Predicting post-surgical functional status in high-grade glioma with resting state fMRI and machine learning.

PURPOSE: High-grade glioma (HGG) is the most common and deadly malignant glioma of the central nervous system. The current standard of care includes surgical resection of the tumor, which can lead to functional and cognitive deficits. The aim of this study is to develop models capable of predicting functional outcomes in HGG patients before surgery, facilitating improved disease management and informed patient care. METHODS: Adult HGG patients (N = 102) from the neurosurgery brain tumor service at Washington University Medical Center were retrospectively recruited. All patients completed structural neuroimaging and resting state functional MRI prior to surgery. Demographics, measures of resting state network connectivity (FC), tumor location, and tumor volume were used to train a random forest classifier to predict functional outcomes based on Karnofsky Performance Status (KPS < 70, KPS ≥ 70). RESULTS: The models achieved a nested cross-validation accuracy of 94.1% and an AUC of 0.97 in classifying KPS. The strongest predictors identified by the model included FC between somatomotor, visual, auditory, and reward networks. Based on location, the relation of the tumor to dorsal attention, cingulo-opercular, and basal ganglia networks were strong predictors of KPS. Age was also a strong predictor. However, tumor volume was only a moderate predictor. CONCLUSION: The current work demonstrates the ability of machine learning to classify postoperative functional outcomes in HGG patients prior to surgery accurately. Our results suggest that both FC and the tumor's location in relation to specific networks can serve as reliable predictors of functional outcomes, leading to personalized therapeutic approaches tailored to individual patients.

Focused Ultrasound-mediated Liquid Biopsy in a Tauopathy Mouse Model.

Background Neurodegenerative disorders (such as Alzheimer disease) characterized by the deposition of various pathogenic forms of tau protein in the brain are collectively referred to as tauopathies. Identification of the molecular drivers and pathways of neurodegeneration is critical to individualized targeted treatment of these disorders. However, despite important advances in fluid biomarker detection, characterization of these molecular subtypes is limited by the blood-brain barrier. Purpose To evaluate the feasibility and safety of focused ultrasound-mediated liquid biopsy (sonobiopsy) in the detection of brain-derived protein biomarkers in a transgenic mouse model of tauopathy (PS19 mice). Materials and Methods Sonobiopsy was performed by sonicating the cerebral hemisphere in 2-month-old PS19 and wild-type mice, followed by measurement of plasma phosphorylated tau (p-tau) species (30 minutes after sonication in the sonobiopsy group). Next, spatially targeted sonobiopsy was performed by sonicating either the cerebral cortex or the hippocampus in 6-month-old PS19 mice. To detect changes in plasma neurofilament light chain (a biomarker of neurodegeneration) levels, blood samples were collected before and after sonication (15 and 45-60 minutes after sonication). Histologic staining was performed to evaluate tissue damage after sonobiopsy. The Shapiro-Wilk test, unpaired and paired t tests, and the Mann-Whitney U test were used. Results In the 2-month-old mice, sonobiopsy significantly increased the normalized levels of plasma p-tau species compared with the conventional blood-based liquid biopsy (p-tau-181-to-mouse tau [m-tau] ratio: 1.7-fold increase, P = .006; p-tau-231-to-m-tau ratio: 1.4-fold increase, P = .048). In the 6-month-old PS19 mice, spatially targeted sonobiopsy resulted in a 2.3-fold increase in plasma neurofilament light chain after sonication of the hippocampus and cerebral cortex (P < .001). After optimization of the sonobiopsy parameters, no excess microhemorrhage was observed in the treated cerebral hemisphere compared with the contralateral side. Conclusion This study showed the feasibility of sonobiopsy to release phosphorylated tau species and neurofilament light chain to the blood circulation, potentially facilitating diagnosis of neurodegenerative disorders. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Fowlkes in this issue.

Predicting survival in glioblastoma with multimodal neuroimaging and machine learning.

