Reducing the Cognitive Footprint of Brain Tumor Surgery

Towards Optical Biopsy in Glioma Surgery

Currently, the focus of intraoperative imaging in brain tumor surgery is beginning to shift to optical methods such as optical coherence tomography (OCT), Raman spectroscopy, confocal laser endomicroscopy (CLE), and fluorescence lifetime imaging (FLIM). Optical imaging technologies provide in vivo and real-time high-resolution images of tissues. "Optical biopsy" can be considered as an alternative to traditional approaches for intraoperative histopathologic consultation. Intraoperative optical imaging can help to achieve precise intraoperative identification of tumor infiltrations within the surrounding brain parenchyma. Therefore, it can be considered as a complement to existing approaches based on wide-field imaging modalities such as MRI, US, or 5-ALA fluorescence. A promising future direction for intraoperative guidance during brain tumor surgery or stereotactic biopsy lies in the integration of optical imaging with machine learning techniques, enabling automated differentiation between tumor tissue and healthy brain parenchyma. We present this review to increase knowledge and form critical opinions in the field of using optical imaging in brain tumor surgery.

Enhancing brain tumor surgery precision with multimodal connectome imaging: Structural and functional connectivity in language-dominant areas

OBJECTIVES

Language is a critical aspect of human cognition and function, and its preservation is a priority for neurosurgical interventions in the left frontal operculum. However, identification of language areas can be inconsistent, even with electrical mapping. The use of multimodal structural and functional neuroimaging in conjunction with intraoperative neuromonitoring may augment cortical language area identification to guide the resection of left frontal opercular lesions.

METHODS

Structural and functional connectome scans were generated using a machine learning software to reparcellate a validated schema of the Human Connectome Project Multi-Modal Parcellation (HCP-MMP) atlas based on individual structural and functional connectivity identified through anatomic, diffusion, and resting-state functional MRI (rs-fMRI). Structural connectivity imaging was analyzed to determine at-risk parcellations and seed-based analysis of regions of interest (ROIs) was performed to identify functional relationships.

RESULTS

Two patients with left frontal lesions were analyzed, one with a WHO Grade IV gliosarcoma, and the other with an intracerebral abscess. Individual patterns of functional connectivity were identified by functional neuroimaging revealing distinct relationships between language network parcellations. Multimodal, connectome-guided resections with intraoperative neuromonitoring were performed, with both patients demonstrating intact or improved language function relative to baseline at follow-up. Follow-up imaging demonstrated functional reorganization observed between Brodmann areas 44 and 45 and other parcellations of the language network.

CONCLUSION

Preoperative visualization of structural and functional connectivity of language areas can be incorporated into a multimodal operative approach with intraoperative neuromonitoring to facilitate the preservation of language areas during intracranial neurosurgery. These modalities may also be used to monitor functional recovery.

Connectome imaging to facilitate preservation of the frontal aslant tract

Supplementary motor area (SMA) syndrome is characterized by contralateral akinesia and mutism, and frequently occurs following resection of tumors involving the superior frontal gyrus. The frontal aslant tract (FAT), involved in functional connectivity of the supplementary area and other related large-scale brain networks, is implicated in the pathogenesis of, and recovery from, SMA syndrome. However, intraoperative neuromonitoring of the FAT is inconsistent and poorly reproducible, leading to a high rate of postoperative SMA syndrome. We report the cases of two patients harboring lesions of the superior frontal gyrus: one cavernoma and one low grade glioma. Connectome imaging revealed involvement of functional networks implicated in SMA syndrome, as well as displacement of the FAT. A connectome-guided awake craniotomy was performed in both cases, and a combinatorial approach using awake language mapping and connectome-imaging guidance facilitated gross total resection of both patient's lesions without inducing SMA syndrome postoperatively. Functional and structural connectivity imaging through connectomics allows the identification of areas not traditionally considered eloquent, such as the SMA and FAT, and can help facilitate their preservation. Conserving the functional and structural connectivity of broader brain regions that are not traditionally deemed eloquent can improve patient outcomes.

Multilayer Network Analysis across Cortical Depths in Resting-State 7T fMRI

In graph theory, "multilayer networks" represent systems involving several interconnected topological levels. One example in neuroscience is the stratification of connections between different cortical depths or "laminae", which is becoming non-invasively accessible in humans using ultra-high-resolution functional MRI (fMRI). Here, we applied multilayer graph theory to examine functional connectivity across different cortical depths in humans, using 7T fMRI (1-mm3 voxels; 30 participants). Blood oxygenation level dependent (BOLD) signals were derived from five depths between the white matter and pial surface. We compared networks where the inter-regional connections were limited to a single cortical depth only ("layer-by-layer matrices") to those considering all possible connections between areas and cortical depths ("multilayer matrix"). We utilized global and local graph theory features that quantitatively characterize network attributes including network composition, nodal centrality, path-based measures, and hub segregation. Detecting functional differences between cortical depths was improved using multilayer connectomics compared to the layer-by-layer versions. Superficial depths of the cortex dominated information transfer and deeper depths drove clustering. These differences were largest in frontotemporal and limbic regions. fMRI functional connectivity across different cortical depths may contain neurophysiologically relevant information; thus, multilayer connectomics could provide a methodological framework for studies on how information flows across this stratification.

Intraoperative glioblastoma surgery-current challenges and clinical trials: An update

Surgical excision is an important part of the multimodal therapy strategy for patients with glioblastoma, a very aggressive and invasive brain tumor. While major advances in surgical methods and technology have been accomplished, numerous hurdles remain in the field of glioblastoma surgery. The purpose of this literature review is to offer a thorough overview of the current challenges in glioblastoma surgery. We reviewed the difficulties associated with tumor identification and visualization, resection extent, neurological function preservation, tumor margin evaluation, and inclusion of sophisticated imaging and navigation technology. Understanding and resolving these challenges is critical in order to improve surgical results and, ultimately, patient survival.

Utilizing machine learning to tailor radiotherapy and chemoradiotherapy for low-grade glioma patients

BACKGROUND

There is ongoing uncertainty about the effectiveness of various adjuvant treatments for low-grade gliomas (LGGs). Machine learning (ML) models that predict individual treatment effects (ITE) and provide treatment recommendations could help tailor treatments to each patient's needs.

OBJECTIVE

We sought to discern the individual suitability of radiotherapy (RT) or chemoradiotherapy (CRT) in LGG patients using ML models.

METHODS

Ten ML models, trained to infer ITE in 4,042 LGG patients, were assessed. We compared patients who followed treatment recommendations provided by the models with those who did not. To mitigate the risk of treatment selection bias, we employed inverse probability treatment weighting (IPTW).

RESULTS

The Balanced Survival Lasso-Network (BSL) model showed the most significant protective effect among all the models we tested (hazard ratio (HR): 0.52, 95% CI, 0.41-0.64; IPTW-adjusted HR: 0.58, 95% CI, 0.45-0.74; the difference in restricted mean survival time (DRMST): 9.11, 95% CI, 6.19-12.03; IPTW-adjusted DRMST: 9.17, 95% CI, 6.30-11.83). CRT presented a protective effect in the 'recommend for CRT' group (IPTW-adjusted HR: 0.60, 95% CI, 0.39-0.93) yet presented an adverse effect in the 'recommend for RT' group (IPTW-adjusted HR: 1.64, 95% CI, 1.19-2.25). Moreover, the models predict that younger patients and patients with overlapping lesions or tumors crossing the midline are better suited for CRT (HR: 0.62, 95% CI, 0.42-0.91; IPTW-adjusted HR: 0.59, 95% CI, 0.36-0.97).

