A Multimodal Approach to Personalized Tracking of Evolving State-Of-Consciousness in Brain- Injured Patients.
In this project FRRB finances Partner number 5: University of Milan, Milano. The Principal Investigator responsible of the project is Dr. Mario Rosanova.
FRRB also finances partner number 3: Fondazione Don Carlo Gnocchi Santa Maria Nascente, IRCCS. The Principal Investigator is Dr. Angela Comanducci.
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Pathology of interest: |
State-Of-Consciousness in Brain-Injured Patients |
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Area of research: |
Neurological disorders |
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Start date: |
June 1st, 2020 |
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End date: |
May 31st , 2023 |
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Funding: |
€ 499.900,00 |
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Project partners: |
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PROJECT SUMMARY
Improved treatment of severe brain injuries has resulted in increased survival rates. While some of these patients regain consciousness after a transient state of coma, others may develop a disorder of consciousness (DoC).
Diagnosis of DoC currently relies on standardized behavioural assessment. The importance of accuracy in such diagnosis cannot be overstated, as it guides critical decisions on treatment (including pain management), and could underlie end-of-life decisions. Despite this importance, current behavioral diagnosis often fails, if because of the major sensory and motor deficits associated with DoC, or because of the heterogeneous etiology and pathophysiology associated with the condition.
Finally, the need for accurate diagnosis and prognosis transcends the needs of the patients alone: caregiving of these patients is very stressful, principally for the large uncertainty associated with them.
Thus, more accurate diagnosis and prognosis provides major relief for caregivers, and paradoxically, even if the news is not "good".
For all these reasons it is critical to developing personalized diagnosis and prognosis prediction tools that permit a stratified analysis at the single-patient level.
The PerBrain Project will benefit from the multidisciplinary partners’ expertise, and the unique opportunity to perform longitudinal assessments in four clinical sites through both established and novel electrophysiological, neuroimaging and physiological techniques.
Based on the collected data, we will develop a multimodal personalized diagnostic tool for DoC patients using state-of-the-art computational tools, such as machine learning, in order to better determine the current state (diagnosis) and future outcome (prognosis). The overall aim of this project will provide for a better understanding of the pathophysiological mechanisms in DoC, which will, in turn, allow personalized rehabilitation strategies, and improved single-patient predictions of state and prognosis.
EraPerMed results of the JTC2019 available for download here: http://www.erapermed.eu/