Lauranne Scheldeman

Intracranial electroencephalography (iEEG) has been increasingly explored as part of multimodal neuromonitoring in acute brain injury, yet its diagnostic benefit compared with continuous surface EEG (suEEG) remains uncertain. We have performed a meta-analysis to quantify seizure and rhythmic and periodic pattern detection rates and concordance with suEEG. Secondary objectives were the assessment of correlations with brain injury, safety, and techniques. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, PubMed, Scopus, and Embase were searched for studies reporting iEEG monitoring in adults with acute brain injury. Epileptic patterns were harmonized to the American Clinical Neurophysiology Society Standardized EEG Nomenclature for Critically Ill Patients (ACNS) 2021 terminology, classifying events as seizures/status epilepticus (SZ/SE) or rhythmic and periodic/ictal–interictal continuum patterns (RPP/IIC). Risk of bias was assessed using the Newcastle–Ottawa scale and custom bias domains. Random-effects meta-analyses were conducted for (i) pooled proportions and (ii) pooled paired within-patient comparisons. Twelve cohorts (n = 864 participants) with aneurysmal subarachnoid hemorrhage (n = 343), traumatic brain injury (n = 351), and mixed etiologies (n = 170) were included. Six studies provided paired iEEG–suEEG data (n = 273). Techniques were based on a strip or depth electrode. No severe adverse events were reported. Pooled iEEG versus suEEG incidence rates were respectively: 26% vs. 15% for SZ/SE, 47% vs. 34% for RPP/IIC, and 57% vs. 37% for clinically relevant epileptic activity. Pooled paired analysis demonstrated that iEEG additionally detected SZ/SE in 16.5% of patients [pooled McNemar odds ratio (OR) 3.46 (0.51–23.6); I² = 63%; p = 0.158] and RPP/IIC in 26% [pooled OR 4.25 (0.19–96.1); I² = 73%; p = 0.236], while suEEG was negative. Sensitivity analyses for high-risk studies or cohort overlap did not alter the results. Invasive EEG monitoring substantially increased the detection of seizures and RPP/IIC patterns compared with suEEG alone in patients with acute brain injury, serving as a promising monitoring adjunct.

Precise lesion localisation is central to favourable surgical outcomes in patients with drug-resistant epilepsy due to focal cortical dysplasia. We validated the Anatomy-Corrected Asymmetry Index of fluorodeoxyglucose positron emission tomography to objectively delineate regions of hypometabolism and predict surgical outcome in patients with focal cortical dysplasia. We first established normative Anatomy-Corrected Asymmetry Index thresholds using five independent and heterogeneous healthy control cohorts (n = 179) to assess reproducibility. We subsequently validated our findings in 40 pathologically confirmed focal cortical dysplasia patients who underwent resective surgery. The primary analysis assessed the association between the extent of resection of defined hypometabolic clusters and 24-month seizure freedom (Engel Class I). After excluding subjects with segmentation artefacts to ensure accurate threshold definition, we established a normative threshold of -19 with a minimum cluster size of 2.0 mL. In the patient cohort, 29 subjects had high-quality segmentations. Patients with at least one localising cluster achieved significantly higher seizure freedom rates compared to those without clusters (76.5% vs. 22.2%, P = 0.014). The percentage of resected hypometabolic volume was significantly associated with Engel Class I outcome (P = 0.011). Sensitivity analysis demonstrated that a more permissive threshold of -16 identified localising clusters in two additional seizure-free patients who were false negatives at the standard threshold. The Anatomy-Corrected Asymmetry Index provides a standardised metric that predicts seizure freedom in focal cortical dysplasia epilepsy surgery. Clinical implementation requires rigorous quality control of anatomical segmentations to ensure diagnostic accuracy. The online version contains supplementary material available at 10.1007/s00259-026-07864-9.

