To analyze clinical data including MRI, biomarker, and EEG patterns in patients diagnosed with Creutzfeldt-Jakob Disease (CJD).

Importance:A leading cause of surgically remediable, drug-resistant focal epilepsy is focal cortical dysplasia (FCD). FCD is challenging to visualize and often considered magnetic resonance imaging (MRI) negative. Existing automated methods for FCD detection are limited by high numbers of false-positive predictions, hampering their clinical utility. Objective:To evaluate the efficacy and interpretability of graph neural networks in automatically detecting FCD lesions on MRI scans. Design, Setting, and Participants:In this multicenter diagnostic study, retrospective MRI data were collated from 23 epilepsy centers worldwide between 2018 and 2022, as part of the Multicenter Epilepsy Lesion Detection (MELD) Project, and analyzed in 2023. Data from 20 centers were split equally into training and testing cohorts, with data from 3 centers withheld for site-independent testing. A graph neural network (MELD Graph) was trained to identify FCD on surface-based features. Network performance was compared with an existing algorithm. Feature analysis, saliencies, and confidence scores were used to interpret network predictions. In total, 34 surface-based MRI features and manual lesion masks were collated from participants, 703 patients with FCD-related epilepsy and 482 controls, and 57 participants were excluded during MRI quality control. Main Outcomes and Measures:Sensitivity, specificity, and positive predictive value (PPV) of automatically identified lesions. Results:In the test dataset, the MELD Graph had a sensitivity of 81.6% in histopathologically confirmed patients seizure-free 1 year after surgery and 63.7% in MRI-negative patients with FCD. The PPV of putative lesions from the 260 patients in the test dataset (125 female [48%] and 135 male [52%]; mean age, 18.0 [IQR, 11.0-29.0] years) was 67% (70% sensitivity; 60% specificity), compared with 39% (67% sensitivity; 54% specificity) using an existing baseline algorithm. In the independent test cohort (116 patients; 62 female [53%] and 54 male [47%]; mean age, 22.5 [IQR, 13.5-27.5] years), the PPV was 76% (72% sensitivity; 56% specificity), compared with 46% (77% sensitivity; 47% specificity) using the baseline algorithm. Interpretable reports characterize lesion location, size, confidence, and salient features. Conclusions and Relevance:In this study, the MELD Graph represented a state-of-the-art, openly available, and interpretable tool for FCD detection on MRI scans with significant improvements in PPV. Its clinical implementation holds promise for early diagnosis and improved management of focal epilepsy, potentially leading to better patient outcomes.

Intracortical microstimulation (ICMS) is a method for restoring sensation to people with paralysis as part of a bidirectional brain-computer interface to restore upper limb function. Evoking tactile sensations of the hand through ICMS requires precise targeting of implanted electrodes. Here we describe the presurgical imaging procedures used to generate functional maps of the hand area of the somatosensory cortex and subsequent planning that guided the implantation of intracortical microelectrode arrays. In five participants with cervical spinal cord injury, across two study locations, this procedure successfully enabled ICMS-evoked sensations localized to at least the first four digits of the hand. The imaging and planning procedures developed through this clinical trial provide a roadmap for other brain-computer interface studies to ensure successful placement of stimulation electrodes.

Intracortical microstimulation (ICMS) is a method for restoring sensation to people with paralysis as part of a bidirectional brain-computer interface (BCI) to restore upper limb function. Evoking tactile sensations of the hand through ICMS requires precise targeting of implanted electrodes. Here we describe the presurgical imaging procedures used to generate functional maps of the hand area of the somatosensory cortex and subsequent planning that guided the implantation of intracortical microelectrode arrays. In five participants with cervical spinal cord injury, across two study locations, this procedure successfully enabled ICMS-evoked sensations localized to at least the first four digits of the hand. The imaging and planning procedures developed through this clinical trial provide a roadmap for other BCI studies to ensure the successful placement of stimulation electrodes.

