ENSEMBLE - European Newborn Study: Early Markers for a Better LifE

En cours

Funding date : 2022-2027

Amount : 1 583 000 € over 5 years

The ENSEMBLE project is an ambitious program of applied research aimed at setting up a program for reliable early detection of cerebral palsy (before the age of 6 months, when the diagnosis is currently made between the ages of 2 and 5 years). Early diagnosis should allow patients to benefit from effective individualized treatments during the critical period of brain development when neuroplasticity can reorganize neural networks and reduce possible deficits.
The project involves the collaboration of 15 European partners, including several French centers, who are among the world’s leading experts in the field. Training clinical teams in international clinical practice recommendations to reduce the age of diagnosis and the age of referral to CP-specific early intervention programs will be the first component of this project. The prospective collection of a large number of clinical data (big data), their analysis by artificial intelligence (machine learning), will allow the development and verification of a model detection of cerebral palsy (2nd part) and the implementation of individualized therapeutic interventions (personalized medicine). Finally, a third component will evaluate the impact of early diagnosis on the family, its relationship to the child and the proposed management, to reduce their stress and give them the weapons to best support the development of their child.
The project was co-designed by experts from the disciplines needed for the project and families with lived experience of cerebral palsy (including a family council) both involved in the reflection and then in the conduct of the project.
The results of this project will have a positive impact on clinical practice by identifying CP at an early stage, improving both the care and quality of life of children with CP and their families. In addition to the benefits offered to children directly involved in the project, ENSEMBLE will allow a wide application of the results to children who are at risk of cerebral palsy due to the conditions of their birth and it will establish a large database which can be used for further studies allowing new developments.
This project will start in April 2022 and will last 5 years

Team Context Objectives & Methodology Status Perspectives To go futher

Team

An interdisciplinary and multicultural research project

This project will be carried out by a complementary European consortium in partnership with families through the establishment within the project of a family advisory council (FAC). Gathered around Professor Manon Benders (Neonatalogy, Netherlands), Professor Andrea Guzzetta (Neuropediatrics, Italy) and Mr JF Mangin (Machine Learning, France), the consortium is composed of world-renowned experts in the field of neonatal neurology and infant development, particularly with regard to the methodologies explored in the project (i.e., neuro-imaging, electrophysiology, general motion, and HINE). More importantly, a comprehensive team of experts in machine learning, information technology and bio-engineering will be a key component of the consortium and will enable the development of the machine learning prediction model. The consortium is characterized by the synergy between leading clinical and fundamental research teams and the CATI multicentre neuroimaging platform, which will allow the introduction of behavioural evaluations, EEGs, MRIs and standardized clinical features throughout the European Union. Thus 15 partners including 8 clinical teams from 5 European countries (Germany, Spain, France, Italy and the Netherlands) will participate in ENSEMBLE.

The following teams will be involved in this project:

Pr Manon Benders, University Medical Center and Wilhelmina Children's Hospital, Utrecht, The Netherlands (coordinator)
Pr Andrea Guzetta, Pisa University, Italy (coordinator)
Mr Jean-François Mangin, CEA, Gif sur Yvette, France (coordinator)
Ms Jessica Dubois, INSERM, Paris, France
Pr Valérie Biran, APHP Robert Debré, Paris, France
Pr Nathalie Bednarek, American Memorial University Hospital, Reims, France
Pr Elie Saliba, Tours University, France
Pr Olivier Claris, Hospices Civils de Lyon, France
Pr Luca Ramenghi , IRCCS Istituto Giannina Gaslini, Genoa, Italy
Pr Fabio Mosca and Pr Monica Fumagalli IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milano, Italy
Pr Luca Filippi, Pisa University, Italy
Dr Adelina Pellicer, University Hospital La Paz, Madrid, Spain
Pr Ursula Felderhoff-Müser, Essen University Hospital, Essen, Germany
Dr Peter Marschik, University Medical Center Goettingen, Germany
Dr Marjolijn Ketelaar, University Medical Center, Utrecht, The Netherlands

