Common Data Elements for Disorders of Consciousness: Recommendations from the Working Group in the Pediatric Population.

BACKGROUND: The fundamental gap obstructing forward progress of evidenced-based care in pediatric and neonatal disorders of consciousness (DoC) is the lack of defining consensus-based terminology to perform comparative research. This lack of shared nomenclature in pediatric DoC stems from the inherently recursive dilemma of the inability to reliably measure consciousness in the very young. However, recent advancements in validated clinical examinations and technologically sophisticated biomarkers of brain activity linked to future abilities are unlocking this previously formidable challenge to understanding the DoC in the developing brain. METHODS: To address this need, the first of its kind international convergence of an interdisciplinary team of pediatric DoC experts was organized by the Neurocritical Care Society's Curing Coma Campaign. The multidisciplinary panel of pediatric DoC experts proposed pediatric-tailored common data elements (CDEs) covering each of the CDE working groups including behavioral phenotyping, biospecimens, electrophysiology, family and goals of care, neuroimaging, outcome and endpoints, physiology and big Data, therapies, and pediatrics. RESULTS: We report the working groups' pediatric-focused DoC CDE recommendations and disseminate CDEs to be used in studies of pediatric patients with DoC. CONCLUSIONS: The CDEs recommended support the vision of progressing collaborative and successful internationally collaborative pediatric coma research.

Functional MRI for Acute Covert Consciousness: Emerging Data and Implementation Case Series.

Although research studies have begun to demonstrate relationships between disorders of consciousness and brain network biomarkers, there are limited data on the practical aspects of obtaining such network biomarkers to potentially guide care. As the state of knowledge continues to evolve, guidelines from professional societies such as the American and European Academies of Neurology and many experts have advocated that the risk-benefit ratio for the assessment of network biomarkers has begun to favor their application toward potentially detecting covert consciousness. Given the lack of detailed operationalization guidance and the context of the ethical implications, herein we offer a roadmap based on local institutional experience with the implementation of functional MRI in the neonatal, pediatric, and adult intensive care units of our local government-supported health system. We provide a case-based demonstrative approach intended to review the current literature and to assist with the initiation of such services at other facilities.

Source-sink connectivity: a novel interictal EEG marker for seizure localization.

Over 15 million epilepsy patients worldwide have drug-resistant epilepsy. Successful surgery is a standard of care treatment but can only be achieved through complete resection or disconnection of the epileptogenic zone, the brain region(s) where seizures originate. Surgical success rates vary between 20% and 80%, because no clinically validated biological markers of the epileptogenic zone exist. Localizing the epileptogenic zone is a costly and time-consuming process, which often requires days to weeks of intracranial EEG (iEEG) monitoring. Clinicians visually inspect iEEG data to identify abnormal activity on individual channels occurring immediately before seizures or spikes that occur interictally (i.e. between seizures). In the end, the clinical standard mainly relies on a small proportion of the iEEG data captured to assist in epileptogenic zone localization (minutes of seizure data versus days of recordings), missing opportunities to leverage these largely ignored interictal data to better diagnose and treat patients. IEEG offers a unique opportunity to observe epileptic cortical network dynamics but waiting for seizures increases patient risks associated with invasive monitoring. In this study, we aimed to leverage interictal iEEG data by developing a new network-based interictal iEEG marker of the epileptogenic zone. We hypothesized that when a patient is not clinically seizing, it is because the epileptogenic zone is inhibited by other regions. We developed an algorithm that identifies two groups of nodes from the interictal iEEG network: those that are continuously inhibiting a set of neighbouring nodes ('sources') and the inhibited nodes themselves ('sinks'). Specifically, patient-specific dynamical network models were estimated from minutes of iEEG and their connectivity properties revealed top sources and sinks in the network, with each node being quantified by source-sink metrics. We validated the algorithm in a retrospective analysis of 65 patients. The source-sink metrics identified epileptogenic regions with 73% accuracy and clinicians agreed with the algorithm in 93% of seizure-free patients. The algorithm was further validated by using the metrics of the annotated epileptogenic zone to predict surgical outcomes. The source-sink metrics predicted outcomes with an accuracy of 79% compared to an accuracy of 43% for clinicians' predictions (surgical success rate of this dataset). In failed outcomes, we identified brain regions with high metrics that were untreated. When compared with high frequency oscillations, the most commonly proposed interictal iEEG feature for epileptogenic zone localization, source-sink metrics outperformed in predictive power (by a factor of 1.2), suggesting they may be an interictal iEEG fingerprint of the epileptogenic zone.

