PM.20.032 – Improving diagnostics and prognostics in disorders of consciousness: An integrative approach

Route: Personalised medicine: the individual at the centre

Cluster question: 104 How do we develop minimally invasive techniques and interventions for diagnosis, prognosis, and treatment?

Due to improvements in emergency treatment and life support, more people survive life-threatening incidents such as a cardiac arrest and traumatic brain injury, but subsist with a disorder of consciousness (DOC). The care for DOC patients causes significant burden to families, caregivers and society. DOC comprises three main diagnostic entities: coma, unresponsive wakefulness syndrome (UWS, previously known as vegetative state) and minimally conscious state (MCS). Diagnostic error is common among DOC patients; reports consistently find that approximately 30-40% of people diagnosed with UWS actually retain some level of conscious awareness. While misdiagnosis may contribute to inappropriate medical care and premature withdrawal of life-sustaining treatment, the current ‘gold standard’ for the detection of conscious awareness is limited to behavioural assessments that are prone to subjective bias and confounding factors. Thus, there is an urgent need to improve DOC diagnosis by developing and testing novel, non-invasive markers of conscious awareness. We will address this issue by adopting a multimodal, integrative approach based on recent advances in functional magnetic resonance imaging (fMRI), magnetoencephalography (MEG), electroencephalography (EEG), eye tracking, and the analysis of facial expressions based on electromyography (EMG) and video recordings. Consortium members will work together to identify new markers of conscious awareness, and integrate these into new, non-invasive tools for objective DOC diagnostics and prognostics. As such, the consortium will form a broad, nation-wide multidisciplinary team of experts in neuroimaging, eye and face tracking, neurophysiology, machine learning and signal analysis, DOC, long-term medical care, and industrial partners. The consortium further connects to the expertise network ‘Expertisenetwerk Ernstig Niet-aangeboren Hersenletsel Na Coma’ (www.eennacoma.net). The envisioned technical advances will personalize care and rehabilitation to improve the quality of life of DOC patients on the basis of objective and reliable assessments of their condition.

Keywords

Diagnosis, Disorders of Consciousness, Eye and Face Tracking, machine learning, Neuroimaging, prognosis

Other organisations

Amsterdam UMC, Braingaze NL, Cognition and Behaviour;, Donders Institute for Brain, Universiteit Twente (UT)

Submitter

Organisation Radboudumc (RUMC)
Name Dr. Koen V. Haak
E-mail k.haak@donders.ru.nl
Website https://www.ru.nl/personen/haak-k/