J., 2001. A method for making group inferences from functional MRI data using independent component analysis. Hum. Brain Mapp. 14, 140–151.] and tensor PICA [Beckmann, C.F., Smith, S.M., 2005. Tensorial extensions of independent component analysis for multisubject FMRI analysis. Neuroimage 25, 294–311.], make different assumptions about the underlying structure of the group spatio-temporal processes and are thus estimated using algorithms tailored for the assumed structure, potentially leading to diverging results. To our knowledge, there are currently no methods for assessing the validity of different model structures in real fMRI data and selecting the most appropriate one among various choices. In this paper, we propose a unified framework for estimating and comparing group ICA models with varying spatio-temporal structures. We consider a class of group ICA models that can accommodate different group structures and include existing models, such as the GIFT and tensor PICA, as special cases. We propose a maximum likelihood (ML) approach with a modified Expectation–Maximization (EM) algorithm for the estimation of the proposed class of models. Likelihood ratio tests (LRT) are presented to compare between different group ICA models. The LRT can be used to perform model comparison and selection, to assess the goodness-of-fit of a model in a particular data set, and to test group differences in the fMRI signal time courses between subject subgroups. Simulation studies are conducted to evaluate the performance of the proposed method under varying structures of group spatio-temporal processes. We illustrate our group ICA method using data from an fMRI study that investigates changes in neural processing associated with the regular practice of Zen meditation.     

ECG-based gating in ultra high field cardiovascular magnetic resonance using an independent component analysis approach

Background

In Cardiovascular Magnetic Resonance (CMR), the synchronization of image acquisition with heart motion is performed in clinical practice by processing the electrocardiogram (ECG). The ECG-based synchronization is well established for MR scanners with magnetic fields up to 3 T. However, this technique is prone to errors in ultra high field environments, e.g. in 7 T MR scanners as used in research applications. The high magnetic fields cause severe magnetohydrodynamic (MHD) effects which disturb the ECG signal. Image synchronization is thus less reliable and yields artefacts in CMR images.

Methods

A strategy based on Independent Component Analysis (ICA) was pursued in this work to enhance the ECG contribution and attenuate the MHD effect. ICA was applied to 12-lead ECG signals recorded inside a 7 T MR scanner. An automatic source identification procedure was proposed to identify an independent component (IC) dominated by the ECG signal. The identified IC was then used for detecting the R-peaks. The presented ICA-based method was compared to other R-peak detection methods using 1) the raw ECG signal, 2) the raw vectorcardiogram (VCG), 3) the state-of-the-art gating technique based on the VCG, 4) an updated version of the VCG-based approach and 5) the ICA of the VCG.

Results

ECG signals from eight volunteers were recorded inside the MR scanner. Recordings with an overall length of 87 min accounting for 5457 QRS complexes were available for the analysis. The records were divided into a training and a test dataset. In terms of R-peak detection within the test dataset, the proposed ICA-based algorithm achieved a detection performance with an average sensitivity (Se) of 99.2%, a positive predictive value (+P) of 99.1%, with an average trigger delay and jitter of 5.8 ms and 5.0 ms, respectively. Long term stability of the demixing matrix was shown based on two measurements of the same subject, each being separated by one year, whereas an averaged detection performance of Se = 99.4% and +P = 99.7% was achieved.Compared to the state-of-the-art VCG-based gating technique at 7 T, the proposed method increased the sensitivity and positive predictive value within the test dataset by 27.1% and 42.7%, respectively.

Conclusions

The presented ICA-based method allows the estimation and identification of an IC dominated by the ECG signal. R-peak detection based on this IC outperforms the state-of-the-art VCG-based technique in a 7 T MR scanner environment.     

