Whole-brain radiotherapy associated with structural changes resembling aging as determined by anatomic surface-based deep learning

BACKGROUND

Brain metastases are the most common intracranial tumors in adults and are associated with significant morbidity and mortality. Whole-brain radiotherapy (WBRT) is used frequently in patients for palliation, but can result in neurocognitive deficits. While dose-dependent injury to individual areas such as the hippocampus has been demonstrated, global structural shape changes after WBRT remain to be studied.

METHODS

We studied healthy controls and patients with brain metastases and examined MRI brain anatomic surface data before and after WBRT. We implemented a validated graph convolutional neural network model to estimate patient's "brain age". We further developed a mixed-effects linear model to compare the estimated age of the whole brain and substructures before and after WBRT.

RESULTS

4220 subjects were analyzed (4148 healthy controls and 72 patients). The median radiation dose was 30 Gy (range 25-37.5 Gy). The whole brain and substructures underwent structural change resembling rapid aging in radiated patients compared to healthy controls; the whole brain "aged" 9.32 times faster, the cortex 8.05 times faster, the subcortical structures 12.57 times faster, and the hippocampus 10.14 times faster. In a subset analysis, the hippocampus "aged" 8.88 times faster in patients after conventional WBRT versus after hippocampal avoidance (HA)-WBRT.

CONCLUSIONS

Our findings suggest that WBRT causes the brain and its substructures to undergo structural changes at a pace up to 13x of the normal aging pace, where hippocampal avoidance offers focal structural protection. Correlating these structural imaging changes with neurocognitive outcomes following WBRT or HA-WBRT would benefit from future analysis.

A multicohort geometric deep learning study of age dependent cortical and subcortical morphologic interactions for fluid intelligence prediction

The relationship of human brain structure to cognitive function is complex, and how this relationship differs between childhood and adulthood is poorly understood. One strong hypothesis suggests the cognitive function of Fluid Intelligence (Gf) is dependent on prefrontal cortex and parietal cortex. In this work, we developed a novel graph convolutional neural networks (gCNNs) for the analysis of localized anatomic shape and prediction of Gf. Morphologic information of the cortical ribbons and subcortical structures was extracted from T1-weighted MRIs within two independent cohorts, the Adolescent Brain Cognitive Development Study (ABCD; age: 9.93 ± 0.62 years) of children and the Human Connectome Project (HCP; age: 28.81 ± 3.70 years). Prediction combining cortical and subcortical surfaces together yielded the highest accuracy of Gf for both ABCD (R = 0.314) and HCP datasets (R = 0.454), outperforming the state-of-the-art prediction of Gf from any other brain measures in the literature. Across both datasets, the morphology of the amygdala, hippocampus, and nucleus accumbens, along with temporal, parietal and cingulate cortex consistently drove the prediction of Gf, suggesting a significant reframing of the relationship between brain morphology and Gf to include systems involved with reward/aversion processing, judgment and decision-making, motivation, and emotion.

Meningeal defects and focal cortical dysplasia: an unrecognized relationship? Illustrative case

BACKGROUND

Focal cortical dysplasias (FCDs) are a heterogenous cluster of histopathologic entities classically associated with medically refractory epilepsy. Because there is substantial histopathologic variation among different types of FCD, there are likely multiple pathogenic mechanisms leading to these disorders. The meninges are known to play a role in cortical development, and disruption of meningeal-derived signaling pathways has been shown to impact neurodevelopment. To our knowledge, there has not yet been an investigation into whether genetic pathways regulating meningeal development may be involved in the development of FCD.

OBSERVATIONS

The authors reported a patient with refractory epilepsy and evidence of FCD on imaging who received surgical intervention and was found to have an unusual dural anomaly overlying a region of type Ic FCD. To the authors’ knowledge, this was the first report describing a lesion of this nature in the context of FCD.

LESSONS

The dural anomaly exhibited by the patient presented what could be a potentially novel pathogenic mechanism of FCD. Resection of the cortical tissue underlying the dural anomaly resulted in improvement in seizure control. Although the pathogenesis is unclear, this case highlighted the importance of further investigation into the developmental origins of FCD, which may help elucidate whether a connection between meningeal development and FCD exists.

