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Contact Information

Scientific Coordinator
Mark van Gils
VTT Technical Research Centre of Finland
P.O. Box 1300
33101 Tampere
tel. +358 20 722 3342

Project Manager
Harri Siitari
VTT Technical Research Centre of Finland
P.O. Box 106
20521 Turku
tel. +358 40 078 4517


Traumatic brain injury (TBI) occurs when a sudden trauma causes damage to the brain. Every year, over 1,600,000 patients sustain a traumatic brain injury in the EU, and 70,000 of these die, with a further 100,000 being left handicapped. Significantly, 75% of the victims are children and young adults, and TBI is the leading cause of disability in people under 40 years of age. Traumatic brain injury results in more lost working years than cancers, stroke and HIV/AIDS together.  On a global scale, the number of life years lost due to traumatic brain injury is four times that of diabetes-related loss. Recent statistics show a steep increase in the incidence of TBIs, with an increase of 21% over the last five years – threefold greater than the rate of increase in population. Despite this, TBI has been seriously underrepresented in medical R&D efforts compared to many other, less significant health problems.

Due to a vast degree of variation in the injuries of individual patients, the methods currently in use in the treatment of brain injury patients lack strong scientific evidence.


TBIcare provides an objective and evidence-based solution for management of TBI by improving diagnostics and treatment decisions for an individual patient by matching a patient’s individual data with the injury’s characteristics. In this way it allows each brain injury patient to receive individual treatment that is optimised for his or her needs.

Project Outcome

The project develops a tool that will make the day-to-day clinical work of doctors easier and also revolutionise the treatment of traumatic brain injury. This software tool will enable doctors to match the patient-related variables with the injury-related variables through the combined use of various databases. Using extensive database and system simulation, the software will then form a detailed analysis of the nature of the patient’s brain injury, its optimal treatment and predicted outcome. A scenario illustrating the TBIcare concept is given in the box text.


An example TBIcare scenario

Harry has been in a serious car accident. When entering the University Hospital, he is conscious but somnolent, confused and suffers from severe headache. As other bodily injuries he has a pelvic fracture with moderate intra-abdominal bleeding, as well as external wounds and crushes. All clinical parameters are checked carefully, including detailed assessment of vital and neurological functions. A laboratory screen is carried out, including available measures of brain injury biomarkers and general physiologic state. A head and body CT-scan is taken after stabilizing the vital functions. Brain CT reveals diffuse axonal injury and fronto-temporal contusions.

The main question is: should the pelvic fracture be stabilized operatively due to bleeding or is external stabilization sufficient – which solution forms a smaller risk for the injured brain? All clinical, imaging, and laboratory values have automatically been transferred into the TBIcare software which calculates the expected risks for the available treatment alternatives in regard to TBI outcome, thus helping the treating clinician to make the best choice. Corresponding treatment decisions will be made several times during the acute in-hospital care period, each time with the help of TBIcare which has collected the relevant variables during the stay, thus guiding the care to produce an optimal outcome.



Project Outline – Work towards Scientific and Technical Objectives

The project has 2 scientific objectives that are supplemented by three technical objectives. Together they define how the work in the project is carried out.



Scientific Objective 1: Development of a methodology for finding efficient combinations of multi-modal biomarkers in statistical models to objectively diagnose and assess an individual TBI patient

The first objective is addressed by using an approach in which a high number of vital signs or biomarkers, relevant to TBIs, are explored from sets of heterogeneous data. These include, for example, structural and functional changes visible in imaging data (computerised tomography, CT; magnetic resonance imaging, MRI; positron emission imaging, PET), changes in electrophysiology (electroencephalography, EEG); changes in bedside multimodality monitoring parameters including systemic cardiac and respiratory physiology, intracranial pressure (ICP), and brain chemistry (monitored by oxygen sensors and microdialysis); and changes in metabolomics visible in the blood. We define sets of biomarkers from several thousand brain injury cases retrospectively, and from several hundred TBI cases and healthy controls prospectively. The goal is to build statistical models allowing standardised and objective interpretation of data from a single patient. The diagnostic rules are derived by comparing the patient data to the most similar cases in a database using statistical inference.


Scientific Objective 2: Development of a simulation model based for objectively predicting outcome of the planned treatment of an individual TBI patient.

Work towards this objective uses the aforementioned statistical models as basis for the construction of a simulation model. Due to the unique responses to treatments, the simulation model must be individualised. The model is personalized for each patient separately using data only from similar cases. Various approaches can be used for the simulations, such as, concepts from system dynamics or Bayesian networks. In the TBIcare concept individual physiological measures and various treatments form the building blocks of the system dynamics model which is used to predict the outcome.

The simulation model provides important information both for scientists and clinical practitioners. It helps a scientist to better understand a human as a system – a viewpoint central to the Virtual Physiological Human. A clinician is able to test the influence of various treatments by first simulating them. As the variability of the individuals and traumas is huge, we do not expect that a simulation model built from hundreds of cases is enough for reliable prediction of the outcome. However, our aim is to develop a strictly evidence based simulation model for objectively predicting the outcome of treatment and rehabilitation of an individual TBI patient. The model provides objective evidence based information about the most probable outcome and will be a step towards scientifically valid approach for the treatment planning. This model will be a basis for future development, where an increasing amount of validated clinical data will continuously improve the reliability and usability of the model. In addition, this kind of model may be used to optimize the diagnostic procedure in TBIs, e.g. it may advise the clinician to take some further tests in order to improve the reliability of the model for a certain individual.

These scientific objectives are supplemented by realization of three technical objectives:

  • a software solution to be used in daily practice to diagnose and plan treatments;
  • new approaches for extracting information from multi-source and multi-scale physiological databases for management of an extremely heterogeneous disease;
  • and development of innovative data quantification methods for the clinical TBI environment.

 By reaching these objectives, TBIcare transfers the scientific Virtual Physiological Human (VPH) concepts to clinical practice.

TBIcare has impacts for healthcare professionals by improving the healthcare process and increasing medical knowledge; for the patients and their nearest by increased quality adjusted life years; for society it brings reduction in healthcare costs and losses due to working disability, and for the European industry it brings an impetus to increased global competitiveness by providing immediately exploitable innovative methods.


This EU co-funded project has started on 1 February 2011. It is co-ordinated by VTT Technical Research Centre of Finland and the consortium includes GE Healthcare Ltd. (UK), Turku University Central Hospital (Finland), University of Cambridge (UK), Imperial College London (UK), Complexio S.a.r.L. (France), Kaunas University of Technology (Lithuania), and GE Healthcare Finland Oy.