CONCLUSION

Our findings underscore the potential of the BSL model in guiding the choice of adjuvant treatment for LGGs patients, potentially improving survival time. This study emphasizes the importance of ML in customizing patient care, understanding the nuances of treatment selection, and advancing personalized medicine.

Personalized, parcel-guided non-invasive transcranial magnetic stimulation for the treatment of post-concussive syndrome: safety and proof of concept

OBJECTIVE

To determine the safety and proof of concept of a parcel-guided, repetitive Transcranial Magnetic Stimulation (rTMS) in patients who develop a heterogeneous array of symptoms, known collectively as post-concussive syndrome (PCS), following traumatic brain injury (TBI).

METHODS

We performed a retrospective review of off-label, individualized, parcel-guided rTMS in 19 patients from December 2020 to May 2023. Patients had at least one instance of mild, moderate, or severe TBI and developed symptoms not present prior to injury. rTMS targets were identified based on machine learning connectomic software using functional connectivity anomaly matrices compared to healthy controls. EuroQol (EQ-5D), as a measurement of quality of life, and additional questionnaires dependent on individual's symptoms were submitted prior to, after, and during follow-up from rTMS.

RESULTS

Nineteen patients showed improvement in EQ-5D and Rivermead Post Concussion Symptoms Questionnaires - 3 after treatment and follow-up. For nine patients who developed depression, five (55%) attained response and remission based on the Beck Depression Inventory after treatment. Eight of ten patients with anxiety had a clinically significant reduction in Generalized Anxiety Disorder-7 scores during follow-up.

CONCLUSION

Parcel-guided rTMS is safe and may be effective in reducing PCS symptoms following TBI and should incite further controlled studies.

Predicting Cognitive Functioning for Patients with a High-Grade Glioma: Evaluating Different Representations of Tumor Location in a Common Space

Cognitive functioning is increasingly considered when making treatment decisions for patients with a brain tumor in view of a personalized onco-functional balance. Ideally, one can predict cognitive functioning of individual patients to make treatment decisions considering this balance. To make accurate predictions, an informative representation of tumor location is pivotal, yet comparisons of representations are lacking. Therefore, this study compares brain atlases and principal component analysis (PCA) to represent voxel-wise tumor location. Pre-operative cognitive functioning was predicted for 246 patients with a high-grade glioma across eight cognitive tests while using different representations of voxel-wise tumor location as predictors. Voxel-wise tumor location was represented using 13 different frequently-used population average atlases, 13 randomly generated atlases, and 13 representations based on PCA. ElasticNet predictions were compared between representations and against a model solely using tumor volume. Preoperative cognitive functioning could only partly be predicted from tumor location. Performances of different representations were largely similar. Population average atlases did not result in better predictions compared to random atlases. PCA-based representation did not clearly outperform other representations, although summary metrics indicated that PCA-based representations performed somewhat better in our sample. Representations with more regions or components resulted in less accurate predictions. Population average atlases possibly cannot distinguish between functionally distinct areas when applied to patients with a glioma. This stresses the need to develop and validate methods for individual parcellations in the presence of lesions. Future studies may test if the observed small advantage of PCA-based representations generalizes to other data.

Discernible interindividual patterns of global efficiency decline during theoretical brain surgery

The concept of functional localization within the brain and the associated risk of resecting these areas during removal of infiltrating tumors, such as diffuse gliomas, are well established in neurosurgery. Global efficiency (GE) is a graph theory concept that can be used to simulate connectome disruption following tumor resection. Structural connectivity graphs were created from diffusion tractography obtained from the brains of 80 healthy adults. These graphs were then used to simulate parcellation resection in every gross anatomical region of the cerebrum by identifying every possible combination of adjacent nodes in a graph and then measuring the drop in GE following nodal deletion. Progressive removal of brain parcellations led to patterns of GE decline that were reasonably predictable but had inter-subject differences. Additionally, as expected, there were deletion of some nodes that were worse than others. However, in each lobe examined in every subject, some deletion combinations were worse for GE than removing a greater number of nodes in a different region of the brain. Among certain patients, patterns of common nodes which exhibited worst GE upon removal were identified as "connectotypes". Given some evidence in the literature linking GE to certain aspects of neuro-cognitive abilities, investigating these connectotypes could potentially mitigate the impact of brain surgery on cognition.

Comparative validation of automated presurgical tractography based on constrained spherical deconvolution and diffusion tensor imaging with direct electrical stimulation

OBJECTIVES

Accurate presurgical brain mapping enables preoperative risk assessment and intraoperative guidance. This cross-sectional study investigated whether constrained spherical deconvolution (CSD) methods were more accurate than diffusion tensor imaging (DTI)-based methods for presurgical white matter mapping using intraoperative direct electrical stimulation (DES) as the ground truth.

METHODS

Five different tractography methods were compared (three DTI-based and two CSD-based) in 22 preoperative neurosurgical patients undergoing surgery with DES mapping. The corticospinal tract (CST, N = 20) and arcuate fasciculus (AF, N = 7) bundles were reconstructed, then minimum distances between tractograms and DES coordinates were compared between tractography methods. Receiver-operating characteristic (ROC) curves were used for both bundles. For the CST, binary agreement, linear modeling, and posthoc testing were used to compare tractography methods while correcting for relative lesion and bundle volumes.

RESULTS

Distance measures between 154 positive (functional response, pDES) and negative (no response, nDES) coordinates, and 134 tractograms resulted in 860 data points. Higher agreement was found between pDES coordinates and CSD-based compared to DTI-based tractograms. ROC curves showed overall higher sensitivity at shorter distance cutoffs for CSD (8.5 mm) compared to DTI (14.5 mm). CSD-based CST tractograms showed significantly higher agreement with pDES, which was confirmed by linear modeling and posthoc tests (PFWE < .05).

CONCLUSIONS

CSD-based CST tractograms were more accurate than DTI-based ones when validated using DES-based assessment of motor and sensory function. This demonstrates the potential benefits of structural mapping using CSD in clinical practice.

Simpson's Grading Scale for WHO Grade I Meningioma Resection in the Modern Neurosurgical Era: Are We Really Asking the Right Question?

The Simpson grading scale for the classification of the extent of meningioma resection provided a tremendous movement forward in 1957 suggesting increasing the extent of resection improves recurrence rates. However, equal, if not greater, movements forward have been made in the neurosurgical community over the last half a century owing to improvements in neuroimaging capabilities, microsurgical techniques, and radiotherapeutic strategies. Sughrue et al proposed the idea that these advancements have altered what a "recurrence" and "subtotal resection" truly means in modern neurosurgery compared with Simpson's era, and that a mandated use of the Simpson Scale is likely less clinically relevant today. A subsequent period of debate ensued in the literature which sought to re-examine the clinical value of using the Simpson Scale in modern neurosurgery. While a large body of evidence has recently been provided, these data generally continue to support the clinical importance of gross tumor resection as well as the value of adjuvant radiation therapy and the importance of recently updated World Health Organization classifications. However, there remains a negligible interval benefit in performing overly aggressive surgery and heroic maneuvers to remove the last bit of tumor, dura, and/or bone just for the simple act of achieving a lower Simpson score. Ultimately, meningioma surgery may be better contextualized as a continuous set of weighted risk-benefit decisions throughout the entire operation.