Geometric deep learning reveals a structuro-temporal understanding of healthy and pathologic brain aging

Background

Brain age has historically been investigated primarily at the whole brain level. The ability to deconstruct the brain into its composite parts and explore brain age at the sub-structure level offers unique advantages. These include the exploration of dynamic and interconnected relationships between different brain structures in healthy and pathologic aging. To achieve this, individual brain structures can be rendered as surface representations on which morphologic analysis is carried out. Combining the advantages of deep learning with the strengths of surface analysis, we investigate the aging process at the individual structure level with the hypothesis being that pathologic aging does not uniformly affect the aging process of individual structures.

Methods

MRI data, age at scan time and diagnosis of dementia were collected from seven publicly available data repositories. The data from 17,440 unique subjects were collected, representing a total of 26,276 T1-weighted MRI accounting for longitudinal acquisitions. Surfaces were extracted for the cortex and seven subcortical structures. Deep learning networks were trained to estimate a subject's age either using several structures together or a single structure. We conducted a cross-sectional analysis to assess the difference between the predicted and actual ages for all structures between healthy subjects, individuals with mild cognitive impairment (MCI) or Alzheimer's disease dementia (ADD). We then performed a longitudinal analysis to assess the difference in the aging pace for each structure between stable healthy controls and healthy controls converting to either MCI or ADD.

Findings

Using an independent cohort of healthy subjects, age was well estimated for all structures. Cross-sectional analysis identified significantly larger predicted age for all structures in patients with either MCI and ADD compared to healthy subjects. Longitudinal analysis revealed varying degrees of involvement of individual subcortical structures for both age difference across groups and aging pace across time. These findings were most notable in the whole brain, cortex, hippocampus and amygdala.

Conclusion

Although similar patterns of abnormal aging were found related to MCI and ADD, the involvement of individual subcortical structures varied greatly and was consistently more pronounced in ADD patients compared to MCI patients.

Whole brain radiotherapy and association with rapid brain aging as determined by anatomic surface morphology

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Background: Brain metastases are the most common intracranial tumors in adults and are associated with significant morbidity and mortality. Whole brain radiotherapy (WBRT) is used frequently in patients for palliation, but can result in neurocognitive deficits. While dose-dependent injury to individual areas such as the hippocampus have been demonstrated, global structural changes after WBRT remain to be studied. Our group previously published a magnetic resonance imaging (MRI) deep learning model based on anatomic brain surface morphology to accurately predict brain age in healthy subjects. We now report the effect of WBRT on aging pace of the irradiated brain. Methods: We studied patients with brain metastases and examined MRI brain anatomic surface data before and after WBRT. We implemented a graph convolutional neural network model to estimate patient’s brain age. We further developed a mixed-effects linear model to compare age of whole brain and substructures before and after WBRT, written as follows: ΔAge = c + β(ΔScan) + 1|patient_ID; where for each patient, ΔAge = [(model_predicted_age_at_follow up – actual_age_at_follow up) – (model_predicted_age_pre_treatment – actual_age_pre_treatment)], ΔScan = time interval between pre-and post-treatment MRI scans, β = aging coefficient (β =0 corresponds to normal aging), and c = intercept (model_predicted_age_pre_treatment – actual_age_pre_treatment). Results: 56 patients were analyzed. The median age was 62 (range 32 – 85). Two-thirds of patients were female. Primary organ site was breast or lung in 87% of cases and 77% of patients had five or more metastases. Median radiation dose was 30Gy (range 25 – 37.5Gy). Results of aging analysis are presented in Table. Small c values demonstrate that model accurately predicted age pre-treatment. The whole brain and substructures underwent rapid aging compared to normal aging pace (β>>0). Based on median follow up of 6.3 months, the whole brain aged approximately 4.94 years, the cortex aged approximately 4.53 years, the subcortical structures aged approximately 5.94 years, and the hippocampus aged approximately 5.17 years. Conclusions: Our findings suggest that WBRT causes the brain and its substructures to age at a pace of 9-11x of the normal aging pace, mirroring deficits in long-term neurocognition seen post-treatment. Given post-treatment aging pace and increasing survival for many patients with brain metastases, WBRT needs to be used judiciously. [Table: see text]

