A multivariate approach for processing magnetization effects in triggered event-related functional magnetic resonance imaging time series

Triggered event-related functional magnetic resonance imaging requires sparse intervals of temporally resolved functional data acquisitions, whose initiation corresponds to the occurrence of an event, typically an epileptic spike in the electroencephalographic trace. However, conventional fMRI time series are greatly affected by non-steady-state magnetization effects, which obscure initial blood oxygen level-dependent (BOLD) signals. Here, conventional echo-planar imaging and a post-processing solution based on principal component analysis were employed to remove the dominant eigenimages of the time series, to filter out the global signal changes induced by magnetization decay and to recover BOLD signals starting with the first functional volume. This approach was compared with a physical solution using radiofrequency preparation, which nullifies magnetization effects. As an application of the method, the detectability of the initial transient BOLD response in the auditory cortex, which is elicited by the onset of acoustic scanner noise, was used to demonstrate that post-processing-based removal of magnetization effects allows to detect brain activity patterns identical with those obtained using the radiofrequency preparation. Using the auditory responses as an ideal experimental model of triggered brain activity, our results suggest that reducing the initial magnetization effects by removing a few principal components from fMRI data may be potentially useful in the analysis of triggered event-related echo-planar time series. The implications of this study are discussed with special caution to remaining technical limitations and the additional neurophysiological issues of the triggered acquisition.

Diagnosis of diabetic autonomic neuropathy: a multivariate approach

In the diagnosis of diabetic autonomic neuropathy (DAN) various autonomic tests are used. We took a novel statistical approach to find a combination of autonomic tests that best separates normal controls from patients with DAN.

Uniform approach to linear and nonlinear interrelation patterns in multivariate time series

Currently, a variety of linear and nonlinear measures is in use to investigate spatiotemporal interrelation patterns of multivariate time series. Whereas the former are by definition insensitive to nonlinear effects, the latter detect both nonlinear and linear interrelation. In the present contribution we employ a uniform surrogate-based approach, which is capable of disentangling interrelations that significantly exceed random effects and interrelations that significantly exceed linear correlation. The bivariate version of the proposed framework is explored using a simple model allowing for separate tuning of coupling and nonlinearity of interrelation. To demonstrate applicability of the approach to multivariate real-world time series we investigate resting state functional magnetic resonance imaging (rsfMRI) data of two healthy subjects as well as intracranial electroencephalograms (iEEG) of two epilepsy patients with focal onset seizures. The main findings are that for our rsfMRI data interrelations can be described by linear cross-correlation. Rejection of the null hypothesis of linear iEEG interrelation occurs predominantly for epileptogenic tissue as well as during epileptic seizures.

A Systems-Level Approach to Human Epileptic Seizures

Epileptic seizures are due to the pathological collective activity of large cellular assemblies. A better understanding of this collective activity is integral to the development of novel diagnostic and therapeutic procedures. In contrast to reductionist analyses, which focus solely on small-scale characteristics of ictogenesis, here we follow a systems-level approach, which combines both small-scale and larger-scale analyses. Peri-ictal dynamics of epileptic networks are assessed by studying correlation within and between different spatial scales of intracranial electroencephalographic recordings (iEEG) of a heterogeneous group of patients suffering from pharmaco-resistant epilepsy. Epileptiform activity as recorded by a single iEEG electrode is determined objectively by the signal derivative and then subjected to a multivariate analysis of correlation between all iEEG channels. We find that during seizure, synchrony increases on the smallest and largest spatial scales probed by iEEG. In addition, a dynamic reorganization of spatial correlation is observed on intermediate scales, which persists after seizure termination. It is proposed that this reorganization may indicate a balancing mechanism that decreases high local correlation. Our findings are consistent with the hypothesis that during epileptic seizures hypercorrelated and therefore functionally segregated brain areas are re-integrated into more collective brain dynamics. In addition, except for a special sub-group, a highly significant association is found between the location of ictal iEEG activity and the location of areas of relative decrease of localised EEG correlation. The latter could serve as a clinically important quantitative marker of the seizure onset zone (SOZ).