PURPOSE: Glioblastoma (GBM) is the most common and aggressive malignant glioma, with an overall median survival of less than two years. The ability to predict survival before treatment in GBM patients would lead to improved disease management, clinical trial enrollment, and patient care. METHODS: GBM patients (N = 133, mean age 60.8 years, median survival 14.1 months, 57.9% male) were retrospectively recruited from the neurosurgery brain tumor service at Washington University Medical Center. All patients completed structural neuroimaging and resting state functional MRI (RS-fMRI) before surgery. Demographics, measures of cortical thickness (CT), and resting state functional network connectivity (FC) were used to train a deep neural network to classify patients based on survival (< 1y, 1-2y, >2y). Permutation feature importance identified the strongest predictors of survival based on the trained models. RESULTS: The models achieved a combined cross-validation and hold out accuracy of 90.6% in classifying survival (< 1y, 1-2y, >2y). The strongest demographic predictors were age at diagnosis and sex. The strongest CT predictors of survival included the superior temporal sulcus, parahippocampal gyrus, pericalcarine, pars triangularis, and middle temporal regions. The strongest FC features primarily involved dorsal and inferior somatomotor, visual, and cingulo-opercular networks. CONCLUSION: We demonstrate that machine learning can accurately classify survival in GBM patients based on multimodal neuroimaging before any surgical or medical intervention. These results were achieved without information regarding presentation symptoms, treatments, postsurgical outcomes, or tumor genomic information. Our results suggest GBMs have a global effect on the brain's structural and functional organization, which is predictive of survival.

Deep learning resting state functional magnetic resonance imaging lateralization of temporal lobe epilepsy.

OBJECTIVE: Localization of focal epilepsy is critical for surgical treatment of refractory seizures. There remains a great need for noninvasive techniques to localize seizures for surgical decision-making. We investigate the use of deep learning using resting state functional magnetic resonance imaging (RS-fMRI) to identify the hemisphere of seizure onset in temporal lobe epilepsy (TLE) patients. METHODS: A total of 2132 healthy controls and 32 preoperative TLE patients were studied. All participants underwent structural MRI and RS-fMRI. Healthy control data were used to generate training samples for a three-dimensional convolutional neural network (3DCNN). RS-fMRI was synthetically altered in randomly lateralized regions in the healthy control participants. The model was then trained to classify the hemisphere containing synthetic noise. Finally, the model was tested on TLE patients to assess its performance for detecting biological seizure onset zones, and gradient-weighted class activation mapping (Grad-CAM) identified the strongest predictive regions. RESULTS: The 3DCNN classified healthy control hemispheres known to contain synthetic noise with 96% accuracy, and TLE hemispheres clinically identified to be seizure onset zones with 90.6% accuracy. Grad-CAM identified a range of temporal, frontal, parietal, and subcortical regions that were strong anatomical predictors of the seizure onset zone, and the resting state networks that colocalized with Grad-CAM results included default mode, medial temporal, and dorsal attention networks. Lastly, in an analysis of a subset of patients with postsurgical outcomes, the 3DCNN leveraged a more focal set of regions to achieve classification in patients with Engel Class >I compared to Engel Class I. SIGNIFICANCE: Noninvasive techniques capable of localizing the seizure onset zone could improve presurgical planning in patients with intractable epilepsy. We have demonstrated the ability of deep learning to identify the correct hemisphere of the seizure onset zone in TLE patients using RS-fMRI with high accuracy. This approach represents a novel technique of seizure lateralization that could improve preoperative surgical planning.

Neoadjuvant stereotactic radiosurgery for brain metastases: a new paradigm.

