Canonical correlation analysis in the study of cerebral and peripheral haemodynamics interrelations with systemic variables in neonates supported on ECMO.

Neonates supported on extracorporeal membrane oxygenation (ECMO) are at high risk of brain injury due to haemodynamic instability. In order to monitor cerebral and peripheral (muscle) haemodynamic and oxygenation changes in this population we used a dual-channel near-infrared spectroscopy (NIRS) system. In addition, to assess interrelations between NIRS and systemic variables, collected simultaneously, canonical correlation analysis (CCA) was employed.

Extending the c-statistic to nominal polytomous outcomes: the Polytomous Discrimination Index.

Diagnostic problems in medicine are sometimes polytomous, meaning that the outcome has more than two distinct categories. For example, ovarian tumors can be benign, borderline, primary invasive, or metastatic. Extending the main measure of binary discrimination, the c-statistic or area under the ROC curve, to nominal polytomous settings is not straightforward.

Incorporating structural information from the multichannel EEG improves patient-specific seizure detection.

Objective: A novel patient-specific seizure detection algorithm is presented. As the spatial distribution of the ictal pattern is characteristic for a patient's seizures, this work incorporates such information into the data representation and provides a learning algorithm exploiting it.

Methods: The proposed training algorithm uses nuclear norm regularization to convey structural information of the channel-feature matrices extracted from the EEG.

Cardiac autonomic dysfunction in West syndrome.

Background: West syndrome is an age-dependent epileptic encephalopathy. Autonomic changes are increasingly being recognized in patients with epilepsy: cardiac autonomic function is mediated by sympathetic and parasympathetic efferent activity to the heart and can provide information on the functional state of the autonomic nervous system. The goal of the study is to evaluate the effect of an early epileptic encephalopathy on the autonomic nervous system by measuring heart rate variability.

Relationship of EEG sources of neonatal seizures to acute perinatal brain lesions seen on MRI: a pilot study.

Even though it is known that neonatal seizures are associated with acute brain lesions, the relationship of electroencephalographic (EEG) seizures to acute perinatal brain lesions visible on magnetic resonance imaging (MRI) has not been objectively studied. EEG source localization is successfully used for this purpose in adults, but it has not been sufficiently explored in neonates. Therefore, we developed an integrated method for ictal EEG dipole source localization based on a realistic head model to investigate the utility of EEG source imaging in neonates with postasphyxial seizures.

Clinically oriented three-step strategy for assessment of adnexal pathology.

Objective: To determine the diagnostic performance of ultrasound-based simple rules, risk of malignancy index (RMI), two logistic regression models (LR1 and LR2) and real-time subjective assessment by experienced ultrasound examiners following the exclusion of masses likely to be judged as easy and 'instant' to diagnose by an ultrasound examiner, and to develop a new strategy for the assessment of adnexal pathology based on this.

Methods: 3511 patients with at least one persistent adnexal mass preoperatively underwent transvaginal ultrasonography to assess tumor morphology and vascularity. They were included in two consecutive prospective studies by the International Ovarian Tumor Analysis (IOTA) group: Phase 1 (1999-2005), development of the simple rules and logistic regression models LR1 and LR2, and Phase 2, a validation study (2005-2007).

A mathematical model for interpretable clinical decision support with applications in gynecology.

Background: Over time, methods for the development of clinical decision support (CDS) systems have evolved from interpretable and easy-to-use scoring systems to very complex and non-interpretable mathematical models. In order to accomplish effective decision support, CDS systems should provide information on how the model arrives at a certain decision. To address the issue of incompatibility between performance, interpretability and applicability of CDS systems, this paper proposes an innovative model structure, automatically leading to interpretable and easily applicable models.

Detection of intracavitary uterine pathology using offline analysis of three-dimensional ultrasound volumes: interobserver agreement and diagnostic accuracy.

Objective: To estimate the diagnostic accuracy and interobserver agreement in predicting intracavitary uterine pathology at offline analysis of three-dimensional (3D) ultrasound volumes of the uterus.

Methods: 3D volumes (unenhanced ultrasound and gel infusion sonography with and without power Doppler, i.e.

Application of kernel principal component analysis for single-lead-ECG-derived respiration.

Recent studies show that principal component analysis (PCA) of heartbeats is a well-performing method to derive a respiratory signal from ECGs. In this study, an improved ECG-derived respiration (EDR) algorithm based on kernel PCA (kPCA) is presented. KPCA can be seen as a generalization of PCA where nonlinearities in the data are taken into account by nonlinear mapping of the data, using a kernel function, into a higher dimensional space in which PCA is carried out.

The "why" and "how" of JointICA: results from a visual detection task.

Since several years, neuroscience research started to focus on multimodal approaches. One such multimodal approach is the combination of electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). However, no standard integration procedure has been established so far.

Independent component analysis as a preprocessing step for data compression of neonatal EEG.

We propose a novel approach for compressive sampling of the neonatal electro-encefalogram (EEG) data. The method assumes that the set of EEG data is generated by linearly mixing a fewer number of source signals. Another assumption is that the sources are nearly-sparse in Gabor dictionary.