Data-driven estimates of the number of clusters in multivariate time series

An important problem in unsupervised data clustering is how to determine the number of clusters. Here we investigate how this can be achieved in an automated way by using interrelation matrices of multivariate time series. Two nonparametric and purely data driven algorithms are expounded and compared. The first exploits the eigenvalue spectra of surrogate data, while the second employs the eigenvector components of the interrelation matrix. Compared to the first algorithm, the second approach is computationally faster and not limited to linear interrelation measures.

Multivariate modelling of responses to conditional items: New possibilities for latent class analysis

Questionnaire data may contain missing values because certain questions do not apply to all respondents. For instance, questions addressing particular attributes of a symptom, such as frequency, triggers or seasonality, are only applicable to those who have experienced the symptom, while for those who have not, responses to these items will be missing. This missing information does not fall into the category 'missing by design', rather the features of interest do not exist and cannot be measured regardless of survey design. Analysis of responses to such conditional items is therefore typically restricted to the subpopulation in which they apply. This article is concerned with joint multivariate modelling of responses to both unconditional and conditional items without restricting the analysis to this subpopulation. Such an approach is of interest when the distributions of both types of responses are thought to be determined by common parameters affecting the whole population. By integrating the conditional item structure into the model, inference can be based both on unconditional data from the entire population and on conditional data from subjects for whom they exist. This approach opens new possibilities for multivariate analysis of such data. We apply this approach to latent class modelling and provide an example using data on respiratory symptoms (wheeze and cough) in children. Conditional data structures such as that considered here are common in medical research settings and, although our focus is on latent class models, the approach can be applied to other multivariate models.

Mid-term results in relation to age and analysis of predictive factors after fixation of acetabular fractures using the modified Stoppa approach.

INTRODUCTION Data concerning outcome after management of acetabular fractures by anterior approaches with focus on age and fractures associated with roof impaction, central dislocation and/or quadrilateral plate displacement are rare. METHODS Between October 2005 and April 2009 a series of 59 patients (mean age 57 years, range 13-91) with fractures involving the anterior column was treated using the modified Stoppa approach alone or for reduction of displaced iliac wing or low anterior column fractures in combination with the 1st window of the ilioinguinal approach or the modified Smith-Petersen approach, respectively. Surgical data, accuracy of reduction, clinical and radiographic outcome at mid-term and the need for endoprosthetic replacement in the postoperative course (defined as failure) were assessed; uni- and multivariate regression analysis were performed to identify independent predictive factors (e.g. age, nonanatomical reduction, acetabular roof impaction, central dislocation, quadrilateral plate displacement) for a failure. Outcome was assessed for all patients in general and in accordance to age in particular; patients were subdivided into two groups according to their age (group "<60yrs", group "≥60yrs"). RESULTS Forty-three of 59 patients (mean age 54yrs, 13-89) were available for evaluation. Of these, anatomic reduction was achieved in 72% of cases. Nonanatomical reduction was identified as being the only multivariate predictor for subsequent total hip replacement (Adjusted Hazard Ratio 23.5; p<0.01). A statistically significant higher rate of nonanatomical reduction was observed in the presence of acetabular roof impaction (p=0.01). In 16% of all patients, total hip replacement was performed and in 69% of patients with preserved hips the clinical results were excellent or good at a mean follow up of 35±10 months (range: 24-55). No statistical significant differences were observed between both groups. CONCLUSION Nonanatomical reconstruction of the articular surfaces is at risk for failure of joint-preserving management of acetabular fractures through an isolated or combined modified Stoppa approach resulting in total joint replacement at mid-term. In the elderly, joint-preserving surgery is worth considering as promising clinical and radiographic results might be obtained at mid-term.

Time-Series Panel Analysis (TSPA): Multivariate Modeling of Temporal Associations in Psychotherapy Process.