Patient-Specific Characteristics Associated with Favorable Response to Vagus Nerve Stimulation

OBJECTIVE

The expansion in treatments for medically refractory epilepsy heightens the importance of identifying patients who are likely to benefit from vagus nerve stimulation (VNS). Here, we identify predictors with a positive VNS response.

METHODS

We present a retrospective analysis of 158 patients with medically refractory epilepsy. Patients were categorized as VNS responders or nonresponders. Baseline characteristics and time to VNS response were recorded. Univariate and multivariate Cox regression were used to identify predictors of response. Recursive partitioning analysis was used to identify likely VNS responders.

RESULTS

Eighty-nine (56.3%) patients achieved ≥50% seizure frequency reduction. Left-hand dominance (hazard ratio [HR] 1.703, P = 0.038), age at epilepsy onset ≥15 years (HR 2.029, P = 0.005), duration of epilepsy ≥8 years (HR 1.968, P = 0.007) and age at implantation ≥35 years (HR 1.809, P = 0.020), and baseline seizure frequency <5/month (HR 1.569, P = 0.044) were significant univariate predictors of VNS response. Following multivariate Cox regression, left-hand dominance, age at epilepsy onset ≥15 years, and duration of epilepsy ≥8 years remained significant. With recursive partitioning analysis, patients with either age at epilepsy onset ≥15 years, left-hand dominance, or baseline seizure frequency <5/month were stratified into Group A and had a 73.9% responder rate; the remaining patients stratified into Group B had a 43.8% responder rate.

CONCLUSIONS

Patients with age at epilepsy onset ≥15 years, left-hand dominance, or baseline seizure frequency <5/month are ideal candidates for VNS.

Geometric deep learning on brain shape predicts sex and age

The complex relationship between the shape and function of the human brain remains elusive despite extensive studies of cortical folding over many decades. The analysis of cortical gyrification presents an opportunity to advance our knowledge about this relationship, and better understand the etiology of a variety of pathologies involving diverse degrees of cortical folding abnormalities. Hypothesis-driven surface-based approaches have been shown to be particularly efficient in their ability to accurately describe unique features of the folded sheet topology of the cortical ribbon. However, the utility of these approaches has been blunted by their reliance on manually defined features aiming to capture the relevant geometric properties of cortical folding. In this paper, we propose an entirely novel, data-driven deep-learning based method to analyze the brain's shape that eliminates this reliance on manual feature definition. This method builds on the emerging field of geometric deep-learning and uses traditional convolutional neural network architecture uniquely adapted to the surface representation of the cortical ribbon. This method is a complete departure from prior brain MRI CNN investigations, all of which have relied on three dimensional MRI data and interpreted features of the MRI signal for prediction. MRI data from 6410 healthy subjects obtained from 11 publicly available data repositories were used for analysis. Ages ranged from 6 to 89 years. Both inner and outer cortical surfaces were extracted using Freesurfer and then registered into MNI space. For purposes of method development, both a classification and regression challenge were introduced for network learning including sex and age prediction, respectively. Two independent graph convolutional neural networks (gCNNs) were trained, the first of which to predict subject's self-identified sex, the second of which to predict subject's age. Class Activation Maps (CAM) and Regression Activation Maps (RAM) were constructed respectively to map the topographic distribution of the most influential brain regions involved in the decision process for each gCNN. Using this approach, the gCNN was able to predict a subject's sex with an average accuracy of 87.99 % and achieved a Person's coefficient of correlation of 0.93 with an average absolute error 4.58 years when predicting a subject's age. We believe this shape-based convolutional classifier offers a novel, data-driven approach to define biomedically relevant features from the brain at both the population and single subject levels and therefore lays a critical foundation for future precision medicine applications.

