Quantitative brain network biomarkers for patient-specific diagnostics in idiopathic generalized epilepsy

Informations projet

NETBIO-GE

N° de convention de subvention: 750884

DOI

10.3030/750884

Projet clôturé

Date de signature de la CE 27 Février 2017

Date de début 1 Octobre 2017

Date de fin 30 Septembre 2019

Financé au titre de

• EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions

Coût total

€ 195 454,80

Contribution de l’UE

€ 195 454,80

Coordonné par

KING'S COLLEGE LONDON
United Kingdom

Periodic Reporting for period 1 - NETBIO-GE (Quantitative brain network biomarkers for patient-specific diagnostics in idiopathic generalized epilepsy)

Période du rapport: 2017-10-01 au 2019-09-30

Résumé du contexte et des objectifs généraux du projet

PROBLEMS AND OBJECTIVES
Genetic (or idiopathic) generalised epilepsies (GGE) are well-known seizure disorders that affect roughly 30-40% of all patients with epilepsy. Although they can, in principle, be identified relatively easily, misdiagnosis and thus late initiation of treatment is still common. This is because electroencephalography and neuroimaging, important diagnostic tools, lack sensitivity and specificity. The first problem we address is thus whether we can improve diagnostics by modern neuroimaging that measures brain connectivity patterns in individual GGE patients.

The second problem we address is variability in clinical presentation. Although GGE have been historically classified based on age of presentation and seizure types patients suffer from, there is a lot of overalp in practice. Thus, while some experts assert that GGE are a group of distinct disease entitites, others say it is rather a spectrum, with different expression in individuals. Using the same neuroimaging technology, we aim to test as a secondary objective, whether there is structural overlap between GGE types.

As a final problem, we will explore whether brain connectivity patterns associate with medication response.


IMPORTANCE FOR SOCIETY
Epilepsies are common and debilitating disorders that generate a lot of individual suffering, reduce quality of life and shorten life spans. It also produces a sizable amount of direct and indirect costs via increased utilisation of health care systems and loss of productivity. Improving diagnostics can hasten therapeutic interventions and thus reduce mortality and morbidity in epilepsy. We hope this project will contribute to this effort.

Travail effectué depuis le début du projet jusqu’à la fin de la période considérée dans le rapport et principaux résultats atteints jusqu’à présent

"This project was an MSCA-IF-Action that contained both a scientific part, a training part for the fellow, and scientific outreach.

WORK
We have tested and deployed a sequence of advanced, quantitative MRI acquisition technology to measure brain connections and their composition. We have acquired MRI and EEG data in a group of healthy control subjects and persons living with a variety of GGE syndromes and are in the process of analysing the data set. In parallel, we have collaborated with other scientists to improve brain connectivity methods in epilepsy (see below) and worked on available epilepsy connectivity data to improve their value and provide further insight into disordered brain connectivity in seizure disorders.


TRAINING
The fellow underwent rigorous training in EEG and MRI data acquisition, preprocessing and analysis, including basic time-series and network analysis methods. He had exposure to personal development and leadership training through dedicated initiatives at King's College London's Insitute of Psychiatry, Psychology, and Neuroscience.

OUTREACH AND COLLABORATIONS
We presented interim results from our work at internal and departmental meetings, as well as the 13th European Congress on Epileptology in Vienna (August 2018). To open up our project to the wider academic and non-academic public, we teamed up with artists at created a multi-media and action art peace that reflected upon the role of brain connectivity, epilepsy, well-being and our environment, which we named ""The Cerebral City"" (a video showcasing our work is here: https://www.kcl.ac.uk/cultural/-/projects/the-cerebral-city). We continued, initiated and maintained close collaborations with scientists working on brain connectivity using different methods, particularly EEG signal analysis, both externally (Prof John Terry and Dr Marc Goodfellow, https://emps.exeter.ac.uk/mathematics/staff/jt354/research_group) and internally (Prof Zoran Cvetkovic and Prof Osvaldo Simeone, https://nms.kcl.ac.uk/osvaldo.simeone/index.htm). Our work is disseminated by publication in scientific journals and made open access whenever possible (see http://epilepsy-london.org/epilepsy-research-publications/). We also keep open repositories of data and code (see https://osf.io/uyv6e/)."

Progrès au-delà de l’état des connaissances et impact potentiel prévu (y compris l’impact socio-économique et les conséquences sociétales plus larges du projet jusqu’à présent)

PROGRESS AND EXPECTED RESULTS
After acquiring a data set of n = 43, we have successfully secured more funding to further increase the sample size to around 70 subjects and continue NETBIO after the end of the action. We expect to obtain brain connectivity results and a first paper within the first months of 2020, and a final set of results by end of that year. Preliminary findings suggest that our connectivity methods might be able to explain EEG dynamics in GGE, a results that has not been obtained before.

An abstract graphic or brain connections assessed in the NETBIO-GE project