0000000000243210
AUTHOR
Sabine Van Huffel
showing 14 related works from this author
Cardiorespiratory information dynamics during mental arithmetic and sustained attention
2015
An analysis of cardiorespiratory dynamics during mental arithmetic, which induces stress, and sustained attention was conducted using information theory. The information storage and internal information of heart rate variability (HRV) were determined respectively as the self-entropy of the tachogram, and the self-entropy of the tachogram conditioned to the knowledge of respiration. The information transfer and cross information from respiration to HRV were assessed as the transfer and cross-entropy, both measures of cardiorespiratory coupling. These information-theoretic measures identified significant nonlinearities in the cardiorespiratory time series. Additionally, it was shown that, alt…
Differentiation between Brain Metastasis and Glioblastoma using MRI and two-dimensional Turbo Spectroscopic Imaging data
2009
In this paper we propose a novel technique to differentiate brain metastases from high-grade gliomas, which represent the most aggressive and common brain lesions. In spite of the significant progresses achieved in the field of MRI in the last decades, the differentiation between these two types of tumors is still a challenge as they show a similar appearance on MRI images, but require a completely different therapeutic treatment. Here, we show that such a differentiation is actually possible and can be obtained by making use of MRI as well as of two-dimensional Turbo Spectroscopic Imaging (2D-TSI) information. Specifically, the proposed technique consists of three steps: we first detect th…
Differentiation between brain metastases and glioblastoma multiforme based on MRI, MRS and MRSI
2009
Brain metastases and glioblastoma multiforme are the most aggressive and common brain tumours in adults and they require a different clinical management. Anatomical magnetic resonance imaging (MRI) or clinical history, cannot always clearly distinguish between them. This study describes and verifies the use of magnetic resonance spectroscopy (MRS) and magnetic resonance spectroscopic imaging (MRSI) in combination with MRI for differential diagnosis of glioblastomas and metastases. Feature selection methods are applied to the magnetic resonance (MR) spectra of 121 patients and relevant features are detected. Different classification methods are used to distinguish glioblastoma multiforme and…
On the Implementation of HealthAgents: Agent-Based Brain Tumour Diagnosis
2007
This paper introduces HealthAgents, an EC-funded research project to improve the classification of brain tumours through multi-agent decision support over a secure and distributed network of local databases or Data Marts. HealthAgents will not only develop new pattern recognition methods for distributed classification and analysis of in vivo MRS and ex vivo/in vitro HRMAS and DNA data, but also define a method to assess the quality and usability of a new candidate local database containing a set of new cases, based on a compatibility score. Using its Multi-Agent architecture, HealthAgents intends to apply cutting-edge agent technology to the Biomedical field and develop the HealthAgents net…
Fast nosological imaging using canonical correlation analysis of brain data obtained by two-dimensional turbo spectroscopic imaging.
2007
A new fast and accurate tissue typing technique has recently been successfully applied to prostate MR spectroscopic imaging (MRSI) data. This technique is based on canonical correlation analysis (CCA), a statistical method able to simultaneously exploit the spectral and spatial information characterizing the MRSI data. Here, the performance of CCA is further investigated by using brain data obtained by two-dimensional turbo spectroscopic imaging (2DTSI) from patients affected by glioblastoma. The purpose of this study is to investigate the applicability of CCA when typing tissues of heterogeneous tumors. The performance of CCA is also compared with that of ordinary correlation analysis on s…
Modelling of Magnetic Resonance Spectra Using Mixtures for Binned and Truncated Data
2007
Magnetic Resonance Spectroscopy (MRS) provides the biochemical composition of a tissue under study. This information is useful for the in-vivo diagnosis of brain tumours. Prior knowledge of the relative position of the organic compound contributions in the MRS suggests the development of a probabilistic mixture model and its EM-based Maximum Likelihood Estimation for binned and truncated data. Experiments for characterizing and classifying Short Time Echo (STE) spectra from brain tumours are reported.