Interpretation of Brain Morphology in Association to Alzheimer's Disease Dementia Classification Using Graph Convolutional Networks on Triangulated Meshes

We propose a mesh-based technique to aid in the classification of Alzheimer's disease dementia (ADD) using mesh representations of the cortex and subcortical structures. Deep learning methods for classification tasks that utilize structural neuroimaging often require extensive learning parameters to optimize. Frequently, these approaches for automated medical diagnosis also lack visual interpretability for areas in the brain involved in making a diagnosis. This work: (a) analyzes brain shape using surface information of the cortex and subcortical structures, (b) proposes a residual learning framework for state-of-the-art graph convolutional networks which offer a significant reduction in learnable parameters, and (c) offers visual interpretability of the network via class-specific gradient information that localizes important regions of interest in our inputs. With our proposed method leveraging the use of cortical and subcortical surface information, we outperform other machine learning methods with a 96.35% testing accuracy for the ADD vs. healthy control problem. We confirm the validity of our model by observing its performance in a 25-trial Monte Carlo cross-validation. The generated visualization maps in our study show correspondences with current knowledge regarding the structural localization of pathological changes in the brain associated to dementia of the Alzheimer's type.

Completion Corpus Callosotomy with Stereotactic Radiosurgery for Drug-Resistant, Intractable Epilepsy

BACKGROUND

Stereotactic radiosurgery (SRS) offers a noninvasive technique for division of the corpus callosum, which can confer improved seizure control to patients suffering from frequent atonic seizures due to rapid interhemispheric generalization. This noninvasive approach is well-suited for use in a palliative intervention for improved seizure control in this patient population. To our knowledge, this is the first report of radiosurgical completion corpus callosotomy in an adult in the United States.

CASE DESCRIPTION

A 20-year-old ambidextrous nonverbal man with a history of refractory generalized epilepsy status post open anterior corpus callosotomy at age 10 years, Lennox-Gastaut syndrome, and autism presented after 2 years of incremental, progressive deterioration in seizure control and behavior including 1 year. The family decided to pursue SRS corpus callosotomy. Under general anesthesia, a volume of interest encompassing a full midsagittal plane of the corpus callosum was defined to deliver 60 Gy to the 50% isodose line fully encompassing the target. Gamma Knife was used with 2 isocenters at 90° and 1 at 110° and isodose lines of 60, 20, and 12 Gy. Treatment was carried out without difficulty or complications while the patient remained under close monitoring. The patient was discharged the next day with a 2-week taper of dexamethasone.

CONCLUSIONS

Eight months postradiosurgical corpus callosotomy, the patient is free of atonic seizures and is ambulatory. In carefully selected cases and with protective radiosurgical planning, SRS for completion corpus callosotomy represents an effective option for refractory seizure control.

Epilepsy Surgery in Children Under Three Years of Age

Researchers from the University Medical Centre Schleswig-Holstein, Epilepsy Centre Kork, University of Freiburg, University Children’s Hospital Heidelberg, Goethe University, and University Children’s Hospital Zürich conducted a study to evaluate seizure occurrence and cognitive development following epilepsy surgery in children under 3 years of age.

Connectivity strength, time lag structure and the epilepsy network in resting-state fMRI

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Stereo-encephalography informed high-resolution functional connectome analysis on the nodal and whole brain levels identifies consistent patterns of altered correlation strength and altered time lag architecture in epilepsy patients compared to controls.

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Specific patterns of altered connectivity include:.○

broadly distributed increased strength of correlation between the seizure onset node and the remainder of the brain.

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decreased time lag within the seizure onset node.

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globally increased time lag throughout all regions of the brain not involved in seizure onset or propagation.

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Comparing the topographic distribution of findings against a functional atlas, all resting state networks were involved to a variable degree. These local and whole brain findings presented here lead us to propose the network steal hypothesis as a possible mechanistic explanation for the non-seizure clinical manifestations of epilepsy.

