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

A comparison of machine learning classifiers for pediatric epilepsy using resting-state functional MRI latency data

Epilepsy affects 1 in 150 children under the age of 10 and is the most common chronic pediatric neurological condition; poor seizure control can irreversibly disrupt normal brain development. The present study compared the ability of different machine learning algorithms trained with resting-state functional MRI (rfMRI) latency data to detect epilepsy. Preoperative rfMRI and anatomical MRI scans were obtained for 63 patients with epilepsy and 259 healthy controls. The normal distribution of latency z-scores from the epilepsy and healthy control cohorts were analyzed for overlap in 36 seed regions. In these seed regions, overlap between the study cohorts ranged from 0.44-0.58. Machine learning features were extracted from latency z-score maps using principal component analysis. Extreme Gradient Boosting (XGBoost), Support Vector Machines (SVM), and Random Forest algorithms were trained with these features. Area under the receiver operating characteristics curve (AUC), accuracy, sensitivity, specificity and F1-scores were used to evaluate model performance. The XGBoost model outperformed all other models with a test AUC of 0.79, accuracy of 74%, specificity of 73%, and a sensitivity of 77%. The Random Forest model performed comparably to XGBoost across multiple metrics, but it had a test sensitivity of 31%. The SVM model did not perform \u3e70% in any of the test metrics. The XGBoost model had the highest sensitivity and accuracy for the detection of epilepsy. Development of machine learning algorithms trained with rfMRI latency data could provide an adjunctive method for the diagnosis and evaluation of epilepsy with the goal of enabling timely and appropriate care for patients

Pre-surgical Features of Intrinsic Brain Networks Predict Single and Joint Epilepsy Surgery Outcomes

Despite the effectiveness of surgical interventions for the treatment of intractable focal temporal lobe epilepsy (TLE), the substrates that support good outcomes are poorly understood. While algorithms have been developed for the prediction of either seizure or cognitive/psychiatric outcomes alone, no study has reported on the functional and structural architecture that supports joint outcomes. We measured key aspects of pre-surgical whole brain functional/structural network architecture and evaluated their ability to predict post-operative seizure control in combination with cognitive/psychiatric outcomes. Pre-surgically, we identified the intrinsic connectivity networks (ICNs) unique to each person through independent component analysis (ICA), and computed: (1) the spatial-temporal match between each person\u27s ICA components and established, canonical ICNs, (2) the connectivity strength within each identified person-specific ICN, (3) the gray matter (GM) volume underlying the person-specific ICNs, and (4) the amount of variance not explained by the canonical ICNs for each person. Post-surgical seizure control and reliable change indices of change (for language [naming, phonemic fluency], verbal episodic memory, and depression) served as binary outcome responses in random forest (RF) models. The above functional and structural measures served as input predictors. Our empirically derived ICN-based measures customized to the individual showed that good joint seizure and cognitive/psychiatric outcomes depended upon higher levels of brain reserve (GM volume) in specific networks. In contrast, singular outcomes relied on systematic, idiosyncratic variance in the case of seizure control, and the weakened pre-surgical presence of functional ICNs that encompassed the ictal temporal lobe in the case of cognitive/psychiatric outcomes. Our data made clear that the ICNs differed in their propensity to provide reserve for adaptive outcomes, with some providing structural (brain), and others functional (cognitive) reserve. Our customized methodology demonstrated that when substantial unique, patient-specific ICNs are present prior to surgery there is a reliable association with poor post-surgical seizure control. These ICNs are idiosyncratic in that they did not match the canonical, normative ICNs and, therefore, could not be defined functionally, with their location likely varying by patient. This important finding suggested the level of highly individualized ICN\u27s in the epileptic brain may signal th

Imaging brain networks in focal epilepsy: a prospective study of the clinical application of simultaneous EEG-fMRI in pre-surgical evaluation