Model-Based Evaluation of Methods for Respiratory Sinus Arrhythmia Estimation
2021
OBJECTIVE: Respiratory sinus arrhythmia (RSA) refers to heart rate oscillations synchronous with respiration, and it is one of the major representations of cardiorespiratory coupling. Its strength has been suggested as a biomarker to monitor different conditions, and diseases. Some approaches have been proposed to quantify the RSA, but it is unclear which one performs best in specific scenarios. The main objective of this study is to compare seven state-of-the-art methods for RSA quantification using data generated with a model proposed to simulate, and control the RSA. These methods are also compared, and evaluated on a real-life application, for their ability to capture changes in cardior…
Information dynamics in cardiorespiratory time series during mental stress testing
2014
In this study, we assessed the information dynamics of respiration and heart rate variability during mental stress testing by means of the cross-entropy, a measure of cardiorespiratory coupling, and the self-entropy of the tachogram conditioned to the knowledge of respiration. Although stress is related to a reduction in vagal activity, no difference in cardiorespiratory coupling was found when 5 minutes of rest and stress were compared. The conditional self-entropy, on the other hand, showed significantly higher values during stress, indicating a higher predictability of the tachogram. These results show that entropy analyses of cardiorespiratory data reveal new information that could not …
Information Transfer Between Respiration and Heart Rate During Sleep Apnea
2016
It is well-known that sleep apnea affects the respiration and the heart rate (HR), and studies have shown that the cardiorespiratory coupling is also compromised during obstructive sleep apnea (OSA). Furthermore, the classification of hypopneas is challenging, in particular when only ECG-derived features are used. In this context, this study investigates how different ECG-derived respiratory (EDR) signals resemble the respiratory effort during different types of apneas, and how the amount of information transferred from respiration to HR varies according to the respiratory signal used, real or ECG-derived. ECG and respiratory signals of 10 patients suffering from sleep apnea were analysed, …
Quantifying brain tumor tissue abundance in HR-MAS spectra using non-negative blind source separation techniques
2012
Given high-resolution magic angle spinning (HR-MAS) spectra from several glial tumor subjects, our goal is to differentiate between tumor tissue types by separating the different sources that contribute to the profile of each spectrum. Blind source separation techniques are applied for obtaining characteristic profiles for necrosis, highly cellular tumor and border tumor tissue and providing the contribution (abundance) of each of these tumor tissue types to the profile of each spectrum. The problem is formulated as a non-negative source separation problem. Non-negative matrix factorization, convex analysis of non-negative sources and non-negative independent component analysis methods are …
Investigating cardiac and respiratory determinants of heart rate variability in an information-theoretic framework.
2014
This study was aimed at comparing two alternative information-theoretic approaches for the combined analysis of heart rate variability (HRV) and respiration variability (RV). The approaches decompose the predictive information about HRV in two terms, quantifying respectively the information stored into HRV and that transferred to HRV from RV. Storage and transfer were assessed by the popular self entropy (SE) and transfer entropy (TE) measures, as well as by the alternative conditional SE (cSE) and cross entropy (CE) measures. The comparison was performed at a theoretical level, computing the exact values of the four measures for simulated cardiorespiratory dynamics, and on real data, estim…
Multiproject–multicenter evaluation of automatic brain tumor classification by magnetic resonance spectroscopy
2008
[EN] Automatic brain tumor classification by MRS has been under development for more than a decade. Nonetheless, to our knowledge, there are no published evaluations of predictive models with unseen cases that are subsequently acquired in different centers. The multicenter eTUMOUR project (2004-2009), which builds upon previous expertise from the INTERPRET project (2000-2002) has allowed such an evaluation to take place. A total of 253 pairwise classifiers for glioblastoma, meningioma, metastasis, and low-grade glial diagnosis were inferred based on 211 SV short TE INTERPRET MR spectra obtained at 1.5 T (PRESS or STEAM, 20-32 ms) and automatically pre-processed. Afterwards, the classifiers …
Information dynamics in cardiorespiratory analyses: application to controlled breathing
2014
Voluntary adjustment of the breathing pattern is widely used to deal with stress-related conditions. In this study, effects of slow and fast breathing with a low and high inspiratory to expiratory time on heart rate variability (HRV) are evaluated by means of information dynamics. Information transfer is quantified both as the traditional transfer entropy as well as the cross entropy, where the latter does not condition on the past of HRV, thereby taking the highly unidirectional relation between respiration and heart rate into account. The results show that the cross entropy is more suited to quantify cardiorespiratory information transfer as this measure increases during slow breathing, i…
Interictal cardiorespiratory variability in temporal lobe and absence epilepsy in childhood
2015
It is well known that epilepsy has a profound effect on the autonomic nervous system, especially on the autonomic control of heart rate and respiration. This effect has been widely studied during seizure activity, but less attention has been given to interictal (i.e. seizure-free) activity. The studies that have been done on this topic, showed that heart rate and respiration can be affected individually, even without the occurrence of seizures. In this work, the interactions between these two individual physiological variables are analysed during interictal activity in temporal lobe and absence epilepsy in childhood. These interactions are assessed by decomposing the predictive information …