Objective: Nonconvulsive epileptic activity is common after acute brain injury and contributes to neuronal injury and poor outcomes. Although intracranial electroencephalography (iEEG) improves detection compared with surface EEG (suEEG), it currently relies on focal recordings of epileptic dynamics. We prospectively evaluated multielectrode iEEG strategies designed to achieve large‐scale cortical and deep brain coverage in critically ill patients. Methods: In a prospective cohort of adults with acute brain injury requiring invasive neuromonitoring, we implemented four depth electrode‐based iEEG techniques: three electrocorticographic approaches (open subdural, burr hole subdural, and foramen ovale) and one stereotactic (transcortical) approach. The primary objective was to establish and quantify the extent and durability of cortical recordings. Additional assessments included safety, feasibility, and management impact. Electrode localization was performed in MNI305 space, and recording longevity was assessed using Kaplan–Meier and Cox proportional hazards models. Results: Thirty patients with severe brain injury underwent implantation of 64 electrodes (772 contacts), yielding 361 total iEEG recording days across heterogeneous etiologies and surgical settings. Multielectrode implantation enabled distributed sampling spanning multilobar frontoparietotemporal cortical clusters. Overall, 72% of electrodes sampled cortical convexity alone, whereas 28% incorporated deep targets, including mesial temporal and orbitofrontal regions. Recording durability differed by implantation strategy (log‐rank p = .0002), with a mean combined iEEG–suEEG monitoring duration of 14.5 days per patient. Implantation was successful in >95% of electrodes, monitoring started within 24 h postoperatively in 88%, and the per‐electrode risk of a causally related adverse event was 3.1%, without hemorrhagic complications. iEEG influenced treatment initiation or escalation in 32% of monitored patients. Significance: Multielectrode iEEG strategies enable durable, large‐scale cortical sampling in acute brain injury while remaining feasible and safe in the intensive care unit. By shifting from focal to distributed spatial sampling, these approaches provide a conceptual framework for improving detection of epileptic activity in critically ill patients.

Introduction: In Acute Ischemic Stroke (AIS), mismatch between Diffusion-Weighted Imaging (DWI) and Fluid-Attenuated Inversion-Recovery (FLAIR) helps identify patients who can benefit from thrombolysis when stroke onset time is unknown (15% of AIS). However, visual assessment has suboptimal observer agreement. Our study aims to develop and validate a Deep-Learning model for predicting DWI-FLAIR mismatch using solely DWI data. Patients and methods: This retrospective study included AIS patients from ETIS registry (derivation cohort, 2018–2024) and WAKE-UP trial (validation cohort, 2012–2017). DWI-FLAIR mismatch was rated visually. We trained a model to predict manually-labeled FLAIR visible areas (FVA) matching the DWI lesion on baseline and early follow-up MRIs, using only DWI as input. FVA-index was defined as the volume of predicted regions. Area under the ROC curve (AUC) and optimal FVA-index cutoff to predict DWI-FLAIR mismatch in the derivation cohort were computed. Validation was performed using baseline MRIs of the validation cohort. Results: The derivation cohort included 3605 MRIs in 2922 patients and the validation cohort 844 MRIs in 844 patients. FVA-index demonstrated strong predictive value for DWI-FLAIR mismatch in baseline MRIs from the derivation (n = 2453, AUC = 0.85, 95%CI: 0.84–0.87) and validation cohort (n = 844, AUC = 0.86, 95%CI: 0.84–0.89). With an optimal FVA-index cutoff at 0.5, we obtained a kappa of 0.54 (95%CI: 0.48–0.59), 70% sensitivity (378/537, 95%CI: 66–74%) and 88% specificity (269/307, 95%CI: 83–91%) in the validation cohort. Discussion and conclusion: The model accurately predicts DWI-FLAIR mismatch in AIS patients with unknown stroke onset. It could aid readers when visual rating is challenging, or FLAIR unavailable.

Introduction: In Acute Ischemic Stroke (AIS), mismatch between Diffusion-Weighted Imaging (DWI) and Fluid-Attenuated Inversion-Recovery (FLAIR) helps identify patients who can benefit from thrombolysis when stroke onset time is unknown (15% of AIS). However, visual assessment has suboptimal observer agreement. Our study aims to develop and validate a Deep-Learning model for predicting DWI-FLAIR mismatch using solely DWI data. Patients and methods: This retrospective study included AIS patients from ETIS registry (derivation cohort, 2018–2024) and WAKE-UP trial (validation cohort, 2012–2017). DWI-FLAIR mismatch was rated visually. We trained a model to predict manually-labeled FLAIR visible areas (FVA) matching the DWI lesion on baseline and early follow-up MRIs, using only DWI as input. FVA-index was defined as the volume of predicted regions. Area under the ROC curve (AUC) and optimal FVA-index cutoff to predict DWI-FLAIR mismatch in the derivation cohort were computed. Validation was performed using baseline MRIs of the validation cohort. Results: The derivation cohort included 3605 MRIs in 2922 patients and the validation cohort 844 MRIs in 844 patients. FVA-index demonstrated strong predictive value for DWI-FLAIR mismatch in baseline MRIs from the derivation ( n = 2453, AUC = 0.85, 95%CI: 0.84–0.87) and validation cohort ( n = 844, AUC = 0.86, 95%CI: 0.84–0.89). With an optimal FVA-index cutoff at 0.5, we obtained a kappa of 0.54 (95%CI: 0.48–0.59), 70% sensitivity (378/537, 95%CI: 66–74%) and 88% specificity (269/307, 95%CI: 83–91%) in the validation cohort. Discussion and conclusion: The model accurately predicts DWI-FLAIR mismatch in AIS patients with unknown stroke onset. It could aid readers when visual rating is challenging, or FLAIR unavailable.

