Thesis defense Hanneke Keijzer (Donders series 564)

13 September 2022

Promotors: Prof. Dr. C.J.M. Klijn, Prof. Dr. J. Hofmeijer
Co-promotor: Dr. C.W.E. Hoedemaekers

Cracking coma: MRI and EEG markers of outcome after cardiac arrest
Approximately 50% of comatose patients after cardiac arrest will never regain consciousness or will not recover to an independent state of life. Accurate prediction of chances of neurological recovery is important to inform treatment decisions, but predictive values of classical predictors, such as brain stem reflexes, EEG and SSEP, are limited. Within this thesis, we investigated if MRI modalities and novel quantitative EEG markers can aid to improve outcome prediction after cardiac arrest.
In part 1 of this thesis, we show that MRI markers focussing on brain diffusion metrics, such as DWI and DTI, show additional predictive value for the prediction of poor neurological outcome. On the other hand, functional MRI seems to be a promising marker for the prediction of good neurological outcome.
In Part 2 of this thesis, we show that EEG based functional connectivity may add to outcome prediction after cardiac arrest, especially when applying a machine learning model. In addition, various quantitative EEG features can identify patients possible at risk for delirium.
Overall, MRI and novel quantitative EEG metrics are promising to add to reliable outcome prediction of comatose patients after cardiac arrest.