OBJECTIVE: For patients with surgically accessible solitary metastases or oligometastatic disease, treatment often involves resection followed by postoperative stereotactic radiosurgery (SRS). This strategy has several potential drawbacks, including irregular target delineation for SRS and potential tumor "seeding" away from the resection cavity during surgery. A neoadjuvant (preoperative) approach to radiation therapy avoids these limitations and offers improved patient convenience. This study assessed the efficacy of neoadjuvant SRS as a new treatment paradigm for patients with brain metastases. METHODS: A retrospective review was performed at a single institution to identify patients who had undergone neoadjuvant SRS (specifically, Gamma Knife radiosurgery) followed by resection of a brain metastasis. Kaplan-Meier survival and log-rank analyses were used to evaluate risks of progression and death. Assessments were made of local recurrence and leptomeningeal spread. Additionally, an analysis of the contemporary literature of postoperative and neoadjuvant SRS for metastatic disease was performed. RESULTS: Twenty-four patients who had undergone neoadjuvant SRS followed by resection of a brain metastasis were identified in the single-institution cohort. The median age was 64 years (range 32-84 years), and the median follow-up time was 16.5 months (range 1 month to 5.7 years). The median radiation dose was 17 Gy prescribed to the 50% isodose. Rates of local disease control were 100% at 6 months, 87.6% at 12 months, and 73.5% at 24 months. In 4 patients who had local treatment failure, salvage therapy included repeat resection, laser interstitial thermal therapy, or repeat SRS. One hundred thirty patients (including the current cohort) were identified in the literature who had been treated with neoadjuvant SRS prior to resection. Overall rates of local control at 1 year after neoadjuvant SRS treatment ranged from 49% to 91%, and rates of leptomeningeal dissemination from 0% to 16%. In comparison, rates of local control 1 year after postoperative SRS ranged from 27% to 91%, with 7% to 28% developing leptomeningeal disease. CONCLUSIONS: Neoadjuvant SRS for the treatment of brain metastases is a novel approach that mitigates the shortcomings of postoperative SRS. While additional prospective studies are needed, the current study of 130 patients including the summary of 106 previously published cases supports the safety and potential efficacy of preoperative SRS with potential for improved outcomes compared with postoperative SRS.

On the role of the corpus callosum in interhemispheric functional connectivity in humans.

Resting state functional connectivity is defined in terms of temporal correlations between physiologic signals, most commonly studied using functional magnetic resonance imaging. Major features of functional connectivity correspond to structural (axonal) connectivity. However, this relation is not one-to-one. Interhemispheric functional connectivity in relation to the corpus callosum presents a case in point. Specifically, several reports have documented nearly intact interhemispheric functional connectivity in individuals in whom the corpus callosum (the major commissure between the hemispheres) never develops. To investigate this question, we assessed functional connectivity before and after surgical section of the corpus callosum in 22 patients with medically refractory epilepsy. Section of the corpus callosum markedly reduced interhemispheric functional connectivity. This effect was more profound in multimodal associative areas in the frontal and parietal lobe than primary regions of sensorimotor and visual function. Moreover, no evidence of recovery was observed in a limited sample in which multiyear, longitudinal follow-up was obtained. Comparison of partial vs. complete callosotomy revealed several effects implying the existence of polysynaptic functional connectivity between remote brain regions. Thus, our results demonstrate that callosal as well as extracallosal anatomical connections play a role in the maintenance of interhemispheric functional connectivity.

Unilateral, 3D Arm Movement Kinematics Are Encoded in Ipsilateral Human Cortex.

There is increasing evidence that the hemisphere ipsilateral to a moving limb plays a role in planning and executing movements. However, the exact relationship between cortical activity and ipsilateral limb movements is uncertain. We sought to determine whether 3D arm movement kinematics (speed, velocity, and position) could be decoded from cortical signals recorded from the hemisphere ipsilateral to the moving limb. By having invasively monitored patients perform unilateral reaches with each arm, we also compared the encoding of contralateral and ipsilateral limb kinematics from a single cortical hemisphere. In four motor-intact human patients (three male, one female) implanted with electrocorticography electrodes for localization of their epileptic foci, we decoded 3D movement kinematics of both arms with accuracies above chance. Surprisingly, the spatial and spectral encoding of contralateral and ipsilateral limb kinematics was similar, enabling cross-prediction of kinematics between arms. These results clarify our understanding that the ipsilateral hemisphere robustly contributes to motor execution and supports that the information of complex movements is more bihemispherically represented in humans than has been previously understood.SIGNIFICANCE STATEMENT Although limb movements are traditionally understood to be driven by the cortical hemisphere contralateral to a moving limb, movement-related neural activity has also been found in the ipsilateral hemisphere. This study provides the first demonstration that 3D arm movement kinematics can be decoded from human electrocorticographic signals ipsilateral to the moving limb. Surprisingly, the spatial and spectral encoding of contralateral and ipsilateral limb kinematics was similar. The finding that specific kinematics are encoded in the ipsilateral hemisphere demonstrates that the ipsilateral hemisphere contributes to the execution of unilateral limb movements, improving our understanding of motor control. Additionally, the bihemisheric representation of voluntary movements has implications for the development of neuroprosthetic systems for reaching and for neurorehabilitation strategies following cortical injuries.

Evaluation of pediatric glioma outcomes using intraoperative MRI: a multicenter cohort study.