ENSEMBLE 2

Context

Cerebral palsy (CP) is the most common cause of motor disability, but it is still diagnosed too late. As a result, the vast majority of children with cerebral palsy do not receive a dedicated intervention before their second birthday, worsening their motor and cognitive development, Most of the neuroplasticity window for motor learning is lost. Use of specific and reliable tools for the early detection of infants with CP is among the first international clinical practice recommendations. Infants with perinatal CP risk factors can be diagnosed early and reliably at less than 6 months by combining brain magnetic resonance imaging (MRI) and, depending on the age of the child, general motion assessment (GMA) and/or neurological examination of Hammersmith infants (HINE). In addition, electroencephalogram (EEG) is essential for defining and monitoring the level of brain maturation and seizures in high-risk newborns, helping to predict their evolution. Since cerebral palsy is a heterogeneous condition, it is essential to be able to formulate the functional prognosis of the child at a very young age, so that clinicians and families are informed and can make the best decisions about treatment goals and interventions. Machine learning is promising in terms of improving the prediction of long-term motor and cognitive outcomes, but its value must be studied in a large sample in order to demonstrate its validity and allow its large-scale application in clinical practice.

Objectives & Methodology

The overall objective of the ENSEMBLE project is to improve the lives of children at high risk of developing cerebral palsy (PC) and their families through a partnership between researchers and families in Europe. This project will explore the role of early diagnosis tools through the following two main objectives:

1/ Improve CP early detection health programs by implementing international clinical practice recommendations, to reduce the age at diagnosis and the age of referral to CP-specific early intervention programs.

Coordinator : Pr Andrea Guzzetta (Italy)

Trainings/e-learning at the five neonatal centres in France and Italy and their correspondents (networking) will be set up to promote the implementation of international guidelines on early diagnosis, monitoring and intervention.

2/ Develop and evaluate a long-term motor and cognitive learning prediction model based on established clinical markers, including neonatal neuroimaging, neuro-monitoring and functional evaluations to enable earlier diagnosis of newborns at risk of CP, personalized intervention and to improve assessment of neuro-developmental prognosis (motor and cognitive)

Coordinator : Pr Manon Benders (Pays-Bas) and Jean-François Mangin (France)

For this purpose, 1000 newborns at risk of CP will be included in 8 clinical centers and monitored until the age of 2 years. Their perinatal clinical data will be collected, including EEG, MRI, General Movement Analysis (GMA) and Hammersmith Infant Neurological Examination (HINE), as well as motor and cognitive monitoring data. These data will allow for the creation of a large database allowing machine learning analyses and thus the determination of the predictive value of the data collected independently and in combination.

ENSEMBLE 2

In addition, the project has a complementary objective

3/ Assess the impact of an early diagnosis of cerebral palsy on the psychological well-being of parents and how they manage their working lives, social relationships and the siblings of their child, as well as their ability to cope with the child’s problems (for example, pain, crying, difficulty sleeping and eating). Identify needs and preferences in the diagnosis announcement (significant information)

Head : Marjolijn Ketelaar (The Netherlands)

Families will be involved throughout the project through the establishment of a Family Advisory Council (FAC) with relays in each country. In particular, they will participate in the development of questionnaires and interviews on the impact of CP on parents and siblings.

Status

This project will begin in April 2022.

Perspectives

The results of this project will have a positive impact on clinical practice by identifying CP at an early stage, improving both the care and quality of life of children with CP and their families. In addition to the benefits offered to children directly involved in the project, ENSEMBLE will allow a wide application of the results to children who are at risk of cerebral palsy due to the conditions of their birth and it will establish a large database that can be used for further studies allowing new developments.

To go futher

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Barreto TM, Bento MN, Jagersbacher JG, Jones NS, Lucena R, Bandeira ID1. Prevalence of depression, anxiety, and substance-related disorders in parents of children with cerebral palsy: a systematic review. Dev Med Child Neurol. 2020 Feb;62(2):163-168.

Novak I, Morgan C, McNamara L, Te Velde A. Best practice guidelines for communicating to parents the diagnosis of disability. Early Hum Dev. 2019 Dec;139:104841.