Proceedings of the First Pediatric Coma and Disorders of Consciousness Symposium by the Curing Coma Campaign, Pediatric Neurocritical Care Research Group, and NINDS: Gearing for Success in Coma Advancements for Children and Neonates.

This proceedings article presents the scope of pediatric coma and disorders of consciousness based on presentations and discussions at the First Pediatric Disorders of Consciousness Care and Research symposium held on September 14th, 2021. Herein we review the current state of pediatric coma care and research opportunities as well as shared experiences from seasoned researchers and clinicians. Salient current challenges and opportunities in pediatric and neonatal coma care and research were identified through the contributions of the presenters, who were Jose I. Suarez, MD, Nina F. Schor, MD, PhD, Beth S. Slomine, PhD Erika Molteni, PhD, and Jan-Marino Ramirez, PhD, and moderated by Varina L. Boerwinkle, MD, with overview by Mark Wainwright, MD, and subsequent audience discussion. The program, executively planned by Varina L. Boerwinkle, MD, Mark Wainwright, MD, and Michelle Elena Schober, MD, drove the identification and development of priorities for the pediatric neurocritical care community.

Common Data Elements for Disorders of Consciousness: Recommendations from the Working Group on Neuroimaging.

BACKGROUND: Over the past 5 decades, advances in neuroimaging have yielded insights into the pathophysiologic mechanisms that cause disorders of consciousness (DoC) in patients with severe brain injuries. Structural, functional, metabolic, and perfusion imaging studies have revealed specific neuroanatomic regions, such as the brainstem tegmentum, thalamus, posterior cingulate cortex, medial prefrontal cortex, and occipital cortex, where lesions correlate with the current or future state of consciousness. Advanced imaging modalities, such as diffusion tensor imaging, resting-state functional magnetic resonance imaging (fMRI), and task-based fMRI, have been used to improve the accuracy of diagnosis and long-term prognosis, culminating in the endorsement of fMRI for the clinical evaluation of patients with DoC in the 2018 US (task-based fMRI) and 2020 European (task-based and resting-state fMRI) guidelines. As diverse neuroimaging techniques are increasingly used for patients with DoC in research and clinical settings, the need for a standardized approach to reporting results is clear. The success of future multicenter collaborations and international trials fundamentally depends on the implementation of a shared nomenclature and infrastructure. METHODS: To address this need, the Neurocritical Care Society's Curing Coma Campaign convened an international panel of DoC neuroimaging experts to propose common data elements (CDEs) for data collection and reporting in this field. RESULTS: We report the recommendations of this CDE development panel and disseminate CDEs to be used in neuroimaging studies of patients with DoC. CONCLUSIONS: These CDEs will support progress in the field of DoC neuroimaging and facilitate international collaboration.

Proceedings of the Second Curing Coma Campaign NIH Symposium: Challenging the Future of Research for Coma and Disorders of Consciousness.

This proceedings article presents actionable research targets on the basis of the presentations and discussions at the 2nd Curing Coma National Institutes of Health (NIH) symposium held from May 3 to May 5, 2021. Here, we summarize the background, research priorities, panel discussions, and deliverables discussed during the symposium across six major domains related to disorders of consciousness. The six domains include (1) Biology of Coma, (2) Coma Database, (3) Neuroprognostication, (4) Care of Comatose Patients, (5) Early Clinical Trials, and (6) Long-term Recovery. Following the 1st Curing Coma NIH virtual symposium held on September 9 to September 10, 2020, six workgroups, each consisting of field experts in respective domains, were formed and tasked with identifying gaps and developing key priorities and deliverables to advance the mission of the Curing Coma Campaign. The highly interactive and inspiring presentations and panel discussions during the 3-day virtual NIH symposium identified several action items for the Curing Coma Campaign mission, which we summarize in this article.

Implementation of Multimodality Neurologic Monitoring Reporting in Pediatric Traumatic Brain Injury Management.