A parcellation-based connectomic model of hemispatial neglect

BACKGROUND AND PURPOSE

Hemispatial neglect is characterized by a reduced awareness to stimuli on the contralateral side. Current literature suggesting that damage to the right parietal lobe and attention networks may cause hemispatial neglect is conflicting and can be improved by investigating a connectomic model of the "neglect system" and the anatomical specificity of regions involved in it.

METHODS

A meta-analysis of voxel-based morphometry magnetic resonance imaging (MRI) studies of hemispatial neglect was used to identify regions associated with neglect. We applied parcellation schemes to these regions and performed diffusion spectrum imaging (DSI) tractography to determine their connectivity. By overlaying neglect areas and maps of the attention networks, we studied the relationship between them.

RESULTS

The meta-analysis generated a list of 13 right hemisphere parcellations. These 13 neglect-related parcellations were predominantly linked by the superior longitudinal fasciculus (SLF) throughout a fronto-parietal-temporal network. We found that the dorsal and ventral attention networks showed partial overlap with the neglect system and included various other higher-order networks.

CONCLUSIONS

We provide an anatomically specific connectomic model of the neurobehavioral substrates underlying hemispatial neglect. Our model suggests a fronto-parietal-temporal network linked via the SLF supports the functions impaired in neglect and implicates various higher-order networks which are not limited to the attention networks.

Connectome-Based Neurosurgery in Primary Intra-Axial Neoplasms: Beyond the Traditional Modular Conception of Brain Architecture for the Preservation of Major Neurological Domains and Higher-Order Cognitive Functions

Despite the therapeutical advancements in the surgical treatment of primary intra-axial neoplasms, which determined both a significative improvement in OS and QoL and a reduction in the incidence of surgery-induced major neurological deficits, nowadays patients continue to manifest subtle post-operative neurocognitive impairments, preventing them from a full reintegration back into social life and into the workforce. The birth of connectomics paved the way for a profound reappraisal of the traditional conception of brain architecture, in favour of a model based on large-scale structural and functional interactions of a complex mosaic of cortical areas organized in a fluid network interconnected by subcortical bundles. Thanks to these advancements, neurosurgery is facing a new era of connectome-based resections, in which the core principle is still represented by the achievement of an ideal onco-functional balance, but with a closer eye on whole-brain circuitry, which constitutes the foundations of both major neurological functions, to be intended as motricity; language and visuospatial function; and higher-order cognitive functions such as cognition, conation, emotion and adaptive behaviour. Indeed, the achievement of an ideal balance between the radicality of tumoral resection and the preservation, as far as possible, of the integrity of local and global brain networks stands as a mandatory goal to be fulfilled to allow patients to resume their previous life and to make neurosurgery tailored and gentler to their individual needs.

Neurocognitive Assessment of Mathematics-Related Capacities in Neurosurgical Patients

A precise neuropsychological assessment is of the utmost importance for neurosurgical patients undergoing the surgical excision of cerebral lesions. The assessment of mathematical abilities is usually limited to arithmetical operations while other fundamental visuo-spatial aspects closely linked to mathematics proficiency, such as the perception of numerical quantities and geometrical reasoning, are completely neglected. We evaluated these abilities with two objective and reproducible psychophysical tests, measuring numerosity perception and non-symbolic geometry, respectively. We tested sixteen neuro-oncological patients before the operation and six after the operation with classical neuropsychological tests and with two psychophysical tests. The scores of the classical neuropsychological tests were very heterogeneous, possibly due to the distinct location and histology of the tumors that might have spared (or not) brain areas subserving these abilities or allowed for plastic reorganization. Performance in the two non-symbolic tests reflected, on average, the presumed functional role of the lesioned areas, with participants with parietal and frontal lesions performing worse on these tests than patients with occipital and temporal lesions. Single-case analyses not only revealed some interesting exceptions to the group-level results (e.g., patients with parietal lesions performing well in the numerosity test), but also indicated that performance in the two tests was independent of non-verbal reasoning and visuo-spatial working memory. Our results highlight the importance of assessing non-symbolic numerical and geometrical abilities to complement typical neuropsychological batteries. However, they also suggest an avoidance of reliance on an excessively rigid localizationist approach when evaluating the neuropsychological profile of oncological patients.

The Brain Connectome for Clinical Neuroscience

In this chapter, we introduce the topic of the brain connectome, consisting of the complete set of both the structural and functional connections of the brain. Connectomic information and the large-scale network architecture of the brain provide an improved understanding of the organization and functional relevance of human cortical and subcortical anatomy. We discuss various analytical methods to both identify and interpret structural and functional connectivity data. In turn, we discuss how these data provide significant clinical promise for neurosurgery, neurology, and psychiatry in that more informed decisions can be made based on connectomic information. These data can provide safer and more informed network-based neurosurgery for brain tumor patients and even offer the possibility to modulate the brain connectome.

Structural connectome-based predictive modeling of cognitive deficits in treated glioma patients

Background

In glioma patients, tumor growth and subsequent treatments are associated with various types of brain lesions. We hypothesized that cognitive functioning in these patients critically depends on the maintained structural connectivity of multiple brain networks.

Methods

The study included 121 glioma patients (median age, 52 years; median Eastern Cooperative Oncology Group performance score 1; CNS-WHO Grade 3 or 4) after multimodal therapy. Cognitive performance was assessed by 10 tests in 5 cognitive domains at a median of 14 months after treatment initiation. Hybrid amino acid PET/MRI using the tracer O-(2-[18F]fluoroethyl)-L-tyrosine, a network-based cortical parcellation, and advanced tractography were used to generate whole-brain fiber count-weighted connectivity matrices. The matrices were applied to a cross-validated machine-learning model to identify predictive fiber connections (edges), critical cortical regions (nodes), and the networks underlying cognitive performance.

Results

Compared to healthy controls (n = 121), patients' cognitive scores were significantly lower in 9 cognitive tests. The models predicted the scores of 7/10 tests (median correlation coefficient, 0.47; range, 0.39-0.57) from 0.6% to 5.4% of the matrix entries; 84% of the predictive edges were between nodes of different networks. Critically involved cortical regions (≥10 adjacent edges) included predominantly left-sided nodes of the visual, somatomotor, dorsal/ventral attention, and default mode networks. Highly critical nodes (≥15 edges) included the default mode network's left temporal and bilateral posterior cingulate cortex.

Conclusions

These results suggest that the cognitive performance of pretreated glioma patients is strongly related to structural connectivity between multiple brain networks and depends on the integrity of known network hubs also involved in other neurological disorders.

