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What did the project achieve?
“Our preliminary results are encouraging, taking us one step closer to a new test that can help diagnose children with autism spectrum condition faster and earlier,” says Professor Aneta Stefanovska of the University of Lancaster. “This could help reduce long periods of uncertainty for families and mean that they can access the care and support they need sooner.”
Autism spectrum conditions (ASC) affect around one in 100 UK children.1 A child with ASC is likely to have difficulties in communicating with and relating to other people. Early diagnosis is crucial so that families can get access to the correct care and support they need.
Currently, a child who is suspected of having ASC will undergo a series of interviews and behavioural tests that involve many different experts. Piecing together the results can be challenging and it can take a long time to get a diagnosis.
“We are aiming to develop a simple new test that could help doctors diagnose ASC earlier,” says Professor Stefanovska. “This is based on a combination of a well-known non-invasive technique called electroencephalography (EEG) that measures electrical activity in the brain, and then applying our new physics-based methods to analyse the data.”
In this study, the researchers took EEG recordings from two groups of children all aged between three and five years of age – 15 who had recently been diagnosed with ASC and 17 who had no signs of the condition. They then analysed these data to look for differences between the groups.
“We identified specific patterns of electrical activity that can accurately and reliably tell apart the children diagnosed with ASC from those who do not have the condition,” says Professor Stefanovska. “We are now carrying out a new study involving a larger number of children to confirm these findings.”
References
- National Institute for Health and Care Excellence, Clinical Knowledge Summaries: Autism in Children https://cks.nice.org.uk/autism-in-children#!backgroundsub:2 [website accessed 26 August 2018]
This research was completed on
Evidence suggests at least one in 100 children in the UK has an autism spectrum condition (ASC).1-3 Diagnosis can take a long time, and often follows a period of uncertainty in a child’s early years when it is unclear whether or not the child actually has an ASC. A team led by Professor Aneta Stefanovska, of the University of Lancaster, is developing an objective new way to diagnose ASCs much earlier, perhaps even in babies. This could reduce uncertainty and give families access to the support they need sooner.
What is the problem and who does it affect?
“As the name implies, the abilities and difficulties of children with autism spectrum conditions (or ASCs) vary widely,” explains Dr Megan Thomas. “However, all of these children will have problems with communication, social interaction and what we call flexibility of thought. This affects how the children make sense of the world around them and relate to other people, including their family and friends.”
Although ASCs are lifelong conditions, they aren’t usually diagnosed until children are at least two years old.4
“There is no single medical test for ASCs,” says Dr Thomas. “Diagnosis typically requires a period of observation, when information is gathered from a range of sources including parents, educational settings, speech and language therapists, and doctors. This clearly takes time and there are sometimes differences of opinion between professionals. The process can be distressing for families, and without a correct diagnosis it can be difficult for children and their families to access the care and support they need.”
What is the project trying to achieve?
“We are developing a sophisticated new way to diagnose ASCs in young children,” says Professor Stefanovska. “Our pioneering new technique involves assessing how children’s brain waves interact with each other.”
Around 40 children between three and four years old are taking part in this pilot study. Half have recently been diagnosed with an ASC. The children’s brain waves are being recorded over 20-30 minutes using a technique called EEG, or electroencephalography. During EEG the children are having sensors, which detect electrical activity in the brain, attached to their scalp with paste.
“If our results are promising, we plan further tests in a much larger group of children. Our work may allow earlier, quicker and more reliable diagnosis of ASCs, which could reduce stress on families, cut NHS costs, and allow children to get the support they need sooner,” says Professor Stefanovska. “Eventually, our work may also lead to new therapies.”
What are the researchers’ credentials?
“Our team combines the expertise of physicists and specialised children’s doctors – a very unusual mix,” says Professor Stefanovska. “The physicists are world leaders in the techniques that are being used in this study. The experienced clinical team works with children with ASCs on a daily basis and has excellent facilities.”
References
1. Baird G et al. Prevalence of disorders of the autism spectrum in a population cohort of children in South Thames: the Special Needs and Autism Project (SNAP)Lancet 2006; 368: 210–15.
2. Office for National Statistics. Mental health of children and young people in Great Britain, 2004. Palgrave Macmillan 2005. http://www.esds.ac.uk/doc/5269/mrdoc/pdf/5269technicalreport.pdf Website accessed 5 June 2013.
3. NICE Clinical Guidance 128. Autism diagnosis in children and young people. http://www.nice.org.uk/nicemedia/live/13572/56428/56428.pdf Website accessed 5 June 2013
4. Ambitious about Autism. How to get a diagnosis of autism. http://www.ambitiousaboutautism.org.uk/page/about_autism/support/i_think... Website accessed 5 June 2013.
Project Leader | Professor A Stefanovska MEng MSc PhD |
Project Team | Dr Megan Thomas BSc MBChB DRCOG FRCP FRCPCH PhDProfessor Peter VE McClintock BSc DPhil DSc FInstP CPhys |
Project Location | Department of Physics, Lancaster University |
Project Location Other | Blackpool Teaching Hospitals NHS Foundation Trust |
Project duration | 3 years |
Date awarded | 1 May 2013 |
Project start date | 1 July 2013 |
Project end date | 31 March 2017 |
Grant amount | £79,117 |
Grant code | GN1963 |
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