BACKGROUND/OBJECTIVE: Multimodality neurologic monitoring (MMM) is an emerging technique for management of traumatic brain injury (TBI). An increasing array of MMM-derived biomarkers now exist that are associated with injury severity and functional outcomes after TBI. A standardized MMM reporting process has not been well described, and a paucity of evidence exists relating MMM reporting in TBI management with functional outcomes or adverse events. METHODS: Prospective implementation of standardized MMM reporting at a single pediatric intensive care unit (PICU) is described that included monitoring of intracranial pressure (ICP), cerebral oxygenation and electroencephalography (EEG). The incidence of clinical decisions made using MMM reporting is described, including timing of neuroimaging, ICP monitoring discontinuation, use of paralytic, hyperosmolar and pentobarbital therapies, neurosurgical interventions, ventilator and CPP adjustments and neurologic prognostication discussions. Retrospective analysis was performed on the association of MMM reporting with initial Glasgow Coma Scale (GCS) and Pediatric Risk of Mortality III (PRISM III) scores, duration of total hospitalization and PICU hospitalization, duration of mechanical ventilation and invasive ICP monitoring, inpatient complications, time with ICP > 20 mmHg, time with cerebral perfusion pressure (CPP) < 40 mmHg and 12-month Glasgow Outcome Scale-Extended Pediatrics (GOSE-Peds) scores. Association of outcomes with MMM reporting was investigated using the Wilcoxon rank-sum test or Fisher's exact test, as appropriate. RESULTS: Eighty-five children with TBI underwent MMM over 6 years, among which 18 underwent daily MMM reporting over a 21-month period. Clinical decision-making influenced by MMM reporting included timing of neuroimaging (100.0%), ICP monitoring discontinuation (100.0%), timing of extubation trials of surviving patients (100.0%), body repositioning (11.1%), paralytic therapy (16.7%), hyperosmolar therapy (22.2%), pentobarbital therapy (33.3%), provocative cerebral autoregulation testing (16.7%), adjustments in CPP thresholds (16.7%), adjustments in PaCO2 thresholds (11.1%), neurosurgical interventions (16.7%) and neurologic prognostication discussions (11.1%). The implementation of MMM reporting was associated with a reduction in ICP monitoring duration (p = 0.0017) and mechanical ventilator duration (p = 0.0018). No significant differences were observed in initial GCS or PRISM III scores, total hospitalization length, PICU hospitalization length, total complications, time with ICP > 20 mmHg, time with CPP < 40 mmHg, use of tier 2 therapy, or 12-month GOS-E Peds scores. CONCLUSION: Implementation of MMM reporting in pediatric TBI management is feasible and can be impactful in tailoring clinical decisions. Prospective work is needed to understand the impact of MMM and MMM reporting systems on functional outcomes and clinical care efficacy.

Multimodal Assessment of Cerebral Autoregulation and Autonomic Function After Pediatric Cerebral Arteriovenous Malformation Rupture.

BACKGROUND: Management after cerebral arteriovenous malformation (AVM) rupture aims toward preventing hemorrhagic expansion while maintaining cerebral perfusion to avoid secondary injury. We investigated associations of model-based indices of cerebral autoregulation (CA) and autonomic function (AF) with outcomes after pediatric cerebral AVM rupture. METHODS: Multimodal neurologic monitoring data from the initial 3 days after cerebral AVM rupture were retrospectively analyzed in children (< 18 years). AF indices included standard deviation of heart rate (HRsd), root-mean-square of successive differences in heart rate (HRrmssd), low-high frequency ratio (LHF), and baroreflex sensitivity (BRS). CA indices include pressure reactivity index (PRx), wavelet pressure reactivity indices (wPRx and wPRx-thr), pulse amplitude index (PAx), and correlation coefficient between intracranial pressure pulse amplitude and cerebral perfusion pressure (RAC). Percent time of cerebral perfusion pressure (CPP) below lower limits of autoregulation (LLA) was also computed for each CA index. Primary outcomes were determined using Pediatric Glasgow Outcome Score Extended-Pediatrics (GOSE-PEDs) at 12 months and acquired epilepsy. Association of biomarkers with outcomes was investigated using linear regression, Wilcoxon signed-rank, or Chi-square. RESULTS: Fourteen children were analyzed. Lower AF indices were associated with poor outcomes (BRS [p = 0.04], HRsd [p = 0.04], and HRrmssd [p = 0.00]; and acquired epilepsy (LHF [p = 0.027]). Higher CA indices were associated with poor outcomes (PRx [p = 0.00], wPRx [p = 0.00], and wPRx-thr [p = 0.01]), and acquired epilepsy (PRx [p = 0.02] and wPRx [p = 0.00]). Increased time below LLA was associated with poor outcome (percent time below LLA based on PRx [p = 0.00], PAx [p = 0.04], wPRx-thr [p = 0.03], and RAC [p = 0.01]; and acquired epilepsy (PRx [p = 0.00], PAx [p = 0.00], wPRx-thr [p = 0.03], and RAC [p = 0.01]). CONCLUSIONS: After pediatric cerebral AVM rupture, poor outcomes are associated with AF and CA when applying various neurophysiologic model-based indices. Prospective work is needed to assess these indices of CA and AF in clinical decision support.