Epilepsy is a common disorder with significant associated morbidity and mortality. Despite advances in treatment, there remain a minority of people with pharmacoresistant focal epilepsy for whom surgery may be beneficial. It has been suggested that not enough people are offered surgical treatment, partly owing to the fact that current non-invasive techniques do not always adequately identify the seizure onset zone so that invasive EEG is required. EEG-fMRI is an imaging technique, developed in the 1990s (Ives, Warach et al. 1993) which identifies regions of interictal epileptiform discharge associated haemodynamic changes, that are concordant with the seizure onset zone in some patients (Salek-Haddadi, Diehl et al. 2006). To date there has been no large scale prospective comparison with icEEG and postoperative outcome. This thesis presents a series of experiments, carried out in a cohort of patients scanned using EEG-fMRI as part of a multi-centre programme, designed to investigate the relationship between EEG-fMRI and intracranial EEG and to assess its potential role in pre-surgical evaluation of patients with focal epilepsy. The results suggested that positive, localised IED-related BOLD signal changes were sensitive for the seizure onset zone, as determined on icEEG, both in patients neocortical epilepsies, but were not predictive of outcome. Widespread regions of positive IEDrelated BOLD signal change were associated with widespread or multifocal abnormalities on icEEG and poor outcome. Patterns of haemodynamic change, identified using both data driven and EEG derived modeling approaches, correspond to regions of seizure onset on icEEG, but improvements for modeling seizures are required. A study of a single seizure in a patient who underwent simultaneous icEEGfMRI, showed similar findings.. An exploratory investigation of fMRI-DCM in EEG-fMRI, suggested it can provide information about seizure propagation and this opens new avenues for the non-invasive study of the epileptic network and interactions with function

Clinical applications of magnetic resonance imaging based functional and structural connectivity

Advances in computational neuroimaging techniques have expanded the armamentarium of imaging tools available for clinical applications in clinical neuroscience. Non-invasive, in vivo brain MRI structural and functional network mapping has been used to identify therapeutic targets, define eloquent brain regions to preserve, and gain insight into pathological processes and treatments as well as prognostic biomarkers. These tools have the real potential to inform patient-specific treatment strategies. Nevertheless, a realistic appraisal of clinical utility is needed that balances the growing excitement and interest in the field with important limitations associated with these techniques. Quality of the raw data, minutiae of the processing methodology, and the statistical models applied can all impact on the results and their interpretation. A lack of standardization in data acquisition and processing has also resulted in issues with reproducibility. This limitation has had a direct impact on the reliability of these tools and ultimately, confidence in their clinical use. Advances in MRI technology and computational power as well as automation and standardization of processing methods, including machine learning approaches, may help address some of these issues and make these tools more reliable in clinical use. In this review, we will highlight the current clinical uses of MRI connectomics in the diagnosis and treatment of neurological disorders; balancing emerging applications and technologies with limitations of connectivity analytic approaches to present an encompassing and appropriate perspective

Multimodal functional neuroimaging of epilepsy and Pain

University of Minnesota Ph.D. dissertation.June 2015. Major: Biomedical Engineering. Advisor: Bin He. 1 computer file (PDF); vi, 139 pages.The overall goal of this thesis work is to use advanced noninvasive neuroimaging modalities and techniques to study the underlying neurological mechanism of both diseased and healthy brains. The two main applications of this work are for the diagnosis of epilepsy and management of pain. Epilepsy is one of the most prevalent neurological disorders. It affects an estimated 2.7 million Americans. There are two broad types of epilepsies: partial and generalized epilepsy. For patients with drug resistant focal epilepsy, which account for one third of the patient population, surgical resection may provide the opportunity of seizure control. Existing presurgical planning methods are not only invasive in nature; they may also fail to provide additional information needed for surgery due to the relatively limited spatial coverage. On the other hand, idiopathic generalized epilepsy (IGE), unlike focal or partial epilepsy, often affects the whole or a larger portion of the brain without obvious, known cause. Treatment options are more restricted as resection is not a choice. Therefore, it is important to understand the underlying network which generates epileptic activity and through which epileptic activity propagates. The aim of the present study in the epilepsy portion was to use noninvasive imaging techniques including fMRI and EEG to localize epileptic areas for the purpose of assisting surgical planning in the focal epilepsy cases; and to improve our understanding the underlying mechanism of generalized epilepsy, thalamocortical relationship in the IGE cases. Chronic Pain is one of the biggest medical burdens in developed countries, affecting 20% of adult population with estimated economic cost in the United States alone over $150 billion. Functional imaging of brain networks associated with pain processing is of vital importance to aid developing new pain-relief therapies and to better understand the mechanisms of pain perception. The long-term goal of this project is to study the neurological mechanism of subjective perception of pain using non-invasive neuroimaging methods. In the present work of the pain portion, changes brain activities in healthy subjects experiencing sustained external painful stimuli were first studied. Neural activities in patient with sickle cell disease, who often surfer spontaneous acute or chronic pain as one of the comorbidities of the disease, were contrasted with healthy controls to study changes in neural network as a result of prolonged exposure to internal In summary, the present dissertation research developed and evaluated the spatiotemporal imaging approaches for the non-invasive mapping of network activities in the diseased and normal brain. Evaluations were conducted in patient and healthy control groups in order to test the clinical applicability of such a pre-surgical noninvasive imaging tool. An investigation has been conducted to study the widespread GSWDs of generalized epilepsy patients. The spatial resolution has been further improved by adding the component of fMRI through an EEG-fMRI integrated imaging framework. For the application in pain study, two investigations were conducted to study changes in network level activity due to external pain in healthy subjects and spontaneous pain in patients with SCD. All of the results that were obtained suggest the importance of noninvasive spatiotemporal neuroimaging approaches for solving clinical problems and for investigating neuroscience questions. Furthermore, an improved understanding of neurological diseases and their mechanisms would help us to develop and deliver curative treatments of neurological diseases