One outstanding challenge for machine learning in diagnostic biomedical imaging is algorithm interpretability. A key application is the identification of subtle epileptogenic focal cortical dysplasias (FCDs) from structural MRI. FCDs are difficult to visualize on structural MRI but are often amenable to surgical resection. We aimed to develop an open-source, interpretable, surface-based machine-learning algorithm to automatically identify FCDs on heterogeneous structural MRI data from epilepsy surgery centres worldwide. The Multi-centre Epilepsy Lesion Detection (MELD) Project collated and harmonized a retrospective MRI cohort of 1015 participants, 618 patients with focal FCD-related epilepsy and 397 controls, from 22 epilepsy centres worldwide. We created a neural network for FCD detection based on 33 surface-based features. The network was trained and cross-validated on 50% of the total cohort and tested on the remaining 50% as well as on 2 independent test sites. Multidimensional feature analysis and integrated gradient saliencies were used to interrogate network performance. Our pipeline outputs individual patient reports, which identify the location of predicted lesions, alongside their imaging features and relative saliency to the classifier. On a restricted 'gold-standard' subcohort of seizure-free patients with FCD type IIB who had T1 and fluid-attenuated inversion recovery MRI data, the MELD FCD surface-based algorithm had a sensitivity of 85%. Across the entire withheld test cohort the sensitivity was 59% and specificity was 54%. After including a border zone around lesions, to account for uncertainty around the borders of manually delineated lesion masks, the sensitivity was 67%. This multicentre, multinational study with open access protocols and code has developed a robust and interpretable machine-learning algorithm for automated detection of focal cortical dysplasias, giving physicians greater confidence in the identification of subtle MRI lesions in individuals with epilepsy.

OBJECTIVE:Drug-resistant focal epilepsy is often caused by focal cortical dysplasias (FCDs). The distribution of these lesions across the cerebral cortex and the impact of lesion location on clinical presentation and surgical outcome are largely unknown. We created a neuroimaging cohort of patients with individually mapped FCDs to determine factors associated with lesion location and predictors of postsurgical outcome. METHODS:The MELD (Multi-centre Epilepsy Lesion Detection) project collated a retrospective cohort of 580 patients with epilepsy attributed to FCD from 20 epilepsy centers worldwide. Magnetic resonance imaging-based maps of individual FCDs with accompanying demographic, clinical, and surgical information were collected. We mapped the distribution of FCDs, examined for associations between clinical factors and lesion location, and developed a predictive model of postsurgical seizure freedom. RESULTS:FCDs were nonuniformly distributed, concentrating in the superior frontal sulcus, frontal pole, and temporal pole. Epilepsy onset was typically before the age of 10 years. Earlier epilepsy onset was associated with lesions in primary sensory areas, whereas later epilepsy onset was associated with lesions in association cortices. Lesions in temporal and occipital lobes tended to be larger than frontal lobe lesions. Seizure freedom rates varied with FCD location, from around 30% in visual, motor, and premotor areas to 75% in superior temporal and frontal gyri. The predictive model of postsurgical seizure freedom had a positive predictive value of 70% and negative predictive value of 61%. SIGNIFICANCE:FCD location is an important determinant of its size, the age at epilepsy onset, and the likelihood of seizure freedom postsurgery. Our atlas of lesion locations can be used to guide the radiological search for subtle lesions in individual patients. Our atlas of regional seizure freedom rates and associated predictive model can be used to estimate individual likelihoods of postsurgical seizure freedom. Data-driven atlases and predictive models are essential for evidence-based, precision medicine and risk counseling in epilepsy.