海洛因成瘾者大脑突显性网络异常的独立成分分析

目的探讨海洛因成瘾者大脑突显性网络的变化特征。材料与方法 26例海洛因成瘾者与39例年龄、性别、教育程度相匹配的健康被试参加本静息态功能性磁共振成像(functional magnetic resonance imaging,f MRI)研究数据处理,运用独立成分分析方法对影像数据提取突显性网络,比较该网络功能连接的差异,探讨差异脑区功能连接与海洛因吸食史的相关性。结果与正常组相比,海洛因成瘾者大脑左侧岛叶功能连接显著性增强,且与海洛因食用剂量成正相关(P=0.02,r=0.46)。结论长期吸食海洛因的成瘾者突显性网络功能连接异常增强,突显性网络在海洛因成瘾过程中发挥重要作用。     

Principal component analysis of the T wave in patients with chest pain and conduction disturbances

There is a need for markers reflecting the increased risk in patients with conduction disturbances. Conduction disturbances presumably cause inhomogeneous repolarization that may create an arrhythmogenic substrate. In patients with normal conduction, parameters derived from principal components analysis (PCA) of the T wave contain prognostic information. The nondipolar PCA components are assumed to reflect repolarization inhomogeneity. This study examined the PCA parameters in relation to conduction disturbances. PCA was performed on continuously recorded 12-lead ECGs in 800 patients with chest pain and nondiagnostic ECG on admission. The patients with conduction disturbance on admission were classified into separate groups and related to comparison groups without conduction disturbance recruited from the same series. For each patient, the dipolar and nondipolar components were quantified by medians of the ratio of the two largest eigenvalues (S2/S1 Median), the residue that summarizes the eigenvalues S4-S8 (TWRabsMedian) and the ratio of this residue to the total power of the T wave (TWRrelMedian). The parameters were assessed with respect to common clinical and ECG parameters, discharge diagnosis, and total mortality during a 35-month follow-up. TWRabsMedian increased with increasing conduction disturbance. In 135 patients with conduction disturbances, ROC curves for TWRabsMedian as indicator of mortality exhibited areas under a curve of 0.66, 0.65, and 0.56 at 6-month, 24-month, and 35-month follow-up. Conduction disturbances were associated with increased nondipolar PCA component and, thus, with increased repolarization inhomogeneity. The nondipolar PCA component contained a moderate amount of prognostic information not present in a simple ECG diagnosis of a conduction disturbance.     

Multivariate analysis of clinical and biological data in cirrhotic patients: application to prognosis

One hundred and thirty-one patients underwent clinical and biological investigation with the following determinations performed on the same day; presence or absence of ascites, icterus and/or encephalopathy, coagulation study, biochemical determinations including albumin, transferrin and immunoglobulins immunoassays. The principal component analysis of biological data showed two sets of highly representative and inversely correlated data; one included coagulation tests, albumin and transferrin, and the other included immunoglobulin A/transferrin ratio, immunoglobulin A and total bilirubin. Clinical and biological data were computed using discriminant analysis between dead and survivors. Six parameters were then selected (total bilirubin, encephalopathy, factor V, AST, antithrombin III and transferrin) giving a correct prognosis in 81.6% (31/38) of cases in a test sample. Neither ascites nor immunoglobulins were useful for the estimation of the prognosis.     

单细胞转录组测序分析揭示腹膜透析患者透析流出液T淋巴细胞的改变

目的 揭示腹膜透析（PD）患者透析流出液中T淋巴细胞随PD时间延长的改变轨迹,探究其与PD相关腹膜纤维化的关系。方法 对笔者前期研究获取的10例PD患者（短期PD组6例,长期PD组4例）透析流出液细胞的单细胞转录组数据进行细胞分类,提取出T淋巴细胞的数据进行2组间的差异分析、通路富集分析;同时收集23例患者PD治疗前及开始后随访的血常规数据,比较PD开始前后免疫细胞组成的差异。结果 PD患者透析流出液中T淋巴细胞在免疫细胞总数中的占比随PD时间延长增加（P < 0.05）。差异分析显示转化生长因子-β1（TGF-β1）和其他纤维化相关的信号通路在长期PD组的腹腔T淋巴细胞中富集。与开始透析前全血细胞计数结果比较,短期及长期PD组患者的淋巴细胞计数均升高,但在比例上呈现为先上升后下降的趋势。结论 长期PD治疗导致的腹膜纤维化与T淋巴细胞密切相关,PD流出液中T淋巴细胞的变化可能是腹腔环境等多因素共同作用的结果。     