The relationship between the epilepsy network, intrinsic brain networks and hypersynchrony in epilepsy remains incompletely understood. To converge upon a synthesized understanding of these features, we studied two elements of functional connectivity in epilepsy: correlation and time lag structure using resting state fMRI data from both SEEG-defined epileptic brain regions and whole-brain fMRI analysis. Functional connectivity (FC) was analyzed in 15 patients with epilepsy and 36 controls. Correlation strength and time lag were selected to investigate the magnitude of and temporal interdependency across brain regions. Zone-based analysis was carried out investigating directed correlation strength and time lag between both SEEG-defined nodes of the epilepsy network and between the epileptogenic zone and all other brain regions. Findings were compared between patients and controls and against a functional atlas. FC analysis on the nodal and whole brain levels identifies consistent patterns of altered correlation strength and altered time lag architecture in epilepsy patients compared to controls. These patterns include 1) broadly distributed increased strength of correlation between the seizure onset node and the remainder of the brain, 2) decreased time lag within the seizure onset node, and 3) globally increased time lag throughout all regions of the brain not involved in seizure onset or propagation. Comparing the topographic distribution of findings against a functional atlas, all resting state networks were involved to a variable degree. These local and whole brain findings presented here lead us to propose the network steal hypothesis as a possible mechanistic explanation for the non-seizure clinical manifestations of epilepsy.

Clinical Integration of Quantitative Susceptibility Mapping Magnetic Resonance Imaging into Neurosurgical Practice

OBJECTIVE

To introduce quantitative susceptibility mapping (QSM), a novel magnetic resonance imaging sequence, to the field of neurosurgery.

METHODS

QSM is introduced both in its historical context and by providing a brief overview of the physics behind the technique tailored to a neurosurgical audience. Its application to clinical neurosurgery is then highlighted using case examples.

RESULTS

QSM offers a quantitative assessment of susceptibility (previously considered as an artifact) via a single, straightforward gradient echo acquisition. QSM differs from standard susceptibility weighted imaging in its ability to both quantify and precisely localize susceptibility effects. Clinical applications of QSM are wide reaching and include precise localization of the deep nuclei for deep brain stimulation electrode placement, differentiation between blood products and calcification within brain lesions, and enhanced sensitivity of cerebral micrometastasis identification.

CONCLUSIONS

We present this diverse range of QSM's clinical applications to neurosurgical care via case examples. QSM can be obtained in all patients able to undergo magnetic resonance imaging and is easily integratable into busy neuroradiology programs because of its short acquisition time and straightforward, automated offline postprocessing workflow. Clinical integration of QSM may help clinicians better identify and characterize neurosurgical lesions, thereby improving patient care.

The impact of high grade glial neoplasms on human cortical electrophysiology

Objective

The brain’s functional architecture of interconnected network-related oscillatory patterns in discrete cortical regions has been well established with functional magnetic resonance imaging (fMRI) studies or direct cortical electrophysiology from electrodes placed on the surface of the brain, or electrocorticography (ECoG). These resting state networks exhibit a robust functional architecture that persists through all stages of sleep and under anesthesia. While the stability of these networks provides a fundamental understanding of the organization of the brain, understanding how these regions can be perturbed is also critical in defining the brain’s ability to adapt while learning and recovering from injury.

Methods

Patients undergoing an awake craniotomy for resection of a tumor were studied as a unique model of an evolving injury to help define how the cortical physiology and the associated networks were altered by the presence of an invasive brain tumor.

Results

This study demonstrates that there is a distinct pattern of alteration of cortical physiology in the setting of a malignant glioma. These changes lead to a physiologic sequestration and progressive synaptic homogeneity suggesting that a de-learning phenomenon occurs within the tumoral tissue compared to its surroundings.

Significance

These findings provide insight into how the brain accommodates a region of “defunctionalized” cortex. Additionally, these findings may have important implications for emerging techniques in brain mapping using endogenous cortical physiology.