Devices interfacing with the brain through implantation in cortical or subcortical structures have great potential for restoration and rehabilitation in patients with sensory or motor dysfunction. Typical implantation surgeries are planned based on maps of brain activity generated from intact function. However, mapping brain activity for planning implantation surgeries is challenging in the target population due to abnormal residual function and, increasingly often, existing MRI-incompatible implanted hardware. Here, we present methods and results for mapping impaired somatosensory and motor function in an individual with paralysis and an existing brain–computer interface (BCI) device. Magnetoencephalography (MEG) was used to directly map the neural activity evoked during transcutaneous electrical stimulation and attempted movement of the impaired hand. Evoked fields were found to align with the expected anatomy and somatotopic organization. This approach may be valuable for guiding implants in other applications, such as cortical stimulation for pain and to improve implant targeting to help reduce the craniotomy size.

BACKGROUND:Autism spectrum disorder (ASD) is associated with anxiety and sleep problems. We investigated transdermal electrical neuromodulation (TEN) of the cervical nerves in the neck as a safe, effective, comfortable and non-pharmacological therapy for decreasing anxiety and enhancing sleep quality in ASD. METHODS:In this blinded, sham-controlled study, seven adolescents and young adults with high-functioning ASD underwent five consecutive treatment days, one day of the sham followed by four days of subthreshold TEN for 20 min. Anxiety-provoking cognitive tasks were performed after the sham/TEN. Measures of autonomic nervous system activity, including saliva α-amylase and cortisol, electrodermal activity, and heart rate variability, were collected from six participants. RESULTS:Self-rated and caretaker-rated measures of anxiety were significantly improved with TEN treatment as compared to the sham, with effect sizes ranging from medium to large depending on the rating scale. Sleep scores from caretaker questionnaires also improved, but not significantly. Performance on two of the three anxiety-provoking cognitive tasks and heart rate variability significantly improved with TEN stimulation as compared to the sham. Four of the seven (57%) participants were responders, defined as a ≥ 30% improvement in self-reported anxiety. Salivary α-amylase decreased with more TEN sessions and decreased from the beginning to the end of the session on TEN days for responders. TEN was well-tolerated without significant adverse events. CONCLUSIONS:This study provides preliminary evidence that TEN is well-tolerated in individuals with ASD and can improve anxiety.

BACKGROUND:Acute necrotizing encephalopathy (ANE) is a rare condition associated with rapid progression to coma and high incidence of morbidity and mortality.METHODS:Clinical, electroencephalographic (EEG), and brain magnetic resonance imaging (MRI) characteristics and immunomodulatory therapy timing were retrospectively analyzed in children with ANE. ANE severity scores (ANE-SS) and MRI scores were also assessed. The associations of patient characteristics with 6-month modified Rankin scale (mRS) and length of hospitalization were determined using either univariate linear regression or one-way analysis of variance.RESULTS:7 children were retrospectively evaluated. Normal EEG sleep spindles (P = .024) and early treatment (R2 = .57, P = .030) were associated with improved outcomes (ie, decreased mRS). Higher ANE-SS (R2 = .79, P = .011), higher age (R2 = .62, P = .038), and presence of brainstem lesions (P = .015) were associated with longer length of hospitalization. Other patient characteristics were not significantly associated with mRS or length of hospitalization.CONCLUSION:Early immunomodulatory therapy and normal sleep spindles are associated with better functional outcome in children with ANE.