Network-targeted approach and postoperative resting-state functional magnetic resonance imaging are associated with seizure outcome.

OBJECTIVE: Postoperative resting-state functional magnetic resonance imaging (MRI) in children with intractable epilepsy has not been quantified in relation to seizure outcome. Therefore, its value as a biomarker for epileptogenic pathology is not well understood. METHODS: In a sample of children with intractable epilepsy who underwent prospective resting-state seizure onset zone (SOZ)-targeted epilepsy surgery, postoperative resting-state functional MRI (rs-fMRI) was performed 6 to 12 months later. Graded normalization of the postoperative resting-state SOZ was compared to seizure outcomes, patient, surgery, and anatomical MRI characteristics. RESULTS: A total of 64 cases were evaluated. Network-targeted surgery, followed by postoperative rs-fMRI normalization was significantly (p < 0.001) correlated with seizure reduction, with a Spearman rank correlation coefficient of 0.83. Of 39 cases with postoperative rs-fMRI SOZ normalization, 38 (97%) became completely seizure free. In contrast, of the 25 cases without complete rs-fMRI SOZ normalization, only 3 (5%) became seizure free. The accuracy of rs-fMRI as a biomarker predicting seizure freedom is 94%, with 96% sensitivity and 93% specificity. INTERPRETATION: Among seizure localization techniques in pediatric epilepsy, network-targeted surgery, followed by postoperative rs-fMRI normalization, has high correlation with seizure freedom. This study shows that rs-fMRI SOZ can be used as a biomarker of the epileptogenic zone, and postoperative rs-fMRI normalization is a biomarker for SOZ quiescence. ANN NEUROL 2019;86:344-356.

Intracranial Electroencephalography in Pediatric Severe Traumatic Brain Injury.

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.

Subcentimeter epilepsy surgery targets by resting state functional magnetic resonance imaging can improve outcomes in hypothalamic hamartoma.

OBJECTIVE: The purpose of this study is to investigate the outcomes of epilepsy surgery targeting the subcentimeter-sized resting state functional magnetic resonance imaging (rs-fMRI) epileptogenic onset zone (EZ) in hypothalamic hamartoma (HH). METHODS: Fifty-one children with HH-related intractable epilepsy received anatomical MRI-guided stereotactic laser ablation (SLA) procedures. Fifteen of these children were control subjects (CS) not guided by rs-fMRI. Thirty-six had been preoperatively guided by rs-fMRI (RS) to determine EZs, which were subsequently targeted by SLA. The primary outcome measure for the study was a predetermined goal of 30% reduction in seizure frequency and improvement in class I Engel outcomes 1 year postoperatively. Quantitative and qualitative volumetric analyses of total HH and ablated tissue were also assessed. RESULTS: In the RS group, the EZ target within the HH was ablated with high accuracy (>87.5% of target ablated in 83% of subjects). There was no difference between the groups in percentage of ablated hamartoma volume (P = 0.137). Overall seizure reduction was higher in the rs-fMRI group: 85% RS versus 49% CS (P = 0.0006, adjusted). The Engel Epilepsy Surgery Outcome Scale demonstrated significant differences in those with freedom from disabling seizures (class I), 92% RS versus 47% CS, a 45% improvement (P = 0.001). Compared to prior studies, there was improvement in class I outcomes (92% vs 76%-81%). No postoperative morbidity or mortality occurred. SIGNIFICANCE: For the first time, surgical SLA targeting of subcentimeter-sized EZs, located by rs-fMRI, guided surgery for intractable epilepsy. Our outcomes demonstrated the highest seizure freedom rate without surgical complications and are a significant improvement over prior reports. The approach improved freedom from seizures by 45% compared to conventional ablation, regardless of hamartoma size or anatomical classification. This technique showed the same or reduced morbidity (0%) compared to recent non-rs-fMRI-guided SLA studies with as high as 20% permanent significant morbidity.

