Towards Evidence-Based Diagnosis and Treatment Planning in Traumatic Brain Injury

1. Towards Evidence-Based Diagnosis and Treatment Planning in Traumatic Brain Injury Mark van Gils, mark.vangils@vtt.fi VTT Technical Research Centre of Finland

2. Traumatic Brain Injury (TBI) - Facts • TBI is the most common cause of permanent disability in people under the age of 40 years • In developed countries, TBI causes more loss of productive life years than cancer, cerebrovascular diseases, and HIV/AIDS combined • The yearly costs from TBI in Europe exceed 100 billion euros • There is a steep increase in the incidence of TBIs, with an increase of 21 % over the last five years • Until now, TBI has been seriously underrepresented in medical R&D efforts

3. “Our most complex disease in our most complex organ” • Individualvariability • Age • Gender • Cognitivereserve • Education • PreviousTBIs • Pre-injuryhealth • Geneticproperties… Howshould I treat??? • Injuryvariability • Mechanism • Haematomas • Contusions • Axonalinjury • Oedema • Concomitant injuries • Intracranialpressure • Neuroinflammation • … • Treatmentvariability • Treatmentdelays • Surgicalmeasures • Cerebral bloodflowmaintenance • Seizuredetection and treatment • ICP treatment • Rehabilitation… Outcome

4. To produce a software tool which is able to: • Give an accurate estimate about the nature of the injury (= improved diagnostics) • Assist in selecting the most appropriate treatment for this particular patients (= improved care) The idea: • To combine modern statistical methods and system simulation modeling, and • Data mining methodology, and • Modern automatic tools to quantify heterogenous physiological data, and • Large databases with clinical TBI data (including outcome)

5. Impact of TBIcare For healthcare professionals - optimizes the treatment process, and increases medical knowledge, aids in everyday diagnostics and treatment planning For the patients and their nearest - minimizes the burden of the injury, it increases quality adjusted life years; For society - brings reduction in healthcare costs, minimizes losses of productive life years, and For the European industry - it gives an impetus to increased global competitiveness by providing immediately exploitable innovative methods.

6. Data used for modelling and validation The following datasets are used for modelling of TBI-related clinical data: * From University of Cambridge and Turku University Hospital, incl. detailed clinical data + blood biomarkers + acute and late MRI + multifactorial outcome

7. Image quantification: automatic segmentation of cortical and subcortical structures from MRI images; quantification pathologies from multi-modal MRI, CT and PET images Assessment brain connectivity using diffusion MR images Metabolomics and lipidomics & Gene expression analysis: Search new metabolomics, lipidomics and genetics biomarkers related to TBIs EEG measurements and analysis: obtain relevant EEG features as input for care decision making; methods for detection of epileptic seizures and other adverse events EIS measurements and analysis: investigate the potential of a novel technology based on electric impedance spectroscopy (EIS) to rapidly reveal structural changes in TBI Prospective assessment of innovative non-invasive absoluteICP value meter: hardware and software solutions for fast, accurate and reliable non-invasive absolute ICP measurements for early diagnosing of TBI

8. Model and software development Modeling and software developementhastwo main objectives: • develop a statisticalmodelthatpredicts the outcomefromheterogeneouspatientmeasurements and biomarkersand • implement the model in a software toolmeetingclinicalrequirements in the care of traumaticbrain injuries and • develop a socio-economic simulation model for understanding interconnections of different aspects in traumatic brain injuries.

9. Lessons learned • Collecting good quality heterogeneous data from different centres is a complex task that requires full commitment from partners, good coordination but also a lot of flexibility and ability to deal with many surprises. But, in the end the result is extremely valuable. • From a data-analysis point-of-view, the task of helping to improve diagnosis in TBI is a very complex problem, with a huge amount of different variables and extremely diverse personalised patient profiles. • Even the smallest progress is very worthwhile though, as the issue being worked upon is a major source of costs to the healthcare system, and potential costs savings are in the order of billions of Euro’s per year.

10. Contact information • Scientific Coordinator Mark van Gils VTT Technical Research Centre of Finland P.O. Box 1300 33101 Tampere Finland tel. +358 20 722 3342 mark.vangils@vtt.fi www.tbicare.eu twitter.com/tbicare Partners: VTT (FIN), GE Healthcare Ltd. (UK), Turku University Central Hospital (FIN), University of Cambridge (UK), Imperial College London (UK), Complexio (FRA), Kaunas University of Technology (LT), GE Healthcare Finland Oy (FIN) Duration: Feb 2011 – Jul 2014 Budget 4.2 M€, EC contribution 3.2 M€