IntroductionMalignant cerebral edema (MCE) may complicate acute ischemic stroke caused by large-vessel occlusion (AIS-LVO) and result in elevated intracranial pressure.In patients with AIS-LVO, infarcts ≥80mL are associated with MCE, whereas smaller infarct cores with successful endovascular revascularization are unlikely to develop MCE.In patients with unsuccessful or suboptimal revascularization following endovascular thrombectomy (ET), features to risk stratify for development of MCE are not well described.We hypothesize that perfusion imaging-derived hypoperfusion intensity ratio (HIR) may predict MCE in patients with volumes of at-risk tissue ≥80mL. MethodsWe retrospectively reviewed all anterior circulation AIS-LVO patients from our prospectively maintained institutional stroke registry who underwent unsuccessful ET (defined as an mTICI score of 0-2a) over an eight-year period.Inclusion criteria were: initial core infarct estimate of ≤80mL using a CBF<30% or ADC<620 threshold, Tmax >6s volume ≥80mL, mismatch ratio ≥1.8, and subsequent mTICI 0-2a revascularization.MCE was defined as the development of ≥5mm of midline shift on follow-up imaging within 6-48 hours.Analyses were performed using HIR and clinical and radiologic criteria to determine predictors of MCE and functional neurologic outcome. ResultsThirty-six patients met inclusion criteria.Univariate analysis demonstrated that younger age, core volume, Tmax >6s volume, and HIR were associated with MCE (all p<0.002).In multivariate linear regression analysis MCE was only associated with HIR and core infarct volume; HIR was the strongest factor.Best-fit linear regression revealed the optimal HIR of 0.54 to predict MCE (r2 = 0.47, AUC 0.79), which corresponds to an odds ratio of 14.7 (95% CI: 2.4-78.0,p=0.003).When controlling for variability in time from ET to stability scan, HIR remained an independent predictor of MCE.Suboptimal threemonth modified Rankin score (3-6) was only significantly associated with higher HIR (OR 10.8, 95% CI: 1.9-44.0,p=0.02). ConclusionsLarger core infarct volume and higher HIR are predictive of MCE in patients with AIS-LVO and poor revascularization.High HIR is correlated with poor three-month functional outcomes.Excellent collateral status, reflected by a low HIR, may be associated with decreased risk for MCE, and hence a predictor of favorable outcome despite suboptimal or unsuccessful revascularization.

Interpreting electrocorticography (ECoG) in the context of neuroimaging requires that multimodal information be integrated accurately. However, the implantation of ECoG electrodes can shift the brain impacting the spatial interpretation of electrode locations in the context of pre-implant imaging. We characterized the amount of shift in ECoG electrode locations immediately after implant in a pediatric population. Electrode-shift was quantified as the difference in the electrode locations immediately after surgery (via post-operation CT) compared to the brain surface before the operation (pre-implant T1 MRI). A total of 1140 ECoG contracts were assessed across 18 patients ranging from 3 to 19 (12.1 ± 4.8) years of age who underwent intracranial monitoring in preparation for epilepsy resection surgery. Patients had an average of 63 channels assessed with an average of 5.64 ± 3.27 mm shift from the pre-implant brain surface within 24 h of implant. This shift significantly increased with estimated intracranial volume, but not age. Shift also varied significantly depending of the lobe the contact was over; where contacts on the temporal and frontal lobe had less shift than the parietal. Furthermore, contacts on strips had significantly less shift than those on grids. The shift in the brain surface due to ECoG implantation could lead to a misinterpretation of contact location particularly in patients with larger intracranial volume and for grid contacts over the parietal lobes.

Objective. Neurofeedback (NF) trains people to volitionally modulate their cortical activity to affect a behavioral outcome. We evaluated the feasibility of using NF to improve hand function after chronic cervical-level spinal cord injury (SCI) using biologically-relevant visual feedback of motor-related brain activity and an intuitive control scheme. Approach. The NF system acquired magnetoencephalography (MEG) data in real-time to provide feedback of event-related desynchronization (ERD) measured over the sensorimotor cortex during attempted hand grasping. During brain control, stronger ERD resulting from attempted grasping drove the virtual hand towards a more closed grasp, while less ERD drove the hand more open. Main results. Eight individuals with partial or complete hand impairment due to chronic SCI controlled the NF to perform a grasping task that increased in difficulty as the participants achieved success. During their first NF session, participants achieved an average success rate of 63.7 ± 6.4% (chance level of 13.9%). After as few as one intervention session, four of the seven individuals evaluated for ERD changes had significantly strengthened ERD and three of the four participants with measurable grip strength prior to NF had increased grip strength. Interestingly, both individuals who participated in a longer-term study (i.e. >8 NF sessions) had improved grip strength and significantly strengthened ERD. Significance. This study demonstrates that MEG-based NF training can change brain activity in individuals with hand impairment due to SCI and has the potential to induce acute changes in grip strength. Future studies will evaluate whether neuroplasticity induced with long term NF can improve hand function for those with moderate impairment.