Advanced Invasive Neurophysiological Methods to Aid Decision Making in Paediatric Epilepsy Surgery

For patients with drug-resistant focal epilepsy, surgery is the most effective treatment to attain seizure freedom. Intracranial electroencephalogram investigations succeed in defining the seizure onset zone (SOZ) where non-invasive methods fail to identify a single seizure generator. However, resection of the SOZ does not always lead to a surgical benefit and, in addition, eloquent functions like language might be compromised. The aim of this thesis was to use advanced invasive neurophysiological methods to improve pre-surgical planning in two ways. The first aim was to improve delineation of the pathological tissue, the SOZ using novel quantitative neurophysiological biomarkers: high gamma activity (80–150Hz) phase-locked to low frequency iEEG discharges (phase-locked high gamma, PLHG) and high frequency oscillations called fast ripples (FR, 250–500Hz). Resection of contacts containing these markers were recently reported to lead to an improved seizure outcome. The current work shows the first replication of the PLHG metric in a small adult pilot study and a larger paediatric cohort. Furthermore, I tested whether surgical removal of PLHG- and/or FR-generating brain areas resulted in better outcome compared to the current clinical SOZ delineation. The second aim of this work was to aid delineation of eloquent language cortex. Invasive event-related potentials (iERP) and spectral changes in the beta and gamma frequency bands were used to determine cortical dynamics during speech perception and production across widespread brain regions. Furthermore, the relationship between these cortical dynamics and the relationship to electrical stimulation responses was explored. For delineation of pathological tissue, the combination of FRs and SOZ proved to be a promising biomarker. Localising language cortex showed the highest level of activity around the perisylvian brain regions with a significantly higher occurrence rate of iERPs compared to spectral changes. Concerning electrical stimulation mapping beta and high gamma frequency bands represented the most promising markers