Parcellation-Based Connectivity Model of the Judgement Core

Judgement is a higher-order brain function utilized in the evaluation process of problem solving. However, heterogeneity in the task methodology based on the many definitions of judgement and its expansive and nuanced applications have prevented the identification of a unified cortical model at a level of granularity necessary for clinical translation. Forty-six task-based fMRI studies were used to generate activation-likelihood estimations (ALE) across moral, social, risky, and interpersonal judgement paradigms. Cortical parcellations overlapping these ALEs were used to delineate patterns in neurocognitive network engagement for the four judgement tasks. Moral judgement involved the bilateral superior frontal gyri, right temporal gyri, and left parietal lobe. Social judgement demonstrated a left-dominant frontoparietal network with engagement of right-sided temporal limbic regions. Moral and social judgement tasks evoked mutual engagement of the bilateral DMN. Both interpersonal and risk judgement were shown to involve a right-sided frontoparietal network with accompanying engagement of the left insular cortex, converging at the right-sided CEN. Cortical activation in normophysiological judgement function followed two separable patterns involving the large-scale neurocognitive networks. Specifically, the DMN was found to subserve judgement centered around social inferences and moral cognition, while the CEN subserved tasks involving probabilistic reasoning, risk estimation, and strategic contemplation.

Functional connectivity reveals different brain networks underlying the idiopathic foreign accent syndrome

Foreign accent syndrome (FAS) is characterized by new onset speech that is perceived as foreign. Available data from acquired cases suggests focal brain damage in language and sensorimotor brain networks, but little remains known about abnormal functional connectivity in idiopathic cases of FAS without structural damage. Here, connectomic analyses were completed on three patients with idiopathic FAS to investigate unique functional connectivity abnormalities underlying accent change for the first time. Machine learning (ML)-based algorithms generated personalized brain connectomes based on a validated parcellation scheme from the Human Connectome Project (HCP). Diffusion tractography was performed on each patient to rule out structural fiber damage to the language system. Resting-state-fMRI was assessed with ML-based software to examine functional connectivity between individual parcellations within language and sensorimotor networks and subcortical structures. Functional connectivity matrices were created and compared against a dataset of 200 healthy subjects to identify abnormally connected parcellations. Three female patients (28-42 years) who presented with accent changes from Australian English to Irish (n = 2) or American English to British English (n = 1) demonstrated fully intact language system structural connectivity. All patients demonstrated functional connectivity anomalies within language and sensorimotor networks in numerous left frontal regions and between subcortical structures in one patient. Few commonalities in functional connectivity anomalies were identified between all three patients, specifically 3 internal-network parcellation pairs. No common inter-network functional connectivity anomalies were identified between all patients. The current study demonstrates specific language, and sensorimotor functional connectivity abnormalities can exist and be quantitatively shown in the absence of structural damage for future study.

The functional role of the precuneus

Recent advancements in computational approaches and neuroimaging techniques have refined our understanding of the precuneus. While previously believed to be largely a visual processing region, the importance of the precuneus in complex cognitive functions has been previously less familiar due to a lack of focal lesions in this deeply seated region, but also a poor understanding of its true underlying anatomy. Fortunately, recent studies have revealed significant information on the structural and functional connectivity of this region, and this data has provided a more detailed mechanistic understanding of the importance of the precuneus in healthy and pathologic states. Through improved resting-state functional MRI analyses, it has become clear that the function of the precuneus can be better understood based on its functional association with large scale brain networks. Dual default mode network systems have been well explained in recent years in supporting episodic memory and theory of mind; however, a novel 'para-cingulate' network, which is a subnetwork of the larger central executive network, with likely significant roles in self-referential processes and related psychiatric symptoms is introduced here and requires further clarification. Importantly, detailed anatomic studies on the precuneus structural connectivity inside and beyond the cingulate cortex has demonstrated the presence of large structural white matter connections, which provide an additional layer of meaning to the structural-functional significance of this region and its association with large scale brain networks. Together, the structural-functional connectivity of the precuneus has provided central elements which can model various neurodegenerative diseases and psychiatric disorders, such as Alzheimer's disease and depression.

Preoperative detailed evaluation intracranial artery stenosis using three-dimensional visualization analysis reduces the invasiveness of superficial temporal artery-middle cerebral artery bypass

OBJECTIVES

Superficial temporal artery (STA) to middle cerebral artery (MCA) bypass surgery is a common treatment for preventing cerebral ischemia in patients with intracranial artery stenosis. The aim of this study was to analyze the surgical outcomes of the STA-MCA bypass procedure, particularly with regard to the invasiveness of targeted bypass (TB) with preoperative planning using Amira® software.

METHODS

Consecutive patients with single STA-MCA bypass performed by a single neurosurgeon from January 2019 to May 2022 were included. The clinical parameters of seven TB patients were compared with those of 11 patients treated with the conventional method (CM).

RESULTS

Compared with CM patients, TB using Amira® software patients had a shorter scalp incision (median [interquartile range]=11.2 [9.7-12.7] cm vs. 16.9 [16.0-17.7] cm, respectively; p=0.004], smaller craniotomy size (11.8 [11.5-14.4] cm2 vs. 20.9 [17.1-22.2] cm2, respectively; p=0.01], shorter surgery duration (201 [195-218] min vs. 277 [229-310] min, respectively; p=0.003], and less intraoperative bleeding (10 [10-20] g vs. 23 [20-50] g, respectively; p=0.033]. However, there were no differences in surgical complications between the two groups.

CONCLUSIONS

Detailed preoperative evaluation using Amira® software can reduce the invasiveness of the STA-MCA bypass procedure.

Large-scale brain networks and intra-axial tumor surgery: a narrative review of functional mapping techniques, critical needs, and scientific opportunities

In recent years, a paradigm shift in neuroscience has been occurring from "localizationism," or the idea that the brain is organized into separately functioning modules, toward "connectomics," or the idea that interconnected nodes form networks as the underlying substrates of behavior and thought. Accordingly, our understanding of mechanisms of neurological function, dysfunction, and recovery has evolved to include connections, disconnections, and reconnections. Brain tumors provide a unique opportunity to probe large-scale neural networks with focal and sometimes reversible lesions, allowing neuroscientists the unique opportunity to directly test newly formed hypotheses about underlying brain structural-functional relationships and network properties. Moreover, if a more complete model of neurological dysfunction is to be defined as a "disconnectome," potential avenues for recovery might be mapped through a "reconnectome." Such insight may open the door to novel therapeutic approaches where previous attempts have failed. In this review, we briefly delve into the most clinically relevant neural networks and brain mapping techniques, and we examine how they are being applied to modern neurosurgical brain tumor practices. We then explore how brain tumors might teach us more about mechanisms of global brain dysfunction and recovery through pre- and postoperative longitudinal connectomic and behavioral analyses.