BACKGROUND: The use of intraoperative MRI (iMRI) during treatment of gliomas may increase extent of resection (EOR), decrease need for early reoperation, and increase progression-free and overall survival, but has not been fully validated, particularly in the pediatric population. OBJECTIVE: To assess the accuracy of iMRI to identify residual tumor in pediatric patients with glioma and determine the effect of iMRI on decisions for resection, complication rates, and other outcomes. METHODS: We retrospectively analyzed a multicenter database of pediatric patients (age ≤ 18 years) who underwent resection of pathologically confirmed gliomas. RESULTS: We identified 314 patients (mean age 9.7 ± 4.6 years) with mean follow-up of 48.3 ± 33.6 months (range 0.03-182.07 months) who underwent surgery with iMRI. There were 201 (64.0%) WHO grade I tumors, 57 (18.2%) grade II, 24 (7.6%) grade III, 9 (2.9%) grade IV, and 23 (7.3%) not classified. Among 280 patients who underwent resection using iMRI, 131 (46.8%) had some residual tumor and underwent additional resection after the first iMRI. Of the 33 tissue specimens sent for pathological analysis after iMRI, 29 (87.9%) showed positive tumor pathology. Gross total resection was identified in 156 patients (55.7%), but this was limited by 69 (24.6%) patients with unknown EOR. CONCLUSIONS: Analysis of the largest multicenter database of pediatric gliomas resected using iMRI demonstrated additional tumor resection in a substantial portion of cases. However, determining the impact of iMRI on EOR and outcomes remains challenging because iMRI use varies among providers nationally. Continued refinement of iMRI techniques for use in pediatric patients with glioma may improve outcomes.

Human cortical-hippocampal dialogue in wake and slow-wave sleep.

Declarative memory consolidation is hypothesized to require a two-stage, reciprocal cortical-hippocampal dialogue. According to this model, higher frequency signals convey information from the cortex to hippocampus during wakefulness, but in the reverse direction during slow-wave sleep (SWS). Conversely, lower-frequency activity propagates from the information "receiver" to the "sender" to coordinate the timing of information transfer. Reversal of sender/receiver roles across wake and SWS implies that higher- and lower-frequency signaling should reverse direction between the cortex and hippocampus. However, direct evidence of such a reversal has been lacking in humans. Here, we use human resting-state fMRI and electrocorticography to demonstrate that δ-band activity and infraslow activity propagate in opposite directions between the hippocampus and cerebral cortex. Moreover, both δ activity and infraslow activity reverse propagation directions between the hippocampus and cerebral cortex across wake and SWS. These findings provide direct evidence for state-dependent reversals in human cortical-hippocampal communication.

Resting-state network mapping in neurosurgical practice: a review.

Resting-state functional MRI (rs-fMRI) is a well-established method for studying intrinsic connectivity and mapping the topography of functional networks in the human brain. In the clinical setting, rs-fMRI has been used to define functional topography, typically language and motor systems, in the context of preoperative planning for neurosurgery. Intraoperative mapping of critical speech and motor areas with electrocortical stimulation (ECS) remains standard practice, but preoperative noninvasive mapping has the potential to reduce operative time and provide functional localization when awake mapping is not feasible. Task-based fMRI has historically been used for this purpose, but it can be limited by the young age of the patient, cognitive impairment, poor cooperation, and need for sedation. Resting-state fMRI allows reliable analysis of all functional networks with a single study and is inherently independent of factors affecting task performance. In this review, the authors provide a summary of the theory and methods for resting-state network mapping. They provide case examples illustrating clinical implementation and discuss limitations of rs-fMRI and review available data regarding performance in comparison to ECS. Finally, they discuss novel opportunities for future clinical applications and prospects for rs-fMRI beyond mapping of regions to avoid during surgery but, instead, as a tool to guide novel network-based therapies.

Distinct phase-amplitude couplings distinguish cognitive processes in human attention.