Motor network dynamic resting state fMRI connectivity of neurotypical children in regions affected by cerebral palsy.

Background: Normative childhood motor network resting-state fMRI effective connectivity is undefined, yet necessary for translatable dynamic resting-state-network-informed evaluation in pediatric cerebral palsy. Methods: Cross-spectral dynamic causal modeling of resting-state-fMRI was investigated in 50 neurotypically developing 5- to 13-year-old children. Fully connected six-node network models per hemisphere included primary motor cortex, striatum, subthalamic nucleus, globus pallidus internus, thalamus, and contralateral cerebellum. Parametric Empirical Bayes with exhaustive Bayesian model reduction and Bayesian modeling averaging informed the model; Purdue Pegboard Test scores of hand motor behavior were the covariate at the group level to determine the effective-connectivity-functional behavior relationship. Results: Although both hemispheres exhibited similar effective connectivity of motor cortico-basal ganglia-cerebellar networks, magnitudes were slightly greater on the right, except for left-sided connections of the striatum which were more numerous and of opposite polarity. Inter-nodal motor network effective connectivity remained consistent and robust across subjects. Age had a greater impact on connections to the contralateral cerebellum, bilaterally. Motor behavior, however, affected different connections in each hemisphere, exerting a more prominent effect on the left modulatory connections to the subthalamic nucleus, contralateral cerebellum, primary motor cortex, and thalamus. Discussion: This study revealed a consistent pattern of directed resting-state effective connectivity in healthy children aged 5-13 years within the motor network, encompassing cortical, subcortical, and cerebellar regions, correlated with motor skill proficiency. Both hemispheres exhibited similar effective connectivity within motor cortico-basal ganglia-cerebellar networks reflecting inter-nodal signal direction predicted by other modalities, mainly differing from task-dependent studies due to network differences at rest. Notably, age-related changes were more pronounced in connections to the contralateral cerebellum. Conversely, motor behavior distinctly impacted connections in each hemisphere, emphasizing its role in modulating left sided connections to the subthalamic nucleus, contralateral cerebellum, primary motor cortex, and thalamus. Motor network effective connectivity was correlated with motor behavior, validating its physiological significance. This study is the first to evaluate a normative effective connectivity model for the pediatric motor network using resting-state functional MRI correlating with behavior and serves as a foundation for identifying abnormal findings and optimizing targeted interventions like deep brain stimulation, potentially influencing future therapeutic approaches for children with movement disorders.

Diffusion and functional MRI in surgical neuromodulation.

Surgical neuromodulation has witnessed significant progress in recent decades. Notably, deep brain stimulation (DBS), delivered precisely within therapeutic targets, has revolutionized the treatment of medication-refractory movement disorders and is now expanding for refractory psychiatric disorders, refractory epilepsy, and post-stroke motor recovery. In parallel, the advent of incisionless treatment with focused ultrasound ablation (FUSA) can offer patients life-changing symptomatic relief. Recent research has underscored the potential to further optimize DBS and FUSA outcomes by conceptualizing the therapeutic targets as critical nodes embedded within specific brain networks instead of strictly anatomical structures. This paradigm shift was facilitated by integrating two imaging modalities used regularly in brain connectomics research: diffusion MRI (dMRI) and functional MRI (fMRI). These advanced imaging techniques have helped optimize the targeting and programming techniques of surgical neuromodulation, all while holding immense promise for investigations into treating other neurological and psychiatric conditions. This review aims to provide a fundamental background of advanced imaging for clinicians and scientists, exploring the synergy between current and future approaches to neuromodulation as they relate to dMRI and fMRI capabilities. Focused research in this area is required to optimize existing, functional neurosurgical treatments while serving to build an investigative infrastructure to unlock novel targets to alleviate the burden of other neurological and psychiatric disorders.