Microscopic Studies of Neurovascular Coupling During Epilepsy in the Mouse Brain

Les mécanismes liant l’activité neuronale au changement local du flot sanguin sont regroupés dans un ensemble nommé couplage neurovasculaire. Ce lien neurovasculaire, qui est à la base de plusieurs principes d’imagerie fonctionnelle du cerveau, est altéré par l’épilepsie. Ces dernières années, des techniques d’imagerie tel l’IRMf, IOS et la NIRS ont été utilisées pour l’étude de cette maladie, montrant une forte corrélation entre l’activité épileptique et le signal mesuré. Par contre, la plupart de ces travaux se sont concentrés sur les changements d’hémoglobine, qui peuvent être liés à des phénomènes non-linéaires et qui ne renseignent pas directement sur la quantification de l’oxygène délivré localement. Le but de cette thèse est d’investiguer l’utilisation de la microscopie avec de nouvelles sondes moléculaires permettant l’imagerie de l’oxygénation des tissus durant les évènements épileptiques dans le cortex sensori-moteur de la souris. Dans un premier temps, une méthode de mesure de la pression partielle d’oxygène (PO2) en microscopie confocale du temps de vie de phosphorescence fut développée. Ce système permet une mesure minimalement invasive du PO2 dans les tissus corticaux à haute fréquences spatiale et temporelle lorsqu’il est utilisé conjointement avec la sonde phosphorescente OxyphorG4. Les mesures réalisées durant les crises épileptiques, induites avec l’agent 4-aminopyridine (4-AP), montrent des changements significatifs de l’oxygénation tissulaire. De plus, la distribution spatio-temporelle de la chute initiale de la réserve en oxygène, à proximité du point d’injection et le long des artérioles, a été caractérisé durant ces mêmes épisodes épileptiques. Une corrélation positive entre la variation du PO2 durant cette première phase et la durée de la crise épileptique a aussi été mesurée. Cette mesure pourrait s’avérer utile dans la localisation des foyers épileptique et dans la prédiction de la durée des crises. La deuxième étude présentée dans cette thèse se concentre sur le possible rôle joué par les astrocytes, qui sont un des acteurs importants dans le couplage neurovasculaire, dans la propagation des crises épileptiques. La concentration en ions calciques libres à la base axonale des astrocytes, conjointement avec le diamètre des artérioles adjacentes a été mesuré in-vivo en simultané sur des souris durant les épisodes épileptiques. Pour la mesure du calcium, la sonde fluorescente OregonGreen BAPTA-1 AM (OGB-1) a été utilisée en imagerie du temps de demie-vie de fluorescence avec un microscope 2-photons. Les résultats montrent que l’augmentation de calcium induirait une vasodilatation à chaque ictus dans la région du foyer épileptique. Dans les régions plus éloignées, cette même mesure corrèlerait plutôt avec une vasoconstriction dans les premiers moments de la crise, suivi par une vasodilatation selon la durée de l’épisode. De plus, une augmentation lente du niveau absolu de la concentration calcique a été observée lors de longues séquences d’évènements. Cette tendance à la hausse semble induire à son tour une constriction des artérioles dans les régions adjacentes. Ces observations confirment le rôle des astrocytes dans le contrôle local de la microcirculation et suggèrent un second rôle de modulation du niveau de la concentration calcique autour de leur base axonale. Puisqu’il n’a pas été possible de mesurer le PO2 en profondeur dans le cerveau ou de pouvoir imager adéquatement les réseaux de capillaires en microscopie confocale, et suivant le développement d’une sonde sensible aux ions d’oxygène en microscopie 2-photons, il a donc été possible, dans le cadre de la dernière étude de cette thèse, d’acquérir cette mesure en profondeur durant des épisodes épileptiques. Des changements significatifs du PO2 dans les tissus et les vaisseaux ont pu être observés. La distribution spatiale de la chute initiale de ce paramètre autour des artérioles, des capillaires, des veinules et du tissu près du foyer a pu être caractérisée. Les résultats obtenus pourraient avoir des implications profondes dans notre compréhension des mécanismes de livraison de l’oxygène dans les tissus en profondeur et leur capacité à supporter le cortex adéquatement dans les situations pathologiques. Le potentiel de la microscopie dans l’étude du couplage neurovasculaire et des changements liés à des pathologies a pu être pleinement démontré par les travaux de cette thèse.----------ABSTRACT Neurovascular coupling (NVC) is the mechanism that links a transient neural activity to the corresponding increase of cerebral blood flow (CBF). It underlies the local increase in blood flow during neural activity, forms the basis of functional brain imaging and is altered in epilepsy. For the last decades, functional imaging using BOLD fMRI, IOS and fNIRS and others have been applied to epilepsy, and yielded good correlation between epileptic activity and the measured signal. However, most previous work on epilepsy focused on the measurement of hemoglobin changes which sometimes leads to non-linear phenomena and does not quantify oxygen delivery in tissue. The aim of this thesis is to study oxygen delivery using microscopy with new oxygen sensitive molecular probes during epileptic events in the mouse somatosensory cortex. First, a confocal phosphorescence lifetime microscopy system for measuring brain oxygen partial pressure (PO2) was developed. This system enabled minimally invasive measurements of oxygen partial pressure in cerebral tissue with high spatial and temporal resolution using a dendritic phosphorescent probe, Oxyphor G4. Significant changes of PO2 in tissue were found at the epileptic focus and in remote areas during 4-aminopyridine (4-AP) induced epilepsy. The spatio-temporal distribution of the “initial dip” in PO2 near the injection site and along nearby arterioles was characterized by investigating epileptic events. A positive correlation between the percent change in the PO2 signal during the “initial dip” and the duration of seizure-like activity was revealed in this work, which may help localize the epileptic focus and predict the length of seizures. Because astrocytic calcium signalling is involved in neurovascular coupling, the second study investigated the role of this pathway in epilepsy. The free calcium concentration in astrocytic endfeet and diameter of adjacent arterioles were simultaneously monitored with the calcium-sensitive indicator OGB-1 by two-photon fluorescence lifetime measurements following 4-AP injection. Our results revealed that, increases in calcium concentration induced vasodilation for each ictal event in the focus. In the remote area, increases in calcium concentration correlated with vasoconstriction at the onset of seizure and vasodilation during the later part of the seizures. Furthermore, a slow increase in absolute calcium concentration following multiple seizures was observed, which in turn, caused a trend of arteriolar constriction both at the epileptic focus and remote areas. These observations confirmed the role of astrocytes in the control of local microcirculation and suggest a modulating role for baseline absolute calcium concentration in astrocytic endfeet. Since the confocal phosphorescence microscopy system was not able to measure PO2 deep in the cortex or resolve capillaries, two-photon phosphorescence microscopy was then used in the last project to study the PO2 delivery during epilepsy in deep tissue and vessels. Significant changes of PO2 in tissue and vasculature were observed during epileptic events. The spatial landscape of “initial dip” in PO2 signals around arterioles, veins and tissue near the injection site was characterized. These results may have profound implications for evaluating microvascular oxygen delivery capacity to support cerebral tissue in disease. The results of this thesis confirmed the potential of using microscopy to study neurovascular coupling during epilepsy