Spatial attention is the cognitive function that coordinates the selection of visual stimuli with appropriate behavioral responses. Recent studies have reported that phase-amplitude coupling (PAC) of low and high frequencies covaries with spatial attention, but differ on the direction of covariation and the frequency ranges involved. We hypothesized that distinct phase-amplitude frequency pairs have differentiable contributions during tasks that manipulate spatial attention. We investigated this hypothesis with electrocorticography (ECoG) recordings from participants who engaged in a cued spatial attention task. To understand the contribution of PAC to spatial attention we classified cortical sites by their relationship to spatial variables or behavioral performance. Local neural activity in spatial sites was sensitive to spatial variables in the task, while local neural activity in behavioral sites correlated with reaction time. We found two PAC frequency clusters that covaried with different aspects of the task. During a period of cued attention, delta-phase/high-gamma (DH) PAC was sensitive to cue direction in spatial sites. In contrast, theta-alpha-phase/beta-low-gamma-amplitude (TABL) PAC robustly correlated with future reaction times in behavioral sites. Finally, we investigated the origins of TABL PAC and found it corresponded to behaviorally relevant, sharp waveforms, which were also coupled to a low frequency rhythm. We conclude that TABL and DH PAC correspond to distinct mechanisms during spatial attention tasks and that sharp waveforms are elements of a coupled dynamical process.

Contralesional Brain-Computer Interface Control of a Powered Exoskeleton for Motor Recovery in Chronic Stroke Survivors.

BACKGROUND AND PURPOSE: There are few effective therapies to achieve functional recovery from motor-related disabilities affecting the upper limb after stroke. This feasibility study tested whether a powered exoskeleton driven by a brain-computer interface (BCI), using neural activity from the unaffected cortical hemisphere, could affect motor recovery in chronic hemiparetic stroke survivors. This novel system was designed and configured for a home-based setting to test the feasibility of BCI-driven neurorehabilitation in outpatient environments. METHODS: Ten chronic hemiparetic stroke survivors with moderate-to-severe upper-limb motor impairment (mean Action Research Arm Test=13.4) used a powered exoskeleton that opened and closed the affected hand using spectral power from electroencephalographic signals from the unaffected hemisphere associated with imagined hand movements of the paretic limb. Patients used the system at home for 12 weeks. Motor function was evaluated before, during, and after the treatment. RESULTS: Across patients, our BCI-driven approach resulted in a statistically significant average increase of 6.2 points in the Action Research Arm Test. This behavioral improvement significantly correlated with improvements in BCI control. Secondary outcomes of grasp strength, Motricity Index, and the Canadian Occupational Performance Measure also significantly improved. CONCLUSIONS: The findings demonstrate the therapeutic potential of a BCI-driven neurorehabilitation approach using the unaffected hemisphere in this uncontrolled sample of chronic stroke survivors. They also demonstrate that BCI-driven neurorehabilitation can be effectively delivered in the home environment, thus increasing the probability of future clinical translation. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT02552368.

Frequency-specific electrophysiologic correlates of resting state fMRI networks.

Resting state functional MRI (R-fMRI) studies have shown that slow (<0.1Hz), intrinsic fluctuations of the blood oxygen level dependent (BOLD) signal are temporally correlated within hierarchically organized functional systems known as resting state networks (RSNs) (Doucet et al., 2011). Most broadly, this hierarchy exhibits a dichotomy between two opposed systems (Fox et al., 2005). One system engages with the environment and includes the visual, auditory, and sensorimotor (SMN) networks as well as the dorsal attention network (DAN), which controls spatial attention. The other system includes the default mode network (DMN) and the fronto-parietal control system (FPC), RSNs that instantiate episodic memory and executive control, respectively. Here, we test the hypothesis, based on the spectral specificity of electrophysiologic responses to perceptual vs. memory tasks (Klimesch, 1999; Pfurtscheller and Lopes da Silva, 1999), that these two large-scale neural systems also manifest frequency specificity in the resting state. We measured the spatial correspondence between electrocorticographic (ECoG) band-limited power (BLP) and R-fMRI correlation patterns in awake, resting, human subjects. Our results show that, while gamma BLP correspondence was common throughout the brain, theta (4-8Hz) BLP correspondence was stronger in the DMN and FPC, whereas alpha (8-12Hz) correspondence was stronger in the SMN and DAN. Thus, the human brain, at rest, exhibits frequency specific electrophysiology, respecting both the spectral structure of task responses and the hierarchical organization of RSNs.

Postoperative seizure freedom does not normalize altered connectivity in temporal lobe epilepsy.