Objective: Regional differences were investigated in quantitative EEG (QEEG) characteristics and associations of QEEG to hemodynamics after pediatric acute stroke. Methods: Quantitative EEG was analyzed, including power in delta, theta, alpha, and beta bands, alpha-delta power ratio, total power, and spectral edge frequency from 11 children with unilateral, anterior circulation strokes during the first 24 hours of continuous EEG recording. Differences between injured and uninjured hemispheres were assessed using multivariate dynamic structural equations modeling. Dynamic structural equations modeling was applied to six children with hemorrhagic stroke undergoing arterial blood pressure, heart rate, and cerebral oximetry monitoring to investigate associations between hemodynamics with QEEG adjacent to anterior circulation regions. Results: All patients with acute ischemic stroke (n = 5) had lower alpha and beta power and spectral edge frequency on injured compared with uninjured regions. This was not consistent after hemorrhagic stroke (n = 6). All hemorrhagic stroke patients demonstrated negative association of total power with arterial blood pressure within injured regions. No consistency was observed for direction or strength of association in other QEEG measures to arterial blood pressure nor were such consistent relationships observed for any QEEG measure studied in relation to heart rate or cerebral oximetry. Conclusions: After pediatric anterior circulation acute ischemic stroke, reduced spectral edge frequency and alpha and beta power can be observed on injured as compared with noninjured regions. After pediatric anterior circulation hemorrhagic stroke, total power can be negatively associated with arterial blood pressure within injured regions. Larger studies are needed to understand conditions in which QEEG patterns manifest and relate to hemodynamics and brain penumbra.

OBJECTIVE The authors' goal was to prospectively quantify the impact of resting-state functional MRI (rs-fMRI) on pediatric epilepsy surgery planning. METHODS Fifty-one consecutive patients (3 months to 20 years old) with intractable epilepsy underwent rs-fMRI for presurgical evaluation. The team reviewed the following available diagnostic data: video-electroencephalography (n = 51), structural MRI (n = 51), FDG-PET (n = 42), magnetoencephalography (n = 5), and neuropsychological testing (n = 51) results to formulate an initial surgery plan blinded to the rs-fMRI findings. Subsequent to this discussion, the connectivity results were revealed and final recommendations were established. Changes between pre- and post-rs-fMRI treatment plans were determined, and changes in surgery recommendation were compared using McNemar's test. RESULTS Resting-state fMRI was successfully performed in 50 (98%) of 51 cases and changed the seizure onset zone localization in 44 (88%) of 50 patients. The connectivity results prompted 6 additional studies, eliminated the ordering of 11 further diagnostic studies, and changed the intracranial monitoring plan in 10 cases. The connectivity results significantly altered surgery planning with the addition of 13 surgeries, but it did not eliminate planned surgeries (p = 0.003). Among the 38 epilepsy surgeries performed, the final surgical approach changed due to rs-fMRI findings in 22 cases (58%), including 8 (28%) of 29 in which extraoperative direct electrical stimulation mapping was averted. CONCLUSIONS This study demonstrates the impact of rs-fMRI connectivity results on the decision-making for pediatric epilepsy surgery by providing new information about the location of eloquent cortex and the seizure onset zone. Additionally, connectivity results may increase the proportion of patients considered eligible for surgery while optimizing the need for further testing.