Functional network correlates of language and semiology in epilepsy

Epilepsy surgery is appropriate for 2-3% of all epilepsy diagnoses. The goal of the presurgical workup is to delineate the seizure network and to identify the risks associated with surgery. While interpretation of functional MRI and results in EEG-fMRI studies have largely focused on anatomical parameters, the focus of this thesis was to investigate canonical intrinsic connectivity networks in language function and seizure semiology. Epilepsy surgery aims to remove brain areas that generate seizures. Language dysfunction is frequently observed after anterior temporal lobe resection (ATLR), and the presurgical workup seeks to identify the risks associated with surgical outcome. The principal aim of experimental studies was to elaborate understanding of language function as expressed in the recruitment of relevant connectivity networks and to evaluate whether it has value in the prediction of language decline after anterior temporal lobe resection. Using cognitive fMRI, we assessed brain areas defined by parameters of anatomy and canonical intrinsic connectivity networks (ICN) that are involved in language function, specifically word retrieval as expressed in naming and fluency. fMRI data was quantified by lateralisation indices and by ICN_atlas metrics in a priori defined ICN and anatomical regions of interest. Reliability of language ICN recruitment was studied in 59 patients and 30 healthy controls who were included in our language experiments. New and established language fMRI paradigms were employed on a three Tesla scanner, while intellectual ability, language performance and emotional status were established for all subjects with standard psychometric assessment. Patients who had surgery were reinvestigated at an early postoperative stage of four months after anterior temporal lobe resection. A major part of the work sought to elucidate the association between fMRI patterns and disease characteristics including features of anxiety and depression, and prediction of postoperative language outcome. We studied the efficiency of reorganisation of language function associated with disease features prior to and following surgery. A further aim of experimental work was to use EEG-fMRI data to investigate the relationship between canonical intrinsic connectivity networks and seizure semiology, potentially providing an avenue for characterising the seizure network in the presurgical workup. The association of clinical signs with the EEG-fMRI informed activation patterns were studied using the data from eighteen patients’ whose seizures and simultaneous EEG-fMRI activations were reported in a previous study. The accuracy of ICN_atlas was validated and the ICN construct upheld in the language maps of TLE patients. The ICN construct was not evident in ictal fMRI maps and simulated ICN_atlas data. Intrinsic connectivity network recruitment was stable between sessions in controls. Amodal linguistic processing and the relevance of temporal intrinsic connectivity networks for naming and that of frontal intrinsic connectivity networks for word retrieval in the context of fluency was evident in intrinsic connectivity networks regions. The relevance of intrinsic connectivity networks in the study of language was further reiterated by significant association between some disease features and language performance, and disease features and activation in intrinsic connectivity networks. However, the anterior temporal lobe (ATL) showed significantly greater activation compared to intrinsic connectivity networks – a result which indicated that ATL functional language networks are better studied in the context of the anatomically demarked ATL, rather than its functionally connected intrinsic connectivity networks. Activation in temporal lobe networks served as a predictor for naming and fluency impairment after ATLR and an increasing likelihood of significant decline with greater magnitude of left lateralisation. Impairment of awareness served as a significant classifying feature of clinical expression and was significantly associated with the inhibition of normal brain functions. Canonical intrinsic connectivity networks including the default mode network were recruited along an anterior-posterior anatomical axis and were not significantly associated with clinical signs