Connectomic insight into unique stroke patient recovery after rTMS treatment

An improved understanding of the neuroplastic potential of the brain has allowed advancements in neuromodulatory treatments for acute stroke patients. However, there remains a poor understanding of individual differences in treatment-induced recovery. Individualized information on connectivity disturbances may help predict differences in treatment response and recovery phenotypes. We studied the medical data of 22 ischemic stroke patients who received MRI scans and started repetitive transcranial magnetic stimulation (rTMS) treatment on the same day. The functional and motor outcomes were assessed at admission day, 1 day after treatment, 30 days after treatment, and 90 days after treatment using four validated standardized stroke outcome scales. Each patient underwent detailed baseline connectivity analyses to identify structural and functional connectivity disturbances. An unsupervised machine learning (ML) agglomerative hierarchical clustering method was utilized to group patients according to outcomes at four-time points to identify individual phenotypes in recovery trajectory. Differences in connectivity features were examined between individual clusters. Patients were a median age of 64, 50% female, and had a median hospital length of stay of 9.5 days. A significant improvement between all time points was demonstrated post treatment in three of four validated stroke scales utilized. ML-based analyses identified distinct clusters representing unique patient trajectories for each scale. Quantitative differences were found to exist in structural and functional connectivity analyses of the motor network and subcortical structures between individual clusters which could explain these unique trajectories on the Barthel Index (BI) scale but not on other stroke scales. This study demonstrates for the first time the feasibility of using individualized connectivity analyses in differentiating unique phenotypes in rTMS treatment responses and recovery. This personalized connectomic approach may be utilized in the future to better understand patient recovery trajectories with neuromodulatory treatment.

Advances in computational and translational approaches for malignant glioma

Gliomas are the most common primary brain tumors in adults and carry a dismal prognosis for patients. Current standard-of-care for gliomas is comprised of maximal safe surgical resection following by a combination of chemotherapy and radiation therapy depending on the grade and type of tumor. Despite decades of research efforts directed towards identifying effective therapies, curative treatments have been largely elusive in the majority of cases. The development and refinement of novel methodologies over recent years that integrate computational techniques with translational paradigms have begun to shed light on features of glioma, previously difficult to study. These methodologies have enabled a number of point-of-care approaches that can provide real-time, patient-specific and tumor-specific diagnostics that may guide the selection and development of therapies including decision-making surrounding surgical resection. Novel methodologies have also demonstrated utility in characterizing glioma-brain network dynamics and in turn early investigations into glioma plasticity and influence on surgical planning at a systems level. Similarly, application of such techniques in the laboratory setting have enhanced the ability to accurately model glioma disease processes and interrogate mechanisms of resistance to therapy. In this review, we highlight representative trends in the integration of computational methodologies including artificial intelligence and modeling with translational approaches in the study and treatment of malignant gliomas both at the point-of-care and outside the operative theater in silico as well as in the laboratory setting.

A timeline of cognitive functioning in glioma patients who undergo awake brain tumor surgery

BACKGROUND

The purpose of awake brain tumor surgery is to maximize the resection of the tumor and to minimize the risk of neurological and cognitive impairments. The aim of this study is to gain understanding of the development of possible postoperative cognitive deficits after awake brain tumor surgery in patients with suspected gliomas, by comparing preoperative, early postoperative, and late postoperative functioning. A more detailed timeline will be helpful in informing candidates for surgery about what to expect regarding their cognitive functioning.

METHODS

Thirty-seven patients were included in this study. Cognitive functioning was measured by means of a broad cognitive screener preoperatively, days after surgery and months after surgery in patients who underwent awake brain tumor surgery with cognitive monitoring. The cognitive screener included tests for object naming, reading, attention span, working memory, inhibition, inhibition/switching, and visuoperception. We performed a Friedman ANOVA to analyze on group level.

RESULTS

Overall, no significant differences were found between preoperative cognitive functioning, early postoperative cognitive functioning, and late postoperative cognitive functioning, except for performances on the inhibition task. Directly after surgery, patients were significantly slower on this task. However, in the following months after surgery, they returned to their preoperative level.

CONCLUSION

The timeline of cognitive functioning after awake tumor surgery appeared overall stable in the early and late postoperative phase, except for inhibition, which is more difficult in the first days after awake brain tumor surgery. This more detailed timeline of cognitive functioning, in combination with future research, can possibly be contributing in informing patients and caregivers what to expect after awake brain tumor surgery.

Non-traditional cognitive brain network involvement in insulo-Sylvian gliomas: a case series study and clinical experience using Quicktome

BACKGROUND

Patients with insulo-Sylvian gliomas continue to present with severe morbidity in cognitive functions primarily due to neurosurgeons' lack of familiarity with non-traditional brain networks. We sought to identify the frequency of invasion and proximity of gliomas to portions of these networks.

METHODS

We retrospectively analyzed data from 45 patients undergoing glioma surgery centered in the insular lobe. Tumors were categorized based on their proximity and invasiveness of non-traditional cognitive networks and traditionally eloquent structures. Diffusion tensor imaging tractography was completed by creating a personalized brain atlas using Quicktome to determine eloquent and non-eloquent networks in each patient. Additionally, we prospectively collected neuropsychological data on 7 patients to compare tumor-network involvement with change in cognition. Lastly, 2 prospective patients had their surgical plan influenced by network mapping determined by Quicktome.

RESULTS

Forty-four of 45 patients demonstrated tumor involvement (< 1 cm proximity or invasion) with components of non-traditional brain networks involved in cognition such as the salience network (SN, 60%) and the central executive network (CEN, 56%). Of the seven prospective patients, all had tumors involved with the SN, CEN (5/7, 71%), and language network (5/7, 71%). The mean scores of MMSE and MOCA before surgery were 18.71 ± 6.94 and 17.29 ± 6.26, respectively. The two cases who received preoperative planning with Quicktome had a postoperative performance that was anticipated.

CONCLUSIONS

Non-traditional brain networks involved in cognition are encountered during surgical resection of insulo-Sylvian gliomas. Quicktome can improve the understanding of the presence of these networks and allow for more informed surgical decisions based on patient functional goals.

Psychedelic-Assisted Therapy and Psychedelic Science: A Review and Perspective on Opportunities in Neurosurgery and Neuro-Oncology

After a decades-long pause, psychedelics are again being intensely investigated for treating a wide range of neuropsychiatric ailments including depression, anxiety, addiction, post-traumatic stress disorder, anorexia, and chronic pain syndromes. The classic serotonergic psychedelics psilocybin and lysergic acid diethylamide and nonclassic psychedelics 3,4-methylenedioxymethamphetamine and ketamine are increasingly appreciated as neuroplastogens given their potential to fundamentally alter mood and behavior well beyond the time window of measurable exposure. Imaging studies with psychedelics are also helping advance our understanding of neural networks and connectomics. This resurgence in psychedelic science and psychedelic-assisted therapy has potential significance for the fields of neurosurgery and neuro-oncology and their diverse and challenging patients, many of whom continue to have mental health issues and poor quality of life despite receiving state-of-the-art care. In this study, we review recent and ongoing clinical trials, the set and setting model of psychedelic-assisted therapy, potential risks and adverse events, proposed mechanisms of action, and provide a perspective on how the safe and evidence-based use of psychedelics could potentially benefit many patients, including those with brain tumors, pain syndromes, ruminative disorders, stroke, SAH, TBI, and movement disorders. By leveraging psychedelics' neuroplastic potential to rehabilitate the mind and brain, novel treatments may be possible for many of these patient populations, in some instances working synergistically with current treatments and in some using subpsychedelic doses that do not require mind-altering effects for efficacy. This review aims to encourage broader multidisciplinary collaboration across the neurosciences to explore and help realize the transdiagnostic healing potential of psychedelics.

Topology of the lateral visual system: The fundus of the superior temporal sulcus and parietal area H connect nonvisual cerebrum to the lateral occipital lobe

BACKGROUND AND PURPOSE

Mapping the topology of the visual system is critical for understanding how complex cognitive processes like reading can occur. We aim to describe the connectivity of the visual system to understand how the cerebrum accesses visual information in the lateral occipital lobe.

