Rike Barth1, Frederic Zubler2, Anja Weck3, Matthias Haenggi4, Kaspar Schindler1, Roland Wiest5, Franca Wagner5. 1. Sleep-Wake-Epilepsy Center, Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Switzerland. 2. Sleep-Wake-Epilepsy Center, Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Switzerland. Electronic address: frederic.zubler@gmail.com. 3. Department of Intensive Care Medicine, Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Intensive Care Medicine, Central Hospital Region Biel/Bienne, Biel/Bienne, Switzerland. 4. Department of Intensive Care Medicine, Inselspital, Bern University Hospital, University of Bern, Switzerland. 5. Department of Diagnostic and Interventional Neuroradiology, Support Center for Advanced Neuroimaging (SCAN), Inselspital, Bern University Hospital, University of Bern, Switzerland.
Abstract
AIM: Multimodal prognostication in comatose patients after cardiac arrest (CA) is complicated by the fact that different modalities are usually not independent. Here we set out to systematically correlate early EEG and MRI findings. METHODS: 89 adult patients from a prospective register who underwent at least one EEG and one MRI in the acute phase after CA were included. The EEGs were characterized using pre-existent standardized categories (highly malignant, malignant, benign). For MRIs, the apparent diffusion coefficient (ADC) was computed in pre-defined regions. We then introduced a novel classification based on the topography of ADC reduction (MR-lesion pattern (MLP) 1: no lesion; MLP 2: purely cortical lesions; MLP 3: involvement of the basal ganglia; MLP 4 involvement of other deep grey matter regions). RESULTS: EEG background reactivity and EEG background continuity were strongly associated with a lower MLP value (p < 0.001 and p = 0.003 respectively). The EEG categories highly malignant, malignant and benign were strongly correlated with the MLP values (rho = 0.46, p < 0.001). CONCLUSION: The MRI lesions are highly correlated with the EEG pattern. Our results suggest that performing MRI in comatose patients after CA with either highly malignant or with a benign EEG pattern is unlikely to yield additional useful information for prognostication, and should therefore be performed in priority in patients with intermediate EEG patterns ("malignant pattern").
AIM: Multimodal prognostication in comatosepatients after cardiac arrest (CA) is complicated by the fact that different modalities are usually not independent. Here we set out to systematically correlate early EEG and MRI findings. METHODS: 89 adult patients from a prospective register who underwent at least one EEG and one MRI in the acute phase after CA were included. The EEGs were characterized using pre-existent standardized categories (highly malignant, malignant, benign). For MRIs, the apparent diffusion coefficient (ADC) was computed in pre-defined regions. We then introduced a novel classification based on the topography of ADC reduction (MR-lesion pattern (MLP) 1: no lesion; MLP 2: purely cortical lesions; MLP 3: involvement of the basal ganglia; MLP 4 involvement of other deep grey matter regions). RESULTS: EEG background reactivity and EEG background continuity were strongly associated with a lower MLP value (p < 0.001 and p = 0.003 respectively). The EEG categories highly malignant, malignant and benign were strongly correlated with the MLP values (rho = 0.46, p < 0.001). CONCLUSION: The MRI lesions are highly correlated with the EEG pattern. Our results suggest that performing MRI in comatosepatients after CA with either highly malignant or with a benign EEG pattern is unlikely to yield additional useful information for prognostication, and should therefore be performed in priority in patients with intermediate EEG patterns ("malignant pattern").
Authors: Samuel B Snider; David Fischer; Morgan E McKeown; Alexander Li Cohen; Frederic L W V J Schaper; Edilberto Amorim; Michael D Fox; Benjamin Scirica; Matthew B Bevers; Jong Woo Lee Journal: Neurology Date: 2022-01-11 Impact factor: 9.910
Authors: Michael Müller; Andrea O Rossetti; Rebekka Zimmermann; Vincent Alvarez; Stephan Rüegg; Matthias Haenggi; Werner J Z'Graggen; Kaspar Schindler; Frédéric Zubler Journal: Crit Care Date: 2020-12-07 Impact factor: 9.097