Resting-State Functional Magnetic Resonance Imaging Network Association With Mortality, Epilepsy, Cognition, and Motor Two-Year Outcomes in Suspected Severe Neonatal Acute Brain Injury.

BACKGROUND AND OBJECTIVES: In acute brain injury of neonates, resting-state functional magnetic resonance imaging (MRI) (RS) showed incremental association with consciousness, mortality, cognitive and motor development, and epilepsy, with correction for multiple comparisons, at six months postgestation in neonates with suspected acute brain injury (ABI). However, there are relatively few developmental milestones at six months to benchmark against, thus, we extended this cohort study to evaluate two-year outcomes. METHODS: In 40 consecutive neonates with ABI and RS, ordinal scores of resting-state networks; MRI, magnetic resonance spectroscopy, and electroencephalography; and up to 42-month outcomes of mortality, general and motor development, Pediatric Cerebral Performance Category Scale (PCPC), and epilepsy informed associations between tests and outcomes. RESULTS: Mean gestational age was 37.8 weeks, 68% were male, and 60% had hypoxic-ischemic encephalopathy. Three died in-hospital, four at six to 42 months, and five were lost to follow-up. Associations included basal ganglia network with PCPC (P = 0.0003), all-mortality (P = 0.005), and motor (P = 0.0004); language/frontoparietal network with developmental delay (P = 0.009), PCPC (P = 0.006), and all-mortality (P = 0.01); default mode network with developmental delay (P = 0.003), PCPC (P = 0.004), neonatal intensive care unit mortality (P = 0.01), and motor (P = 0.009); RS seizure onset zone with epilepsy (P = 0.01); and anatomic MRI with epilepsy (P = 0.01). CONCLUSION: For the first time, at any age, resting state functional MRI in ABI is associated with long-term epilepsy and RSNs predicted mortality in neonates. Severity of RSN abnormality was associated with incrementally worsened neurodevelopment including cognition, language, and motor function over two years.

The expert's knowledge combined with AI outperforms AI alone in seizure onset zone localization using resting state fMRI.

We evaluated whether integration of expert guidance on seizure onset zone (SOZ) identification from resting state functional MRI (rs-fMRI) connectomics combined with deep learning (DL) techniques enhances the SOZ delineation in patients with refractory epilepsy (RE), compared to utilizing DL alone. Rs-fMRI was collected from 52 children with RE who had subsequently undergone ic-EEG and then, if indicated, surgery for seizure control (n = 25). The resting state functional connectomics data were previously independently classified by two expert epileptologists, as indicative of measurement noise, typical resting state network connectivity, or SOZ. An expert knowledge integrated deep network was trained on functional connectomics data to identify SOZ. Expert knowledge integrated with DL showed a SOZ localization accuracy of 84.8 ± 4.5% and F1 score, harmonic mean of positive predictive value and sensitivity, of 91.7 ± 2.6%. Conversely, a DL only model yielded an accuracy of <50% (F1 score 63%). Activations that initiate in gray matter, extend through white matter, and end in vascular regions are seen as the most discriminative expert-identified SOZ characteristics. Integration of expert knowledge of functional connectomics can not only enhance the performance of DL in localizing SOZ in RE but also lead toward potentially useful explanations of prevalent co-activation patterns in SOZ. RE with surgical outcomes and preoperative rs-fMRI studies can yield expert knowledge most salient for SOZ identification.

Treatable brain network biomarkers in children in coma using task and resting-state functional MRI: a case series.