METHODS

Using meta-analytic software focused on task-based functional MRI studies, an activation likelihood estimation (ALE) of the visual network was created. Regions of interest corresponding to the cortical parcellation scheme previously published under the Human Connectome Project were co-registered onto the ALE to identify the hub-like regions of the visual network. Diffusion Spectrum Imaging-based fiber tractography was performed to determine the structural connectivity of these regions with extraoccipital cortices.

RESULTS

The fundus of the superior temporal sulcus (FST) and parietal area H (PH) were identified as hub-like regions for the visual network. FST and PH demonstrated several areas of coactivation beyond the occipital lobe and visual network. Furthermore, these parcellations were highly interconnected with other cortical regions throughout extraoccipital cortices related to their nonvisual functional roles. A cortical model demonstrating connections to these hub-like areas was created.

CONCLUSIONS

FST and PH are two hub-like areas that demonstrate extensive functional coactivation and structural connections to nonvisual cerebrum. Their structural interconnectedness with language cortices along with the abnormal activation of areas commonly located in the temporo-occipital region in dyslexic individuals suggests possible important roles of FST and PH in the integration of information related to language and reading. Future studies should refine our model by examining the functional roles of these hub areas and their clinical significance.

Maximal Safe Resection in Glioblastoma Surgery: A Systematic Review of Advanced Intraoperative Image-Guided Techniques

Glioblastoma multiforme (GBM) represents the most common and aggressive central nervous system tumor associated with a poor prognosis. The aim of this study was to depict the role of intraoperative imaging techniques in GBM surgery and how they can ensure the maximal extent of resection (EOR) while preserving the functional outcome. The authors conducted a systematic review following PRISMA guidelines on the PubMed/Medline and Scopus databases. A total of 1747 articles were identified for screening. Studies focusing on GBM-affected patients, and evaluations of EOR and functional outcomes with the aid of advanced image-guided techniques were included. The resulting studies were assessed for methodological quality using the Risk of Bias in Systematic Review tool. Open Science Framework registration DOI 10.17605/OSF.IO/3FDP9. Eighteen studies were eligible for this systematic review. Among the selected studies, eight analyzed Sodium Fluorescein, three analyzed 5-aminolevulinic acid, two evaluated IoMRI imaging, two evaluated IoUS, and three evaluated multiple intraoperative imaging techniques. A total of 1312 patients were assessed. Gross Total Resection was achieved in the 78.6% of the cases. Follow-up time ranged from 1 to 52 months. All studies assessed the functional outcome based on the Karnofsky Performance Status scale, while one used the Neurologic Assessment in Neuro-Oncology score. In 77.7% of the cases, the functional outcome improved or was stable over the pre-operative assessment. Combining multiple intraoperative imaging techniques could provide better results in GBM surgery than a single technique. However, despite good surgical outcomes, patients often present a neurocognitive decline leading to a marked deterioration of the quality of life. Advanced intraoperative image-guided techniques can allow a better understanding of the anatomo-functional relationships between the tumor and the surrounding brain, thus maximizing the EOR while preserving functional outcomes.

Graph Theory Measures and Their Application to Neurosurgical Eloquence

Improving patient safety and preserving eloquent brain are crucial in neurosurgery. Since there is significant clinical variability in post-operative lesions suffered by patients who undergo surgery in the same areas deemed compensable, there is an unknown degree of inter-individual variability in brain 'eloquence'. Advances in connectomic mapping efforts through diffusion tractography allow for utilization of non-invasive imaging and statistical modeling to graphically represent the brain. Extending the definition of brain eloquence to graph theory measures of hubness and centrality may help to improve our understanding of individual variability in brain eloquence and lesion responses. While functional deficits cannot be immediately determined intra-operatively, there has been potential shown by emerging technologies in mapping of hub nodes as an add-on to existing surgical navigation modalities to improve individual surgical outcomes. This review aims to outline and review current research surrounding novel graph theoretical concepts of hubness, centrality, and eloquence and specifically its relevance to brain mapping for pre-operative planning and intra-operative navigation in neurosurgery.

Lesion network mapping of ectopic craniopharyngioma identifies potential cause of psychosis: a case report

We report the case of a patient with craniopharyngioma who demonstrated ectopic spread to the right temporal lobe and concurrent local recurrence, 10 years after her initial diagnosis. The patient additionally demonstrated new-onset psychotic symptoms of uncertain etiology during her admission. Lesion network mapping identified the ectopic lesion as a putative cause for her psychosis. These findings were substantiated after the resection of the ectopic lesion and subsequent resolution of her psychiatric symptoms. This report adds to the rare accounts of ectopic craniopharyngioma, while highlighting the utility of network-based analyses in peri-operative tumor evaluation and the assessment of atypical neuropsychiatric phenomena.

Parcellation-based tractographic modeling of the salience network through meta-analysis

BACKGROUND

The salience network (SN) is a transitory mediator between active and passive states of mind. Multiple cortical areas, including the opercular, insular, and cingulate cortices have been linked in this processing, though knowledge of network connectivity has been devoid of structural specificity.

OBJECTIVE

The current study sought to create an anatomically specific connectivity model of the neural substrates involved in the salience network.

METHODS

A literature search of PubMed and BrainMap Sleuth was conducted for resting-state and task-based fMRI studies relevant to the salience network according to PRISMA guidelines. Publicly available meta-analytic software was utilized to extract relevant fMRI data for the creation of an activation likelihood estimation (ALE) map and relevant parcellations from the human connectome project overlapping with the ALE data were identified for inclusion in our SN model. DSI-based fiber tractography was then performed on publicaly available data from healthy subjects to determine the structural connections between cortical parcellations comprising the network.

RESULTS

Nine cortical regions were found to comprise the salience network: areas AVI (anterior ventral insula), MI (middle insula), FOP4 (frontal operculum 4), FOP5 (frontal operculum 5), a24pr (anterior 24 prime), a32pr (anterior 32 prime), p32pr (posterior 32 prime), and SCEF (supplementary and cingulate eye field), and 46. The frontal aslant tract was found to connect the opercular-insular cluster to the middle cingulate clusters of the network, while mostly short U-fibers connected adjacent nodes of the network.

CONCLUSION

Here we provide an anatomically specific connectivity model of the neural substrates involved in the salience network. These results may serve as an empiric basis for clinical translation in this region and for future study which seeks to expand our understanding of how specific neural substrates are involved in salience processing and guide subsequent human behavior.