Objective: Processes occurring in the course of psychotherapy are characterized by the simple fact that they unfold in time and that the multiple factors engaged in change processes vary highly between individuals (idiographic phenomena). Previous research, however, has neglected the temporal perspective by its traditional focus on static phenomena, which were mainly assessed at the group level (nomothetic phenomena). To support a temporal approach, the authors introduce time-series panel analysis (TSPA), a statistical methodology explicitly focusing on the quantification of temporal, session-to-session aspects of change in psychotherapy. TSPA-models are initially built at the level of individuals and are subsequently aggregated at the group level, thus allowing the exploration of prototypical models. Method: TSPA is based on vector auto-regression (VAR), an extension of univariate auto-regression models to multivariate time-series data. The application of TSPA is demonstrated in a sample of 87 outpatient psychotherapy patients who were monitored by postsession questionnaires. Prototypical mechanisms of change were derived from the aggregation of individual multivariate models of psychotherapy process. In a 2nd step, the associations between mechanisms of change (TSPA) and pre- to postsymptom change were explored. Results: TSPA allowed a prototypical process pattern to be identified, where patient's alliance and self-efficacy were linked by a temporal feedback-loop. Furthermore, therapist's stability over time in both mastery and clarification interventions was positively associated with better outcomes. Conclusions: TSPA is a statistical tool that sheds new light on temporal mechanisms of change. Through this approach, clinicians may gain insight into prototypical patterns of change in psychotherapy.

Novel prognostic markers revealed by a proteomic approach separating benign from malignant insulinomas.

The prognosis of pancreatic neuroendocrine tumors is related to size, histology and proliferation rate. However, this stratification needs to be refined further. We conducted a proteome study on insulinomas, a well-defined pancreatic neuroendocrine tumor entity, in order to identify proteins that can be used as biomarkers for malignancy. Based on a long follow-up, insulinomas were divided into those with metastases (malignant) and those without (benign). Microdissected cells from six benign and six malignant insulinomas were subjected to a procedure combining fluorescence dye saturation labeling with high-resolution two-dimensional gel electrophoresis. Differentially expressed proteins were identified using nano liquid chromatography-electrospray ionization/multi-stage mass spectrometry and validated by immunohistochemistry on tissue microarrays containing 62 insulinomas. Sixteen differentially regulated proteins were identified among 3000 protein spots. Immunohistochemical validation revealed that aldehyde dehydrogenase 1A1 and voltage-dependent anion-selective channel protein 1 showed significantly stronger expression in malignant insulinomas than in benign insulinomas, whereas tumor protein D52 (TPD52) binding protein was expressed less strongly in malignant insulinomas than in benign insulinomas. Using multivariate analysis, low TPD52 expression was identified as a strong independent prognostic factor for both recurrence-free and overall disease-related survival.

Anterior fixation of unstable pelvic ring fractures using the modified Stoppa approach: mid-term results are independent on patients' age

PURPOSE Open surgical management of unstable pelvic ring injuries has been discussed controversially compared to percutaneous techniques in terms of surgical site morbidity especially in older patients. Thus, we assessed the impact of age on the outcome following fixation of unstable pelvic ring injuries through the modified Stoppa approach. METHODS Out of a consecutive series of 92 patients eligible for the study, 63 patients (mean age 50 years, range 19-78) were evaluated [accuracy of reduction, complications, failures, Majeed-Score, Oswestry Disability Questionnaire (ODI), Mainz Pain Staging System (MPSS)] at a mean follow-up of 3.3 years (range 1.0-7.9). Logistic multivariate regression analysis was performed to assess the outcome in relation to increasing patient age and/or Injury Severity Score (ISS). RESULTS Out of 63 patients, in 36 an "anatomic" reduction was achieved. Ten postoperative complications occurred in eight patients. In five patients, failure of fixation was noted at the anterior and/or posterior pelvic ring. In 49 patients, an "excellent" or "good" Majeed-Score was obtained; the mean ODI was 14 % (range 0-76 %); 50 patients reported either no or only minor chronic pelvic pain (MPSS). Only an increasing ISS conferred an increased likelihood of the occurrence of a non-anatomical reduction, a "poor" or "fair" Majeed-Score, or an ODI >20 %. CONCLUSIONS Increasing age did not impact the analysed parameters. Open reduction and internal fixation of the anterior pelvic ring through a modified Stoppa approach in unstable pelvic ring injuries did not result in an unfavourable outcome with increasing age of patients.