The withdrawal of life-sustaining therapies is frequently considered for pediatric patients with severe acute brain injuries who are admitted to the intensive care unit. However, it is worth noting that some children with a resultant poor neurological status may ultimately survive and achieve a positive neurological outcome. Evidence suggests that adults with hidden consciousness may have a more favorable prognosis compared to those without it. Currently, no treatable network disorders have been identified in cases of severe acute brain injury, aside from seizures detectable through an electroencephalogram (EEG) and neurostimulation via amantadine. In this report, we present three cases in which multimodal brain network evaluation played a helpful role in patient care. This evaluation encompassed various assessments such as continuous video EEG, visual-evoked potentials, somatosensory-evoked potentials, auditory brainstem-evoked responses, resting-state functional MRI (rs-fMRI), and passive-based and command-based task-based fMRI. It is worth noting that the latter three evaluations are unique as they have not yet been established as part of the standard care protocol for assessing acute brain injuries in children with suppressed consciousness. The first patient underwent serial fMRIs after experiencing a coma induced by trauma. Subsequently, the patient displayed improvement following the administration of antiseizure medication to address abnormal signals. In the second case, a multimodal brain network evaluation uncovered covert consciousness, a previously undetected condition in a pediatric patient with acute brain injury. In both patients, this discovery potentially influenced decisions concerning the withdrawal of life support. Finally, the third patient serves as a comparative control case, demonstrating the absence of detectable networks. Notably, this patient underwent the first fMRI prior to experiencing brain death as a pediatric patient. Consequently, this case series illustrates the clinical feasibility of employing multimodal brain network evaluation in pediatric patients. This approach holds potential for clinical interventions and may significantly enhance prognostic capabilities beyond what can be achieved through standard testing methods alone.

Discerning Seizure-Onset v. Propagation Zone: Pre-and-Post-Operative Resting-State fMRI Directionality and Boerwinkle Neuroplasticity Index.

The goal of this study was to determine resting state fMRI (rs-fMRI) effective connectivity (RSEC) capacity, agnostic of epileptogenic events, in distinguishing seizure onset zones (SOZ) from propagation zones (pZ). Consecutive patients (2.1-18.2 years old), with epilepsy and hypothalamic hamartoma, pre-operative rs-fMRI-directed surgery, post-operative imaging, and Engel class I outcomes were collected. Cross-spectral dynamic causal modelling (DCM) was used to estimate RSEC between the ablated rs-fMRI-SOZ to its region of highest connectivity outside the HH, defined as the propagation zone (pZ). Pre-operatively, RSEC from the SOZ and PZ was expected to be positive (excitatory), and pZ to SOZ negative (inhibitory), and post-operatively to be either diminished or non-existent. Sensitivity, accuracy, positive predictive value were determined for node-to-node connections. A Parametric Empirical Bayes (PEB) group analysis on pre-operative data was performed to identify group effects and effects of Engel class outcome and age. Pre-operative RSEC strength was also evaluated for correlation with percent seizure frequency improvement, sex, and region of interest size. Of the SOZ's RSEC, only 3.6% had no connection of significance to the pZ when patient models were individually reduced. Among remaining, 96% were in expected (excitatory signal found from SOZ â†’ pZ and inhibitory signal found from pZ â†’ SOZ) versus 3.6% reversed polarities. Both pre-operative polarity signals were equivalently as expected, with one false signal direction out of 26 each (3.7% total). Sensitivity of 95%, specificity 73%, accuracy of 88%, negative predictive value 88%, and positive predictive value of 88% in identifying and differentiating the SOZ and pZ. Groupwise PEB analysis confirmed SOZ â†’ pZ EC was excitatory, and pZ â†’ SOZ EC was inhibitory. Patients with better outcomes (Engel Ia vs. Ib) showed stronger inhibitory signal (pZ â†’ SOZ). Age was negatively associated with absolute RSEC bidirectionally but had no relationship with Directionality SOZ identification performance. In an additional hierarchical PEB analysis identifying changes from pre-to-post surgery, SOZ â†’ pZ modulation became less excitatory and pZ â†’ SOZ modulation became less inhibitory. This study demonstrates the accuracy of Directionality to identify the origin of excitatory and inhibitory signal between the surgically confirmed SOZ and the region of hypothesized propagation zone in children with DRE due to a HH. Thus, this method validation study in a homogenous DRE population may have potential in narrowing the SOZ-candidates for epileptogenicity in other DRE populations and utility in other neurological disorders.

Is Resting State Functional MRI Effective Connectivity in Movement Disorders Helpful? A Focused Review Across Lifespan and Disease.

In the evolving modern era of neuromodulation for movement disorders in adults and children, much progress has been made recently characterizing the human motor network (MN) with potentially important treatment implications. Herein is a focused review of relevant resting state fMRI functional and effective connectivity of the human motor network across the lifespan in health and disease. The goal is to examine how the transition from functional connectivity to dynamic effective connectivity may be especially informative of network-targeted movement disorder therapies, with hopeful implications for children.