A connectivity model of the anatomic substrates underlying Gerstmann syndrome

The Gerstmann syndrome is a constellation of neurological deficits that include agraphia, acalculia, left-right discrimination and finger agnosia. Despite a growing interest in this clinical phenomenon, there remains controversy regarding the specific neuroanatomic substrates involved. Advancements in data-driven, computational modelling provides an opportunity to create a unified cortical model with greater anatomic precision based on underlying structural and functional connectivity across complex cognitive domains. A literature search was conducted for healthy task-based functional MRI and PET studies for the four cognitive domains underlying Gerstmann's tetrad using the electronic databases PubMed, Medline, and BrainMap Sleuth (2.4). Coordinate-based, meta-analytic software was utilized to gather relevant regions of interest from included studies to create an activation likelihood estimation (ALE) map for each cognitive domain. Machine-learning was used to match activated regions of the ALE to the corresponding parcel from the cortical parcellation scheme previously published under the Human Connectome Project (HCP). Diffusion spectrum imaging-based tractography was performed to determine the structural connectivity between relevant parcels in each domain on 51 healthy subjects from the HCP database. Ultimately 102 functional MRI studies met our inclusion criteria. A frontoparietal network was found to be involved in the four cognitive domains: calculation, writing, finger gnosis, and left-right orientation. There were three parcels in the left hemisphere, where the ALE of at least three cognitive domains were found to be overlapping, specifically the anterior intraparietal area, area 7 postcentral (7PC) and the medial intraparietal sulcus. These parcels surround the anteromedial portion of the intraparietal sulcus. Area 7PC was found to be involved in all four domains. These regions were extensively connected in the intraparietal sulcus, as well as with a number of surrounding large-scale brain networks involved in higher-order functions. We present a tractographic model of the four neural networks involved in the functions which are impaired in Gerstmann syndrome. We identified a 'Gerstmann Core' of extensively connected functional regions where at least three of the four networks overlap. These results provide clinically actionable and precise anatomic information which may help guide clinical translation in this region, such as during resective brain surgery in or near the intraparietal sulcus, and provides an empiric basis for future study.

12 Plagues of AI in Healthcare: A Practical Guide to Current Issues With Using Machine Learning in a Medical Context

The healthcare field has long been promised a number of exciting and powerful applications of Artificial Intelligence (AI) to improve the quality and delivery of health care services. AI techniques, such as machine learning (ML), have proven the ability to model enormous amounts of complex data and biological phenomena in ways only imaginable with human abilities alone. As such, medical professionals, data scientists, and Big Tech companies alike have all invested substantial time, effort, and funding into these technologies with hopes that AI systems will provide rigorous and systematic interpretations of large amounts of data that can be leveraged to augment clinical judgments in real time. However, despite not being newly introduced, AI-based medical devices have more than often been limited in their true clinical impact that was originally promised or that which is likely capable, such as during the current COVID-19 pandemic. There are several common pitfalls for these technologies that if not prospectively managed or adjusted in real-time, will continue to hinder their performance in high stakes environments outside of the lab in which they were created. To address these concerns, we outline and discuss many of the problems that future developers will likely face that contribute to these failures. Specifically, we examine the field under four lenses: approach, data, method and operation. If we continue to prospectively address and manage these concerns with reliable solutions and appropriate system processes in place, then we as a field may further optimize the clinical applicability and adoption of medical based AI technology moving forward.

Should Neurosurgeons Try to Preserve Non-Traditional Brain Networks? A Systematic Review of the Neuroscientific Evidence

The importance of large-scale brain networks in higher-order human functioning is well established in neuroscience, but has yet to deeply penetrate neurosurgical thinking due to concerns of clinical relevance. Here, we conducted the first systematic review examining the clinical importance of non-traditional, large-scale brain networks, including the default mode (DMN), central executive (CEN), salience (SN), dorsal attention (DAN), and ventral attention (VAN) networks. Studies which reported evidence of neurologic, cognitive, or emotional deficits in relation to damage or dysfunction in these networks were included. We screened 22,697 articles on PubMed, and 551 full-text articles were included and examined. Cognitive deficits were the most common symptom of network disturbances in varying amounts (36–56%), most frequently related to disruption of the DMN (n = 213) or some combination of DMN, CEN, and SN networks (n = 182). An increased proportion of motor symptoms was seen with CEN disruption (12%), and emotional (35%) or language/speech deficits (24%) with SN disruption. Disruption of the attention networks (VAN/DAN) with each other or the other networks mostly led to cognitive deficits (56%). A large body of evidence is available demonstrating the clinical importance of non-traditional, large-scale brain networks and suggests the need to preserve these networks is relevant for neurosurgical patients.

Transcranial magnetic stimulation for post-operative neurorehabilitation in neuro-oncology: a review of the literature and future directions

INTRODUCTION

Transcranial magnetic stimulation (TMS) is a neuromodulation technology capable of targeted stimulation and inhibition of cortical areas. Repetitive TMS (rTMS) has demonstrated efficacy in the treatment of several neuropsychiatric disorders, and novel uses of rTMS for neurorehabilitation in patients with acute and chronic neurologic deficits are being investigated. However, studies to date have primarily focused on neurorehabilitation in stroke patients, with little data supporting its use for neurorehabilitation in brain tumor patients.

METHODS

We performed a review of the current available literature regarding uses of rTMS for neurorehabilitation in post-operative neuro-oncologic patients.

RESULTS

Data have demonstrated that rTMS is safe in the post-operative neuro-oncologic patient population, with minimal adverse effects and no documented seizures. The current evidence also demonstrates potential effectiveness in terms of neurorehabilitation of motor and language deficits.

CONCLUSIONS

Although data are overall limited, both safety and effectiveness have been demonstrated for the use of rTMS for neurorehabilitation in the neuro-oncologic population. More randomized controlled trials and specific comparisons of contralateral versus ipsilateral rTMS protocols should be explored. Further work may also focus on individualized, patient-specific TMS treatment protocols for optimal functional recovery.

Interventional neurorehabilitation for promoting functional recovery post-craniotomy: a proof-of-concept

The human brain is a highly plastic ‘complex’ network—it is highly resilient to damage and capable of self-reorganisation after a large perturbation. Clinically, neurological deficits secondary to iatrogenic injury have very few active treatments. New imaging and stimulation technologies, though, offer promising therapeutic avenues to accelerate post-operative recovery trajectories. In this study, we sought to establish the safety profile for ‘interventional neurorehabilitation’: connectome-based therapeutic brain stimulation to drive cortical reorganisation and promote functional recovery post-craniotomy. In n = 34 glioma patients who experienced post-operative motor or language deficits, we used connectomics to construct single-subject cortical networks. Based on their clinical and connectivity deficit, patients underwent network-specific transcranial magnetic stimulation (TMS) sessions daily over five consecutive days. Patients were then assessed for TMS-related side effects and improvements. 31/34 (91%) patients were successfully recruited and enrolled for TMS treatment within two weeks of glioma surgery. No seizures or serious complications occurred during TMS rehabilitation and 1-week post-stimulation. Transient headaches were reported in 4/31 patients but improved after a single session. No neurological worsening was observed while a clinically and statistically significant benefit was noted in 28/31 patients post-TMS. We present two clinical vignettes and a video demonstration of interventional neurorehabilitation. For the first time, we demonstrate the safety profile and ability to recruit, enroll, and complete TMS acutely post-craniotomy in a high seizure risk population. Given the lack of randomisation and controls in this study, prospective randomised sham-controlled stimulation trials are now warranted to establish the efficacy of interventional neurorehabilitation following craniotomy.

Subcortical Stimulation in Brain Tumor Surgery: A closer look beneath the surface

INTRODUCTION

Maximizing a patient's onco-functional balance is the central tenet of brain tumor surgery. As a result, numerous surgical adjuncts have been developed to facilitate identification of the tumor-brain interface and preservation of functional anatomy. Among these, intraoperative neurophysiologic monitoring (IONM) with direct cortical and subcortical stimulation remains the gold standard for real time, functional mapping of motor and language activity. However, stimulation techniques are not standardized and vary significantly across institutions. This is particularly true with subcortical stimulation for mapping of motor function.