OBJECTIVES: Specific changes in the functional connectivity of brain networks occur in patients with epilepsy. Yet whether such changes reflect a stable disease effect or one that is a function of active seizure burden remains unclear. Here, we longitudinally assessed the connectivity of canonical cognitive functional networks in patients with intractable temporal lobe epilepsy (TLE), both before and after patients underwent epilepsy surgery and achieved seizure freedom. METHODS: Seventeen patients with intractable TLE who underwent epilepsy surgery with Engel class I outcome and 17 matched healthy controls took part in the study. The functional connectivity of a set of cognitive functional networks derived from typical cognitive tasks was assessed in patients, preoperatively and postoperatively, as well as in controls, using stringent methods of artifact reduction. RESULTS: Preoperatively, functional networks in TLE patients differed significantly from healthy controls, with differences that largely, but not exclusively, involved the default mode and temporal/auditory subnetworks. However, undergoing epilepsy surgery and achieving seizure freedom did not lead to significant changes in network connectivity, with postoperative functional network abnormalities closely mirroring the preoperative state. SIGNIFICANCE: This result argues for a stable chronic effect of the disease on brain connectivity, with changes that are largely "burned in" by the time a patient with intractable TLE undergoes epilepsy surgery, which typically occurs years after the initial diagnosis. The result has potential implications for the treatment of intractable epilepsy, suggesting that delaying surgical intervention that may achieve seizure freedom may lead to functional network changes that are no longer reversible by the time of epilepsy surgery.

MRI-Guided Interstitial Laser Ablation for Intracranial Lesions: A Large Single-Institution Experience of 133 Cases.

BACKGROUND: Managing difficult-to-access lesions or surgically accessible lesions in fragile patients is a central problem in neurosurgery. MRI-guided interstitial laser ablation (ILA) is a minimally invasive option that may provide a safe means of treating these challenging patients. OBJECTIVE: We aim to (1) evaluate safety, efficacy, and preliminary outcomes within a diverse and large series of ILA treatments; and (2) report technical details and operative trends that proved useful over time in the authors' experience and that may be of use to neurosurgeons who perform ILA. METHODS: A retrospective evaluation of ILA patients was performed in terms of demographics, surgical techniques, and clinical outcomes. RESULTS: A total of 133 intracranial lesions in 120 patients were treated with ILA, including glioblastomas (GBM), other gliomas, metastases, epilepsy foci, and radionecrosis. The rate of complications/unexpected readmission was 6.0%, and the mortality rate was 2.2%. With high-grade tumors, tumor volumes >3 cm in diameter trended toward a higher rate of complication (p = 0.056). Median progression-free survival (PFS) and overall survival (OS) for recurrent GBM were 7.4 and 11.6 months, respectively. As a frontline treatment for newly diagnosed GBM, median PFS and OS were 5.9 and 11.4 months, respectively. For metastases, median PFS was not yet reached, and OS was 17.2 months. CONCLUSION: Our series suggests that ILA is a safe and efficacious treatment for a variety of intracranial pathologies, can be tailored to treat difficult-to-access lesions, and may offer a novel alternative to open craniotomy in properly selected patients.

Fast-scale network dynamics in human cortex have specific spectral covariance patterns.

Whether measured by MRI or direct cortical physiology, infraslow rhythms have defined state invariant cortical networks. The time scales of this functional architecture, however, are unlikely to be able to accommodate the more rapid cortical dynamics necessary for an active cognitive task. Using invasively monitored epileptic patients as a research model, we tested the hypothesis that faster frequencies would spectrally bind regions of cortex as a transient mechanism to enable fast network interactions during the performance of a simple hear-and-repeat speech task. We term these short-lived spectrally covariant networks functional spectral networks (FSNs). We evaluated whether spectrally covariant regions of cortex, which were unique in their spectral signatures, provided a higher degree of task-related information than any single site showing more classic physiologic responses (i.e., single-site amplitude modulation). Taken together, our results showing that FSNs are a more sensitive measure of task-related brain activation and are better able to discern phonemic content strongly support the concept of spectrally encoded interactions in cortex. Moreover, these findings that specific linguistic information is represented in FSNs that have broad anatomic topographies support a more distributed model of cortical processing.

Frequency-specific mechanism links human brain networks for spatial attention.