Whole-Brain High-Resolution Structural Connectome: Inter-Subject Validation and Application to the Anatomical Segmentation of the Striatum

The present study describes extraction of high-resolution structural connectome (HRSC) in 99 healthy subjects, acquired and made available by the Human Connectome Project. Single subject connectomes were then registered to the common surface space to allow assessment of inter-individual reproducibility of this novel technique using a leave-one-out approach. The anatomic relevance of the surface-based connectome was examined via a clustering algorithm, which identified anatomic subdivisions within the striatum. The connectivity of these striatal subdivisions were then mapped on the cortical and other subcortical surfaces. Findings demonstrate that HRSC analysis is robust across individuals and accurately models the actual underlying brain networks related to the striatum. This suggests that this method has the potential to model and characterize the healthy whole-brain structural network at high anatomic resolution.

Reverberation index: a novel metric by which to quantify the impact of a scientific entity on a given field

The authors propose a novel bibilometric index, the reverberation index (r-index), as a comparative assessment tool for use in determining differential reverberation between scientific fields for a given scientific entity. Conversely, this may allow comparison of 2 similar scientific entities within a single scientific field. This index is calculated using a relatively simple 3-step process. Briefly, Thompson Reuters' Web of Science is used to produce a citation report for a unique search parameter (this may be an author, journal article, or topical key word). From this citation report, a list of citing journals is retrieved from which a weighted ratio of citation patterns across journals can be calculated. This r-index is then used to compare the reverberation of the original search parameter across different fields of study or wherever a comparison is required. The advantage of this novel tool is its ability to transcend a specific component of the scientific process. This affords application to a diverse range of entities, including an author, a journal article, or a topical key word, for effective comparison of that entity's reverberation within a scientific arena. The authors introduce the context for and applications of the r-index, emphasizing neurosurgical topics and journals for illustration purposes. It should be kept in mind, however, that the r-index is readily applicable across all fields of study.

Resting state functional connectivity magnetic resonance imaging integrated with intraoperative neuronavigation for functional mapping after aborted awake craniotomy

BACKGROUND

Awake craniotomy is currently the gold standard for aggressive tumor resections in eloquent cortex. However, a significant subset of patients is unable to tolerate this procedure, particularly the very young or old or those with psychiatric comorbidities, cardiopulmonary comorbidities, or obesity, among other conditions. In these cases, typical alternative procedures include biopsy alone or subtotal resection, both of which are associated with diminished surgical outcomes.

CASE DESCRIPTION

Here, we report the successful use of a preoperatively obtained resting state functional connectivity magnetic resonance imaging (MRI) integrated with intraoperative neuronavigation software in order to perform functional cortical mapping in the setting of an aborted awake craniotomy due to loss of airway.

CONCLUSION

Resting state functional connectivity MRI integrated with intraoperative neuronavigation software can provide an alternative option for functional cortical mapping in the setting of an aborted awake craniotomy.

Congenital Acute Myeloid Leukemia with Unique Translocation t(11;19)(q23;p13.3)

Congenital leukemia is rarely encountered in clinical practice, even in tertiary children's hospitals. Leukemia may cause significant coagulopathy, putting the patient at risk of intracranial hemorrhage. In this case, the authors present a female infant with a unique mixed phenotypic congenital acute myeloid leukemia showing mixed-lineage leukemia (MLL) rearrangement and severe coagulopathy resulting in a large subdural hematoma. Despite the fatal outcome in this case, neurosurgical treatment of patients with acute myeloid leukemia should be considered if coagulopathy and the clinical scenario allow.

Laser ablation as treatment strategy for medically refractory dominant insular epilepsy: therapeutic and functional considerations

Since its introduction to neurosurgery in 2008, laser ablative techniques have been largely confined to the management of unresectable tumors. Application of this technology for the management of focal epilepsy in the adult population has not been fully explored. Given that nearly 1,000,000 Americans live with medically refractory epilepsy and current surgical techniques only address a fraction of epileptic pathologies, additional therapeutic options are needed. We report the successful treatment of dominant insular epilepsy in a 53-year-old male with minimally invasive laser ablation complicated by mild verbal and memory deficits. We also report neuropsychological test data on this patient before surgery and at 8 months after the ablation procedure. This account represents the first reported successful patient outcome of laser ablation as an effective treatment option for medically refractory post-stroke epilepsy in an adult.