METHODS

We review the state of subcortical IONM and mapping techniques. Historical and predicate literature were reviewed as well as new and emerging techniques. We discuss their evolution, clinical utility, and limitations to direct future research and application.

RESULTS

We evaluate and discuss the background and current clinical use of direct cortical and subcortical stimulation techniques and protocols and identify current trends and limitations. We focus specifically on methods of subcortical stimulation given the heterogeneity in the published literature. We also suggest directions to optimize the clinical utility of these tools.

CONCLUSION

Despite significant heterogeneity in published techniques, trends support the use of the Taniguchi method for subcortical stimulation. Novel dynamic stimulation techniques may improve accuracy. Prospective studies to define standardized guidelines are needed.

Eigenvector PageRank difference as a measure to reveal topological characteristics of the brain connectome for neurosurgery

PURPOSE

Applying graph theory to the human brain has the potential to help prognosticate the impacts of intracerebral surgery. Eigenvector (EC) and PageRank (PR) centrality are two related, but uniquely different measures of nodal centrality which may be utilized together to reveal varying neuroanatomical characteristics of the brain connectome.

METHODS

We obtained diffusion neuroimaging data from a healthy cohort (UCLA consortium for neuropsychiatric phenomics) and applied a personalized parcellation scheme to them. We ranked parcels based on weighted EC and PR, and then calculated the difference (EP difference) and correlation between the two metrics. We also compared the difference between the two metrics to the clustering coefficient.

RESULTS

While EC and PR were consistent for top and bottom ranking parcels, they differed for mid-ranking parcels. Parcels with a high EC centrality but low PR tended to be in the medial temporal and temporooccipital regions, whereas PR conferred greater importance to multi-modal association areas in the frontal, parietal and insular cortices. The EP difference showed a weak correlation with clustering coefficient, though there was significant individual variation.

CONCLUSIONS

The relationship between PageRank and eigenvector centrality can identify distinct topological characteristics of the brain connectome such as the presence of unimodal or multimodal association cortices. These results highlight how different graph theory metrics can be used alone or in combination to reveal unique neuroanatomical features for further clinical study.

Endoscopic-assisted surgical approach for butterfly glioma surgery

PURPOSE

Gliomas that spread along the white matter tracts of the corpus callosum to both hemispheres have traditionally been considered surgically challenging largely due to the relative complexity of safely achieving complete resections. We present a series of endoscopic-assisted resections of butterfly gliomas with post-operative radiological assessment of EOR and clinical outcome data.

METHODS

Retrospective review of patients who underwent surgical resection of a butterfly glioma from 2007 to 2020. Butterfly gliomas were defined as gliomas, which appeared to arise from the corpus callosum with significant bilateral extension. All records were retrospectively reviewed with operative/clinical outcomes and complications recorded.

RESULTS

70 patients who underwent an endoscopic-assisted transcortical or interhemispheric approach for butterfly glioma resection met inclusion criteria. A unilateral transcortical approach was used in 86% of cases and an interhemispheric approach in 14%. The endoscope enhanced the visualization of the contralateral hemisphere and allowed for resection of tumor, not reached by standard microscopic visualization, in 100% of cases. 90% of resections resulted in greater than a 95% resection rate. Neurological deficits mostly consisted of motor (10%) and memory (6%) deficits and were most common with posterior tumors of the splenium.

CONCLUSION

The endoscopic-assisted transcortical or interhemispheric approach for butterfly glioma resection is effective in achieving a greater than 95% resection with minimal complications. An angled approach allows careful maneuvering around complex anatomic structures and difficult corners, and should be examined further for its clinical benefits in a prospective manner.

Insular gliomas and tractographic visualization of the connectome

In this video, the authors present a connectome-guided surgical resection of an insular glioma in a 39-year-old woman. Preoperative study with constrained spherical deconvolution (CSD)-based tractography revealed the surrounding brain connectome architecture around the tumor relevant for safe surgical resection. Connectomic information provided detailed maps of the surrounding language and salience networks, including eloquent white matter fibers and cortical regions, which were visualized intraoperatively with image guidance and artificial intelligence (AI)-based brain mapping software. Microsurgical dissection is presented with detailed discussion of the safe boundaries and angles of resection when entering the insular operculum defined by connectomic information. The video can be found here: https://stream.cadmore.media/r10.3171/2021.10.FOCVID21194.

Examining the benefits of extended reality in neurosurgery: A systematic review

While well-established in other surgical subspecialties, the benefits of extended reality, consisting of virtual reality (VR), augmented reality (AR), and mixed reality (MR) technologies, remains underexplored in neurosurgery despite its increasing utilization. To address this gap, we conducted a systematic review of the effects of extended reality (XR) in neurosurgery with an emphasis on the perioperative period, to provide a guide for future clinical optimization. Seven primary electronic databases were screened following guidelines outlined by PRISMA and the Institute of Medicine. Reported data related to outcomes in the perioperative period and resident training were all examined, and a focused analysis of studies reporting controlled, clinical outcomes was completed. After removal of duplicates, 2548 studies were screened with 116 studies reporting measurable effects of XR in neurosurgery. The majority (82%) included cranial based applications related to tumor surgery with 34% showing improved resection rates and functional outcomes. A rise in high-quality studies was identified from 2017 to 2020 compared to all previous years (p = 0.004). Primary users of the technology were: 56% neurosurgeon (n = 65), 28% residents (n = 33) and 5% patients (n = 6). A final synthesis was conducted on 10 controlled studies reporting patient outcomes. XR technologies have demonstrated benefits in preoperative planning and multimodal neuronavigation especially for tumor surgery. However, few studies have reported patient outcomes in a controlled design demonstrating a need for higher quality data. XR platforms offer several advantages to improve patient outcomes and specifically, the patient experience for neurosurgery.

A Network-Based Approach to Glioma Surgery: Insights from Functional Neurosurgery

Simple Summary

This manuscript details the literature and discussion around revolutionizing the neurosurgeon’s approach to surgery for brain tumors by conceptualizing these tumors as entities within functional networks. We hope that the work detailed herein will aid in establishing neurosurgical paradigms to optimize planning for brain tumor surgery to improve functional outcomes for all patients.

Abstract

The evaluation and manipulation of structural and functional networks, which has been integral to advancing functional neurosurgery, is beginning to transcend classical subspecialty boundaries. Notably, its application in neuro-oncologic surgery has stimulated an exciting paradigm shift from the traditional localizationist approach, which is lacking in nuance and optimization. This manuscript reviews the existing literature and explores how structural and functional connectivity analyses have been leveraged to revolutionize and individualize pre-operative tumor evaluation and surgical planning. We describe how this novel approach may improve cognitive and neurologic preservation after surgery and attenuate tumor spread. Furthermore, we demonstrate how connectivity analysis combined with neuromodulation techniques can be employed to induce post-operative neuroplasticity and personalize neurorehabilitation. While the landscape of functional neuro-oncology is still evolving and requires further study to encourage more widespread adoption, this functional approach can transform the practice of neuro-oncologic surgery and improve the care and outcomes of patients with intra-axial tumors.