Selective attention allows us to filter out irrelevant information in the environment and focus neural resources on information relevant to our current goals. Functional brain-imaging studies have identified networks of broadly distributed brain regions that are recruited during different attention processes; however, the dynamics by which these networks enable selection are not well understood. Here, we first used functional MRI to localize dorsal and ventral attention networks in human epileptic subjects undergoing seizure monitoring. We subsequently recorded cortical physiology using subdural electrocorticography during a spatial-attention task to study network dynamics. Attention networks become selectively phase-modulated at low frequencies (δ, θ) during the same task epochs in which they are recruited in functional MRI. This mechanism may alter the excitability of task-relevant regions or their effective connectivity. Furthermore, different attention processes (holding vs. shifting attention) are associated with synchrony at different frequencies, which may minimize unnecessary cross-talk between separate neuronal processes.

Laser interstitial thermal therapy for subependymal giant cell astrocytoma: technical case report.

Subependymal giant cell astrocytoma (SEGA) is a rare tumor occurring almost exclusively in patients with tuberous sclerosis complex. Although open resection remains the standard therapy, complication rates remain high. To minimize morbidity, less invasive approaches, such as endoscope-assisted resection, radiosurgery, and chemotherapy with mTOR pathway inhibitors, are also used to treat these lesions. Laser interstitial thermal therapy (LITT) is a relatively new modality that is increasingly used to treat a variety of intracranial lesions. In this report, the authors describe two pediatric cases of SEGA that were treated with LITT. In both patients the lesion responded well to this treatment modality, with tumor shrinkage observed on follow-up MRI. These cases highlight the potential of LITT to serve as a viable minimally invasive therapeutic approach to the management of SEGAs in the pediatric population.

Utilizing personalized stereotactic frames for laser interstitial thermal ablation of posterior fossa and mesiotemporal brain lesions: a single-institution series.

OBJECTIVE The precision of laser probe insertion for interstitial thermal therapy of deep-seated lesions is limited by the method of stereotactic guidance. The objective of this study was to evaluate the feasibility of customized STarFix 3D-printed stereotactic platforms to guide laser probe insertion into mesiotemporal and posterior fossa targets. METHODS The authors conducted a retrospective review of 5 patients (12-55 years of age) treated with laser interstitial thermal therapy (LITT) in which STarFix platforms were used for probe insertion. Bone fiducials were implanted in each patient's skull, and subsequent CT scans were used to guide the design of each platform and incorporate desired treatment trajectories. Once generated, the platforms were mounted on the patients' craniums and used to position the laser probe during surgery. Placement of the laser probe and the LITT procedure were monitored with intraoperative MRI. Perioperative and follow-up MRI were performed to identify and monitor changes in target lesions. RESULTS Accurate placement of the laser probe was observed in all cases. For all patients, thermal ablation was accomplished without intraoperative complications. Of the 4 patients with symptomatic lesions, 2 experienced complete resolution of symptoms, and 1 reported improved symptoms compared with baseline. CONCLUSIONS Customized stereotactic platforms were seamlessly incorporated into the authors' previously established LITT workflow and allowed for accurate treatment delivery.

Resting-State Blood Oxygen Level-Dependent Functional MRI: A Paradigm Shift in Preoperative Brain Mapping.

Currently, functional magnetic resonance imaging (fMRI) facilitates a preoperative awareness of an association of an eloquent region with a tumor. This information gives the neurosurgeon helpful information that can aid in creating a surgical strategy. Typically, task-based fMRI has been employed to preoperatively localize speech and motor function. Task-based fMRI depends on the patient's ability to comply with the task paradigm, which often is impaired in the setting of a brain tumor. This problem is overcome by using resting-state fMRI (rs-fMRI) to localize function. rs-fMRI measures spontaneous fluctuations in the blood oxygen level-dependent (BOLD) signal, representing the brain's functional organization. In a neurosurgical context, it allows noninvasive simultaneous assessment of multiple large-scale distributed networks. Compared with task-related fMRI, rs-fMRI provides more comprehensive information on the functional architecture of the brain and is applicable in settings where task-related fMRI may provide inadequate information or could not be performed. Taken together, rs-fMRI substantially expands the preoperative mapping capability in efficiency, effectiveness, and scope. In this article, a brief introduction into rs-fMRI processing methods is followed by a detailed discussion on the role rs-fMRI plays in presurgical planning.