Trans-middle temporal gyrus selective amygdalohippocampectomy for medically intractable mesial temporal lobe epilepsy in adults: seizure response rates, complications, and neuropsychological outcomes

OBJECTIVE

Selective amygdalohippocampectomy (AHC) has evolved to encompass a variety of techniques to resect the mesial temporal lobe. To date, there have been few large-scale evaluations of trans-middle temporal gyrus selective AHC. The authors examine a large series of patients who have undergone the trans-middle temporal gyrus AHC and assess its clinical and neuropsychological impact.

METHODS

A series of 76 adult patients underwent selective AHC via the trans-middle temporal gyrus approach over a 10-year period, 19 of whom underwent pre- and postoperative neuropsychological evaluations.

RESULTS

Favorable seizure response rates were achieved (92% Engel class I or II), with very low surgical morbidity and no mortality. Postoperative neuropsychological assessment revealed a decline in verbal memory for the left AHC group. No postoperative memory decline was identified for the right AHC group, but rather some improvements were noted within this group.

CONCLUSIONS

The trans-middle temporal gyrus selective AHC is a safe and effective choice for management of medically refractory epilepsy in adults.

Management of pediatric intracranial gunshot wounds: predictors of favorable clinical outcome and a new proposed treatment paradigm

OBJECT

There has been an increase in civilian gun violence since the late 1980s, with a disproportionately high increase occurring within the pediatric population. To date, no definite treatment paradigm exists for the management of these patients, nor is there a full understanding of the predictors of favorable clinical outcome in this population.

METHODS

The authors completed a retrospective review of all victims of intracranial gunshot injury from birth to age 18 years at a major metropolitan Level 1 trauma center (n = 48) from 2002 to 2011. The predictive values of widely accepted adult clinical and radiographic factors for poor prognosis were investigated.

RESULTS

Eight statistically significant factors (p < 0.05) for favorable outcome were identified. These factors include single hemispheric involvement, absence of a transventricular trajectory, < 3 lobes involved, ≥ 1 reactive pupil on arrival, systolic blood pressure > 100 mm Hg on arrival, absence of deep nuclei and/or third ventricular involvement, initial ICP < 30 mm Hg when monitored, and absence of midline shift. Of these 8 factors, 5 were strong predictors of favorable clinical outcome as defined by Glasgow Outcome Scale score of 4 or 5. These predictive factors included absence of a transventricular trajectory, < 3 lobes involved, ≥ 1 reactive pupil on arrival, absence of deep nuclei and/or third ventricular involvement, and initial ICP < 30 mm Hg. These findings form the basis of the St. Louis Scale for Pediatric Gunshot Wounds to the Head, a novel metric to inform treatment decisions for pediatric patients who sustain these devastating injuries.

CONCLUSIONS

The pediatric population tends to demonstrate more favorable outcomes following intracranial gunshot injury when compared with the adult population; therefore some patients may benefit from more aggressive treatment than is considered for adults. The St. Louis Scale for Pediatric Gunshot Wounds to the Head may provide critical data toward evidence-based guidelines for clinical decision making.

Association of magnetic resonance imaging identification of mesial temporal sclerosis with pathological diagnosis and surgical outcomes in children following epilepsy surgery

OBJECT

Mesial temporal sclerosis (MTS) is widely recognized as a significant underlying cause of temporal lobe epilepsy. Magnetic resonance imaging is routinely used in the preoperative evaluation of children with epilepsy. The purpose of this study was to evaluate the prevalence, reliability, and prognostic value of MRI identification of MTS and MRI findings indicative of MTS in a series of patients who underwent resection of the medial temporal lobe for medically refractory epilepsy.