BACKGROUND: Blood-brain barrier (BBB) leakage measured with dynamic susceptibility contrast-enhanced magnetic resonance imaging (MRI) has been associated with hemorrhagic transformation in acute ischemic stroke. However, the influence of prethrombolysis BBB leakage on infarct growth has not been studied. Therefore, we aimed to characterize BBB integrity according to tissue state at admission and tissue fate on follow-up MRI. METHODS: This is a post hoc analysis of the WAKE-UP trial (Efficacy and Safety of MRI-Based Thrombolysis in Wake-Up Stroke). Ischemic cores were segmented on diffusion-weighted imaging at baseline and on fluid-attenuated inversion recovery images at follow-up (22–36 hours). Dynamic susceptibility contrast-enhanced–MRI provided penumbra masks (time to maximum of the tissue residue function >6 s minus ischemic core) and BBB leakage (extraction fraction [EF], Z scored) maps via automated analysis. EF was averaged within the ischemic core, total penumbra, 2 penumbra subtypes (salvaged/infarcted penumbra), and normal tissue. Adjusted linear mixed-effects models tested for differences between tissue types and associations of EF with clinical/imaging outcomes. Complementary voxel-wise analyses were performed. RESULTS: Of 503 patients enrolled in the trial, 165 with suitable dynamic susceptibility contrast-enhanced–MRI data were included in this analysis (mean age 66 years, 38% women, median National Institutes of Health Stroke Scale score of 6; 53% receiving alteplase). EF was significantly increased in the ischemic core and penumbra relative to normally perfused tissue, while differences between total penumbra and ischemic core were statistically nonsignificant. Infarcted penumbra exhibited higher EF than salvaged penumbra, even after adjusting for hypoperfusion severity ( P <0.001, n=79 with baseline penumbral tissue and follow-up MRI). Voxel-wise analyses showed a significant association between EF and voxel-level infarction in the placebo group only. EF did not predict hemorrhagic transformation or functional outcomes. CONCLUSIONS: Penumbral BBB leakage may identify tissue at increased risk of infarction. Larger, prospective studies are needed to determine the clinical relevance of BBB leakage as an imaging marker of tissue fate. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT01525290. URL: https://eudract.ema.europa.eu/ ; Unique identifier: 2011-005906-32.

Introduction: Blood-brain barrier disruption in acute ischemic stroke is a well described phenomenon associated with hemorrhagic complications. The hyperintense acute reperfusion marker (HARM) represents gadolinium leakage in the cerebrospinal fluid. Gadolinium leakage into ocular structures (GLOS) might represent a dysfunction of the blood-ocular barrier. We aimed to investigate the presence of GLOS in the WAKE-UP trial and its association with HARM, hemorrhagic transformation (HT) and functional outcome. Patients and methods: Randomized patients from the WAKE-UP trial who underwent dynamic susceptibility contrast perfusion weighted imaging at baseline and fluid attenuated inversion recovery (FLAIR) imaging at both baseline and follow-up, were included. We studied the association between GLOS with baseline and outcome variables. Results: We were able to analyze the data of 192/503 (38%) randomized WAKE-UP patients. GLOS was detected in 56 (29%) cases, four times more frequently than HARM (7%). GLOS positive patients were older (73 vs 65 years; p < 0.01), had a lower glomerular infiltration rate (GFR 79.5 vs 87.2 mL/min; p = 0.01), higher white matter hyperintensity volume (15.0 vs 9.9 mL; p < 0.01), less often presented with a large vessel occlusion (27% vs 44%; p = 0.02) and HARM was more often observed (9/56 vs 4/136; p = 0.01). In multivariable analysis the presence of GLOS was not associated with HT nor poor functional outcome (modified Rankin scale 3–6). Discussion and conclusion: GLOS is a relatively common finding in acute ischemic stroke patients and is associated with older age, worse renal function, increased white matter hyperintensity burden and HARM but not with HT or functional outcome.