OBJECTIVES:Electroencephalography is used in neurocritical care for detection of seizures and assessment of cortical function. Due to limited resolution from scalp electroencephalography, important abnormalities may not be readily detectable. We aimed to identify whether intracranial electroencephalography allows for improved methods of monitoring cortical function in children with severe traumatic brain injury.DESIGN:This is a retrospective cohort study from a prospectively collected clinical database. We investigated the occurrence rate of epileptiform abnormalities detected on intracranial electroencephalography when compared with scalp electroencephalography. We also investigated the strength of association of quantitative electroencephalographic parameters and cerebral perfusion pressure between both intracranial and scalp electroencephalography.SETTING:This is a single-institution study performed in the Phoenix Children's Hospital PICU.PATIENTS:Eleven children with severe traumatic brain injury requiring invasive neuromonitoring underwent implantation of a six-contact intracranial electrode as well as continuous surface electroencephalography.INTERVENTIONS:None.MEASUREMENTS AND MAIN RESULTS:Visual detection of epileptiform abnormalities was performed by pediatric epileptologists. Association of intracranial and scalp electroencephalography total power, alpha percentage, and alpha-delta power ratio to cerebral perfusion pressure was performed using univariate dynamic structural equations modeling. Demographic data were assessed by retrospective analysis. Intracranial and scalp electroencephalography was performed in 11 children. Three of 11 children had observed epileptiform abnormalities on intracranial electroencephalography. Two patients had epileptiform abnormalities identified exclusively on intracranial electroencephalography, and one patient had seizures initiating on intracranial electroencephalography before arising on scalp electroencephalography. Identification of epileptiform abnormalities was associated with subsequent identification of stroke or malignant cerebral edema. We observed statistically significant positive associations between intracranial alpha-delta power ratio to cerebral perfusion pressure in nine of 11 patients with increased strength of association on intracranial compared with scalp recordings.CONCLUSIONS:These findings suggest that intracranial electroencephalography may be useful for detection of secondary insult development in children with traumatic brain injury.

Traumatic brain injury (TBI) is a leading cause of morbidity and mortality in children. Improved methods of monitoring real-time cerebral physiology are needed to better understand when secondary brain injury develops and what treatment strategies may alleviate or prevent such injury. In this review, we discuss emerging technologies that exist to better understand intracranial pressure (ICP), cerebral blood flow, metabolism, oxygenation and electrical activity. We also discuss approaches to integrating these data as part of a multimodality monitoring strategy to improve patient care.

Traumatic brain injury (TBI) is a leading cause of morbidity and mortality in children both in the United States and throughout the world. Despite valiant efforts and multiple clinical trials completed over the last few decades, there are no high-level recommendations for pediatric TBI available in current guidelines. In this review, the authors explore key findings from the major pediatric clinical trials in children with TBI that have shaped present-day recommendations and the insights gained from them. The authors also offer a perspective on potential efforts to improve the efficacy of future clinical trials in children following TBI.

In this paper, we introduce electroencephalography (EEG)- PDC based network connectivity average mean degrees (E-PDC) measure to analyze the interhemispheric interaction between the left and right motor cortices after stroke. E-PDC uses a graph and partial directed coherence (PDC) approach to quantify the directional functional connectivity between the motor cortices, which is not only altered after stroke but also is one of the important mechanisms linked with poor recovery of hand function. The brain activity between the two motor cortices is calculated via PDC and is used to form a graph. The PDC based network connectivity average mean degree of connectivity defined over this graph is defined as the E-PDC, which quantifies the directional connectivity between the two motor cortices. We preliminarily validated the novel E-PDC measure with three individuals with stroke, where one individual received a non-invasive brain stimulation (NIBS) intervention and the other two received sham-NIBS intervention. Unlike the two individuals who received sham-NIBS, the individual who received the NIBS intervention showed improvement in E-PDC after intervention, which strongly correlated with improvement in hand function after intervention (Fugl Meyer Upper Extremity Subscale and grip strength). This implies that the introduced E-PDC measure quantifies the interactions between the motor cortices and could be used to elucidate the underlying mechanism in restoring hand function after stroke.