Tracer kinetics analysis of dynamic contrast‐enhanced CT and MR data in patients with squamous cell carcinoma of the upper aerodigestive tract: comparison of the results

Purpose: (i) To evaluate the feasibility of tracer kinetics analysis of dynamic contrast‐enhanced (DCE) CT and T2‐weighted MR data of squamous cell carcinoma (SCCA) of the upper aerodigestive tract. (ii) To compare functional parameters derived by both modalities and examine the interchangeability of them as well as the intra‐ and inter‐rater agreement. Materials and methods: Dynamic contrast‐enhanced‐CT and MR images of 23 patients with SCCA were postprocessed using a distributed‐parameter (DP) tracer kinetic model. The evaluated parameters included blood flow (F), intravascular blood volume (v₁), extravascular extracellular blood volume (v₂), intravascular mean transit time (t₁), lag time (t₀), permeability surface area product (PS) and extraction ratio (E). Mean perfusion values, based on region‐of‐interest analysis, of the tumors and the healthy muscle tissue were compared and correlated. Inter‐rater and intra‐rater variability were assessed. Interchangeability of the tumor functional parameters was tested using Pearson’s correlation coeficients and Bland–Altman plots. Results: The mean values in tumor and healthy muscle tissues were significantly different for each modality (0·0001≤P≤0·03). The mean values of all tumor perfusion parameters apart from v₂ and E were significantly different (0·001≤P≤0·009) between the two modalities. The intra‐rater variability was good to very good for all parameters. The inter‐rater variability was moderate to good. Bland–Altman plots of F, t₁, t₀, and v₂ showed moderate interchangeability. There was a proportionality error in v₁ and PS graphs. Conclusion: The estimation of functional parameters in SCCA is feasible using DCE‐CT and ‐MR with a DP model. The parameters are mostly significantly different and the interchangeability of them is limited.     

2007年北京地区在透析血液透析患者进入透析时心脑血管合并症——BJHDQCIC统计结果分析

目的统计并分析2007年北京地区在透析血液透析患者进入透析时心脑血管并发症患病率。方法北京市血液透析质量控制和改进中心(Beijing Hemodialysis Quality ControlImprovement Center,BJHDQCIC)收集北京地区各血液透析中心2007年在透析血液透析患者资料,大多数血液透析中心使用北京市汇百通公司"血液透析管理软件",部分使用access数据库上报。BJHDQCIC将access数据库和汇百通数据库合并形成包含所有上报信息的数据库。结果2007年在透析患者共7795例,92.4%性别资料完整,(男性51.9%,女性48.1%)。2007年在透析患者致病原因前四位依次为慢性肾炎(30.8%),糖尿病肾病(21.0%),高血压(14.7%),慢性间质性肾炎(10.7%),是北京地区维持性血液透析患者的主要病因(共77.2%)。41～70岁是在透患者主要年龄段,共占63.6%。在透析患者首次透析时缺血性心脏病患病率为43.5%;心肌梗死患病率为13.8%;心律失常患病率为30.5%。充血性心力衰竭患病率为48.4%,高血压患病率为87.7%。脑血管病患病率为19.6%。外周血管病患病率为12.9%。结论提示在透析患者心血管疾病(cardiavascular disease,CVD)、脑血管意外(cerebrovascular accidents,CVA)的患病率较高;要充分认识终末期肾病患者合并CVD、CVA的危险性,积极预防和控制CVD、CVA传统的危险因素如高血压、糖尿病等。