Objective: To improve the accuracy and reliability of the localisation of epileptogenic activity using spatially filtered MEG data.
Methods: A synthetic epileptic source was embedded in healthy brain activity in different orientations in order to estimate how reliably this signal containing high levels of kurtosis can be localised. An existing approach (SAM(g2)) was compared to a new implementation of the methodology.
Results: The results confirm that a kurtosis beamformer is an effective tool with which to localise spontaneous epileptiform activity. However, it is crucial that the orientation of source reconstruction matches that of the true source otherwise the epileptic activity is either mis-localised or completely missed. Therefore as the original SAM(g2) implementation is restricted to the tangential plane, in certain circumstances it will perform poorly compared to the approach described here.
Conclusions: A kurtosis beamformer is made more accurate and more robust if the analysis is not restricted to the tangential plane and if the optimisation routine for selecting the source orientation is performed using kurtosis rather than power.
Significance: MEG is increasingly being used for the non-invasive localisation of epileptic biomagnetic signals and the implementation described in this paper increases the clinical utility of the technique.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.clinph.2012.09.024 | DOI Listing |
J Acoust Soc Am
June 2022
Department of Naval Architecture and Ocean Engineering, Seoul National University, Seoul 08826, Republic of Korea.
Ray-based blind deconvolution (RBD) is a method that estimates the source waveform and channel impulse response (CIR) using the ray arrival in an underwater environment. The RBD estimates the phase of the source waveform by using beamforming. However, low sampling, array shape deformation, and other factors can cause phase errors in the beamforming results.
View Article and Find Full Text PDFClin Neurophysiol
September 2021
Aston Institute of Health and Neurodevelopment, College of Health and Life Sciences, Aston University, Birmingham, UK; Children's Epilepsy Surgery Program, The Birmingham Women's and Children's NHS Foundation Trust, Birmingham, UK.
Objective: To assess the feasibility of automatically detecting high frequency oscillations (HFOs) in magnetoencephalography (MEG) recordings in a group of ten paediatric epilepsy surgery patients who had undergone intracranial electroencephalography (iEEG).
Methods: A beamforming source-analysis method was used to construct virtual sensors and an automatic algorithm was applied to detect HFOs (80-250 Hz). We evaluated the concordance of MEG findings with the sources of iEEG HFOs, the clinically defined seizure onset zone (SOZ), the location of resected brain structures, and with post-operative outcome.
Biomed Opt Express
April 2021
Department of Biomedical Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA.
Ovarian cancer is the fifth most common cause of death due to cancer, and it is the deadliest of all gynecological cancers. Diagnosing ovarian cancer via conventional photoacoustic delay-and-sum beamforming (DAS) presents several challenges, such as poor image resolution and low lesion to background tissue contrast. To address these concerns, we propose an improved beamformer named lag-based delay multiply and sum combined with coherence factor (DMAS-LAG-CF).
View Article and Find Full Text PDFClin Neurophysiol
April 2021
Department of Biomedical Engineering, The University of Melbourne, Parkville, VIC, Australia; Department of Medicine, The University of Melbourne, Fitzroy, VIC, Australia; Graeme Clark Institute for Biomedical Engineering, The University of Melbourne, Parkville, VIC, Australia.
Objective: Magnetoencephalography (MEG) kurtosis beamforming is an automated localization method for focal epilepsy. Visual examination of virtual sensors, which are source activities reconstructed by beamforming, can improve performance but can be time-consuming for neurophysiologists. We propose a framework to automate the method and evaluate its effectiveness against surgical resections and outcomes.
View Article and Find Full Text PDFClin Neurophysiol Pract
March 2020
HUS Medical Imaging Center, BioMag Laboratory, University of Helsinki and Helsinki University Hospital, Finland.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!