Automated way to obtain motor units' signatures and estimate their firing patterns during voluntary contractions using HD-sEMG.

A new, automated way to obtain signatures of active motor units (MUs) from high density surface EMG recordings during voluntary contractions is presented. It relies on clustering of repetitive shapes corresponding to different MU action potentials (MUAPs) present. The number of clusters and the mean shapes of the MUAPs as observed on the electrode grid, are estimated in a fast way without user interaction.

Time-frequency heart rate variability characteristics of young adults during physical, mental and combined stress in laboratory environment.

The goal of this study was to evaluate the changes in heart rate variability (HRV) parameters due to a specific physical, mental or combined load. More specifically, the difference in effect between mental load and physical activity is studied. In addition, the effect of the combined physical and mental demand on the HRV parameters was examined and compared with the changes during the single task.

External validation of diagnostic models to estimate the risk of malignancy in adnexal masses.

Purpose: To externally validate and compare the performance of previously published diagnostic models developed to predict malignancy in adnexal masses.

Experimental Design: We externally validated the diagnostic performance of 11 models developed by the International Ovarian Tumor Analysis (IOTA) group and 12 other (non-IOTA) models on 997 prospectively collected patients. The non-IOTA models included the original risk of malignancy index (RMI), three modified versions of the RMI, six logistic regression models, and two artificial neural networks.

Quantitative autism traits in first degree relatives: evidence for the broader autism phenotype in fathers, but not in mothers and siblings.

Autism spectrum disorder (ASD) symptoms are present in unaffected relatives and individuals from the general population. Results are inconclusive, however, on whether unaffected relatives have higher levels of quantitative autism traits (QAT) or not. This might be due to differences in research populations, because behavioral data and molecular genetic research suggest that the genetic etiology of ASD is different in multiplex and simplex families.

A novel approach to predict the likelihood of specific ovarian tumor pathology based on serum CA-125: a multicenter observational study.

Background: The CA-125 tumor marker has limitations when used to distinguish between benign and malignant ovarian masses. We therefore establish likelihood curves of six subgroups of ovarian pathology based on CA-125 and menopausal status.

Methods: This cross-sectional study conducted by the International Ovarian Tumor Analysis group involved 3,511 patients presenting with a persistent adnexal mass that underwent surgical intervention.

Autonomic effects of refractory epilepsy on heart rate variability in children: influence of intermittent vagus nerve stimulation.

Aim: Vagus nerve stimulation (VNS) is a therapeutic option for individuals with refractory epilepsy. Individuals with refractory epilepsy are prone to dysfunction of the autonomic nervous system. Reduced heart rate variability is a marker of dysfunction of the autonomic nervous system.

Nonlinear heart rate dynamics: circadian profile and influence of age and gender.

Heart rate variability (HRV) is used as a marker of autonomic modulation of heart rate. Nonlinear HRV parameters providing information about the scaling behaviour or the complexity of the cardiac system were included. In addition, the chaotic behaviour was quantified by means of the recently developed numerical noise titration technique.

Exploiting spatial information to estimate metabolite levels in two-dimensional MRSI of heterogeneous brain lesions.

MRSI provides MR spectra from multiple adjacent voxels within a body volume represented as a two- or three-dimensional matrix, allowing the measurement of the distribution of metabolites over this volume. The spectra of these voxels are usually analyzed one by one, without exploiting their spatial context. In this article, we present an advanced metabolite quantification method for MRSI data, in which the available spatial information is considered.

Support vector methods for survival analysis: a comparison between ranking and regression approaches.

Objective: To compare and evaluate ranking, regression and combined machine learning approaches for the analysis of survival data.

Methods: The literature describes two approaches based on support vector machines to deal with censored observations. In the first approach the key idea is to rephrase the task as a ranking problem via the concordance index, a problem which can be solved efficiently in a context of structural risk minimization and convex optimization techniques.

Systematic analysis of secreted proteins reveals synergism between IL6 and other proteins in soft agar growth of MCF10A cells.

Introduction: Breast cancer, the most common malignancy in women, still holds many secrets. The causes for non-hereditary breast cancer are still unknown. To elucidate any role for circulating naturally secreted proteins, a screen of secreted proteins' influence of MCF10A cell anchorage independent growth was set up.

Automated artifact removal as preprocessing refines neonatal seizure detection.

Objective: The description and evaluation of algorithms using Independent Component Analysis (ICA) for automatic removal of ECG, pulsation and respiration artifacts in neonatal EEG before automated seizure detection.

Methods: The developed algorithms decompose the EEG using ICA into its underlying sources. The artifact source was identified using the simultaneously recorded polygraphy signals after preprocessing.

Lobular and non-lobular breast cancers differ regarding axillary lymph node metastasis: a cross-sectional study on 4,292 consecutive patients.

Invasive lobular carcinoma (ILC) accounts for 8-14% of all breast cancers and carries distinct prognostic and biologic implications. The goal of our study was to investigate the impact of lobular histology on axillary lymph node (ALN) involvement. This is a cross-sectional study of 4,292 consecutive patients surgically treated for breast carcinoma at the University Hospitals Leuven.