Forum for Science, Industry and Business

Sponsored by:     3M 
Search our Site:

 

EEG predicts response to medication for schizophrenia

05.08.2010
A commonplace electroencephalography (EEG) test may hold the key to predicting whether a person will respond to certain prescribed drugs, particularly those related to psychiatric conditions.

In a study to be published by Clinical Neurophysiology, and now posted online, engineering and health sciences researchers at McMaster University applied machine learning to EEG patterns and successfully predicted how patients with schizophrenia would respond to clozapine therapy.

Clozapine is recognized as an effective treatment for chronic medication-resistant schizophrenia but can produce serious side effects such as seizures, cardiac arrhythmias or bone marrow suppression. Some patients can develop blood problems that are life-threatening. Weekly to monthly blood sampling is required.

"Some people can suffer terrible side effects from clozapine," said Dr. Gary Hasey, associate professor at McMaster and director of the Transcranial Magnetic Stimulation laboratory at St. Joseph's Healthcare Mood Disorders Clinic in Hamilton. "The logistic difficulties for the patient and treatment team are also substantial. A method to reliably determine, before the onset of therapy, whether a patient will or will not respond to clozapine would greatly assist the clinician in determining whether the risks and logistic complexity of clozapine are outweighed by the potential benefits."

To conduct the study, EEGs were taken from 23 patients diagnosed with medication-resistant schizophrenia before they began taking clozapine. Twelve were men and 11 were women, all of middle age. The brainwave patterns and response to the clozapine therapy of these patients were used to "train" a computer algorithm to predict whether or not a specific patient will respond to the drug. The prediction accuracy was approximately 89 per cent. This algorithm showed similar predictive accuracy when it was further tested in a new group of 14 additional patients treated with clozapine.

This innovative work grows out of the close collaborative relationship between members of the Department of Electrical and Computer Engineering (Prof. James Reilly, Ph.D. student Ahmad Khodayari-Rostamabad), the School of Biomedical Engineering (Prof. Hubert de Bruin), and the Department of Psychiatry and Behavioural Neurosciences (Drs. Gary Hasey and Duncan MacCrimmon).

"The computational power available today supports new machine learning methodologies that can help doctors better diagnose and treat illness and disease," said Prof. Reilly. "Large amounts of data can be processed very quickly to identify patterns or predict outcomes. We're looking forward to applying the findings to other areas."

EEG records the brain's electrical activity close to the scalp. Traditionally, it has been used to monitor for epilepsy, and to diagnose coma, encephalopathies, and brain death. EEG is still often used as a first-line method to diagnose tumors, stroke and other focal brain disorders.

"EEG is an inexpensive, non-invasive technique widely available in smaller hospitals and in community laboratories," explains Dr. MacCrimmon. "Also, EEG readings take only 20 to 30 minutes of a patient's time, with no preparation required, so pose minimal inconvenience."

Funding for the research was provided in part by The Magstim Company Ltd., a developer and manufacturer of medical and research devices for the neurological and surgical fields. The company is based in Wales, U.K.

The researchers now plan to test their findings on a larger sample group. They have successfully demonstrated the application of machine learning methods for analyzing EEG signals to predict the response to various treatments available for patients with other psychiatric conditions, specifically major depression. They have also demonstrated the effectiveness of machine learning methods as a diagnostic tool for distinguishing various forms of psychiatric illness. It may also be possible to incorporate a range of other clinical and laboratory data such as personality inventory scores, personal and demographic information and treatment history to improve performance.

Gene Nakonechny | EurekAlert!
Further information:
http://www.mcmaster.ca

More articles from Studies and Analyses:

nachricht Innovative genetic tests for children with developmental disorders and epilepsy
11.07.2018 | Christian-Albrechts-Universität zu Kiel

nachricht Oxygen loss in the coastal Baltic Sea is “unprecedentedly severe”
05.07.2018 | European Geosciences Union

All articles from Studies and Analyses >>>

The most recent press releases about innovation >>>

Die letzten 5 Focus-News des innovations-reports im Überblick:

Im Focus: Future electronic components to be printed like newspapers

A new manufacturing technique uses a process similar to newspaper printing to form smoother and more flexible metals for making ultrafast electronic devices.

The low-cost process, developed by Purdue University researchers, combines tools already used in industry for manufacturing metals on a large scale, but uses...

Im Focus: First evidence on the source of extragalactic particles

For the first time ever, scientists have determined the cosmic origin of highest-energy neutrinos. A research group led by IceCube scientist Elisa Resconi, spokesperson of the Collaborative Research Center SFB1258 at the Technical University of Munich (TUM), provides an important piece of evidence that the particles detected by the IceCube neutrino telescope at the South Pole originate from a galaxy four billion light-years away from Earth.

To rule out other origins with certainty, the team led by neutrino physicist Elisa Resconi from the Technical University of Munich and multi-wavelength...

Im Focus: Magnetic vortices: Two independent magnetic skyrmion phases discovered in a single material

For the first time a team of researchers have discovered two different phases of magnetic skyrmions in a single material. Physicists of the Technical Universities of Munich and Dresden and the University of Cologne can now better study and understand the properties of these magnetic structures, which are important for both basic research and applications.

Whirlpools are an everyday experience in a bath tub: When the water is drained a circular vortex is formed. Typically, such whirls are rather stable. Similar...

Im Focus: Breaking the bond: To take part or not?

Physicists working with Roland Wester at the University of Innsbruck have investigated if and how chemical reactions can be influenced by targeted vibrational excitation of the reactants. They were able to demonstrate that excitation with a laser beam does not affect the efficiency of a chemical exchange reaction and that the excited molecular group acts only as a spectator in the reaction.

A frequently used reaction in organic chemistry is nucleophilic substitution. It plays, for example, an important role in in the synthesis of new chemical...

Im Focus: New 2D Spectroscopy Methods

Optical spectroscopy allows investigating the energy structure and dynamic properties of complex quantum systems. Researchers from the University of Würzburg present two new approaches of coherent two-dimensional spectroscopy.

"Put an excitation into the system and observe how it evolves." According to physicist Professor Tobias Brixner, this is the credo of optical spectroscopy....

All Focus news of the innovation-report >>>

Anzeige

Anzeige

VideoLinks
Industry & Economy
Event News

Leading experts in Diabetes, Metabolism and Biomedical Engineering discuss Precision Medicine

13.07.2018 | Event News

Conference on Laser Polishing – LaP: Fine Tuning for Surfaces

12.07.2018 | Event News

11th European Wood-based Panel Symposium 2018: Meeting point for the wood-based materials industry

03.07.2018 | Event News

 
Latest News

A smart safe rechargeable zinc ion battery based on sol-gel transition electrolytes

20.07.2018 | Power and Electrical Engineering

Reversing cause and effect is no trouble for quantum computers

20.07.2018 | Information Technology

Princeton-UPenn research team finds physics treasure hidden in a wallpaper pattern

20.07.2018 | Materials Sciences

VideoLinks
Science & Research
Overview of more VideoLinks >>>