METHODS

The authors reviewed the medical records and preoperative MRI reports of 25 patients who had undergone medial temporal resections (anterior temporal lobectomy or functional hemispherotomy) for medically intractable epilepsy. The preoperative MRI studies were presented for blinded review by 2 neuroradiologists who independently evaluated the radiographs for selected MTS features and provided a final interpretation. To quantify interrater agreement and accuracy, the findings of the 2 blinded neuroradiologists, the nonblinded clinical preoperative radiology report, and the final pathology interpretation were compared.

RESULTS

The preoperative MRI studies revealed MTS in 6 patients (24%), and histopathological analysis verified MTS in 8 (32%) of 25 specimens. Six MRI features of MTS were specifically evaluated: 1) increased hippocampal signal intensity, 2) reduced hippocampal size, 3) atrophy of the ipsilateral hippocampal collateral white matter, 4) enlarged ipsilateral temporal horn, 5) reduced gray-white matter demarcation in the temporal lobe, and 6) decreased temporal lobe size. The most prevalent feature of MTS identified on MRI was a reduced hippocampal size, found in 11 of the MRI studies (44%). Analysis revealed moderate interrater agreement for MRI identification of MTS between the 2 blinded neuroradiologists and the nonblinded preoperative report (Cohen κ 0.40-0.59). Interrater agreement was highly variable for different MTS features indicative of MTS, ranging from poor to near perfect. Agreement was highest for increased hippocampal signal and decreased temporal lobe size and was consistently poor for reduced gray-white matter demarcation. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and proportion perfect agreement were highest for increased hippocampal signal and reduced hippocampal size. An MRI finding of MTS was not predictive of seizure outcome in this small series.

CONCLUSIONS

Mesial temporal sclerosis identification on brain MRI in children evaluated for medial temporal resections has a PPV of 55%-67% and an NPV of 79%-87%. Increased hippocampal signal and reduced hippocampal size were associated with high predictive values, while gray-white differentiation and an enlarged temporal horn were not predictive of MTS. Seizure outcome following medial temporal resections was not associated with MRI findings of MTS or MRI abnormalities indicative of MTS in this small sample size.

Preventing cerebrospinal fluid leak following transection of a tight filum terminale

OBJECT

Tethered cord release for a tight filum terminale is a common pediatric operation associated with low morbidity and mortality rates. While almost all would agree that keeping patients lying flat after the operation will prevent a CSF leak, the optimal period of doing so has not been determined. In this study, the authors examined whether a longer length of stay in the hospital for the sole purpose of maintaining patients flat correlates with a decreased rate of CSF leakage.

METHODS

Intraoperative and postoperative data were retrospectively collected in 222 cases of simple tethered cord release at 3 large children's hospitals. Risk factors for postoperative CSF leakage were identified.

RESULTS

Thirty-eight patients were maintained lying flat for 24 hours, 86 for 48 hours, and 98 for 72 hours at the individual surgeon's discretion. A CSF leak occurred in 13 patients (5.9%) and pseudomeningocele developed in 9 patients (4.1%). In the univariate analysis, operating time, use of the microscope, use of dural sealant, and duration of remaining flat after surgery failed to correlate with the occurrence of complications.

CONCLUSIONS

A longer hospital stay for maintaining patients flat after a simple tethered cord release appears not to prevent CSF leakage. However, a larger patient cohort will be needed to detect small differences in complication rates.

Deep brain stimulation as an effective treatment option for post–midbrain infarction-related tremor as it presents with Benedikt syndrome

Benedikt syndrome is a rare but debilitating constellation of symptoms that manifests from infarction of the red nucleus, cerebral peduncle, oculomotor fascicles, and lower oculomotor nucleus. Clinically, it presents as ipsilateral cranial nerve III palsy, contralateral hemiataxia with intention tremor, contralateral hemiparesis, and hyperactive tendon reflexes. Commonly, the tremor upon purposeful movement proves to be the most debilitating manifestation of the infarction with significant impact on the patient's ability to perform activities of daily living and, therefore, quality of life. The authors report the successful management of this debilitating post–midbrain infarction tremor with the insertion of a deep brain stimulator with targets in the contralateral lenticular fasciculus.