Background: In patients with an acute ischemic stroke, the penumbra is defined as ischemic tissue that remains salvageable when reperfusion occurs. However, the expected clinical recovery congruent with penumbral salvage is not always observed. Aims: We aimed to determine whether the magnetic resonance imaging (MRI)-defined penumbra includes irreversible neuronal loss that impedes expected clinical recovery after reperfusion. Methods: In the prospective French Acute Multimodal Imaging Study to Select Patients for Mechanical Thrombectomy (FRAME) and an observational cohort of patients with large vessel occlusions undergoing endovascular treatment, we quantified penumbral integrity by fluid-attenuated inversion recovery (FLAIR) changes. We studied the influence of recanalization status on the evolution of penumbral FLAIR changes and studied penumbral FLAIR changes as predictor of tissue fate and functional outcome on the 90-day modified Rankin Scale (mRS). Results: Recanalization status did not modify the evolution of rFLAIR signal intensity (SI) over time in the total cohort, but was associated with lower SI in the FRAME subset (b = −0.06, p for interaction = 0.04). Median rFLAIR SI was higher at baseline in the subsequently infarcted penumbra compared to the salvaged (ratio = 1.07, standard deviation (SD) = 0.07 vs 1.03, SD = 0.06 p < 0.0001, n = 150). The severity and extent of rFLAIR SI changes did not predict 90-day functional outcome in univariate (p = 0.09) and multivariate logistic regression (p = 0.4). Conclusions: Recanalization status did not influence the evolution of penumbral FLAIR changes. FLAIR SI changes in the baseline penumbra were associated with tissue fate, but not functional outcome.

Acute ST-elevation myocardial infarction (STEMI) and acute ischaemic stroke (AIS) share a number of similarities. However, important differences in pathophysiology demand a disease-tailored approach. In both conditions, fast treatment plays a crucial role as ischaemia and eventually infarction develop rapidly. Furthermore, in both fields, the introduction of fibrinolytic treatments historically preceded the implementation of endovascular techniques. However, in contrast to STEMI, only a minority of AIS patients will eventually be considered eligible for reperfusion treatment. Non-invasive cerebral imaging always precedes cerebral angiography and thrombectomy, whereas coronary angiography is not routinely preceded by non-invasive cardiac imaging in patients with STEMI. In the late or unknown time window, the presence of specific patterns on brain imaging may help identify AIS patients who benefit most from reperfusion treatment. For STEMI, a uniform time window for reperfusion up to 12 h after symptom onset, based on old placebo-controlled trials, is still recommended in guidelines and generally applied. Bridging fibrinolysis preceding endovascular treatment still remains the mainstay of reperfusion treatment in AIS, while primary percutaneous coronary intervention is the strategy of choice in STEMI. Shortening ischaemic times by fine-tuning collaboration networks between ambulances, community hospitals, and tertiary care hospitals, optimizing bridging fibrinolysis, and reducing ischaemia–reperfusion injury are important topics for further research. The aim of this review is to provide insights into the common as well as diverging pathophysiology behind current reperfusion strategies and to explore new ways to enhance their clinical benefit.

BACKGROUND AND PURPOSE: ASPECTS quantifies early ischemic changes in anterior circulation stroke on NCCT but has interrater variability. We examined the agreement of conventional and automated ASPECTS and studied the value of computer-aided detection. MATERIALS AND METHODS: We retrospectively collected imaging data from consecutive patients with acute ischemic stroke with large-vessel occlusion undergoing thrombectomy. Five raters scored conventional ASPECTS on baseline NCCTs, which were also processed by RAPID software. Conventional and automated ASPECTS were compared with a consensus criterion standard. We determined the agreement over the full ASPECTS range as well as dichotomized, reflecting thrombectomy eligibility according to the guidelines (ASPECTS 0–5 versus 6–10). Raters subsequently scored ASPECTS on the same NCCTs with assistance of the automated ASPECTS outputs, and agreement was obtained. RESULTS: For the total of 175 cases, agreement among raters individually and the criterion standard varied from fair to good (weighted κ = between 0.38 and 0.76) and was moderate (weighted κ = 0.59) for the automated ASPECTS. The agreement of all raters individually versus the criterion standard improved with software assistance, as did the interrater agreement (overall Fleiss κ = 0.15–0.23; P < .001 and .39 to .55; P = .01 for the dichotomized ASPECTS). CONCLUSIONS: Automated ASPECTS had agreement with the criterion standard similar to that of conventional ASPECTS. However, including automated ASPECTS during the evaluation of NCCT in acute stroke improved the agreement with the criterion standard and improved interrater agreement, which could, therefore, result in more uniform scoring in clinical practice.