CNTM-04. Alterations in structural connectomic properties associated with neurocognitive changes following glioma resection

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi225-vi225
Author(s):  
Kyle Noll ◽  
Drew Mitchell ◽  
Henry Chen ◽  
Jeffrey Wefel ◽  
Vinodh Kumar ◽  
...  
Keyword(s):  
Verbal Memory ◽  
Diffusion Tensor ◽  
Rank Order ◽  
Tumor Resection ◽  
Receptive Language ◽  
Clustering Coefficient ◽  
Medium Effect ◽  
Postoperative Changes ◽  
Structural Network ◽  
Network Properties

Abstract BACKGROUND Patients with brain tumors often experience decline in neurocognitive functioning (NCF) following surgical tumor resection. Connectomic studies have begun to uncover how abnormalities to underlying cerebral networks contribute to NCF deficits; however, few studies have investigated relationships between pre- to postoperative changes in structural connectomics and NCF. METHODS Fifteen right-handed adults with left perisylvian tumors underwent MRI of the brain with diffusion tensor imaging (DTI) and neuropsychological assessment before and after awake tumor resection. Graph theoretical analysis was applied to DTI-derived connectivity matrices to calculate structural network properties. Structural network properties and NCF measures were compared across the pre- to postoperative periods with matched pairs Wilcoxon signed-rank tests. Associations between pre- to postoperative change in network properties and change in NCF were determined with Spearman rank-order correlations (ρ). RESULTS Nearly 90% of the sample showed postoperative decline on 1 or more NCF measures. Significant postoperative NCF decline was found across measures of verbal memory, processing speed, executive functioning, receptive language, and the Clinical Trial Battery Composite (CTB COMP) index. Regarding connectomic properties, significant postoperative changes were observed in global and local efficiency, characteristic path length, clustering coefficient, betweenness centrality, and assortativity, with medium effect sizes. Significant associations (ρ = .59 to .62, all p < .05) were observed between changes in aspects of NCF and connectomic properties. CONCLUSIONS Decline in NCF was common following resection and some postoperative outcomes were associated with changes in structural connectomic properties following surgery.

scholarly journals Alterations in Functional Connectomics Associated With Neurocognitive Changes Following Glioma Resection

Neurosurgery ◽  
2020 ◽  
Author(s):  
Kyle R Noll ◽  
Henry S Chen ◽  
Jeffrey S Wefel ◽  
Vinodh A Kumar ◽  
Ping Hou ◽  
...  
Keyword(s):  
Brain Tumor ◽  
Executive Functioning ◽  
Verbal Memory ◽  
Rank Order ◽  
Verbal Learning ◽  
Tumor Resection ◽  
Receptive Language ◽  
Network Properties ◽  
Brain Tumor Resection ◽  
The Impact

Abstract BACKGROUND Decline in neurocognitive functioning (NCF) often occurs following brain tumor resection. Functional connectomics have shown how neurologic insults disrupt cerebral networks underlying NCF, though studies involving patients with brain tumors are lacking. OBJECTIVE To investigate the impact of brain tumor resection upon the connectome and relationships with NCF outcome in the early postoperative period. METHODS A total of 15 right-handed adults with left perisylvian glioma underwent resting-state functional magnetic resonance imaging (rs-fMRI) and neuropsychological assessment before and after awake tumor resection. Graph theoretical analysis was applied to rs-fMRI connectivity matrices to calculate network properties. Network properties and NCF measures were compared across the pre- to postoperative periods with matched pairs Wilcoxon signed-rank tests. Associations between pre- to postoperative change in network and NCF measures were determined with Spearman rank-order correlations (ρ). RESULTS A majority of the sample showed postoperative decline on 1 or more NCF measures. Significant postoperative NCF decline was found across measures of verbal memory, processing speed, executive functioning, receptive language, and a composite index. Regarding connectomic properties, betweenness centrality and assortativity were significantly smaller postoperatively, and reductions in these measures were associated with better NCF outcomes. Significant inverse associations (ρ = −.51 to −.78, all P < .05) were observed between change in language, executive functioning, and learning and memory, and alterations in segregation, centrality, and resilience network properties. CONCLUSION Decline in NCF was common shortly following resection of glioma involving eloquent brain regions, most frequently in verbal learning/memory and executive functioning. Better postoperative outcomes accompanied reductions in centrality and resilience connectomic measures.

Associations between clinical outcome and tractography based on navigated transcranial magnetic stimulation in patients with language-eloquent brain lesions

2020 ◽  
Vol 132 (4) ◽  
pp. 1033-1042 ◽  
Author(s):  
Nico Sollmann ◽  
Alessia Fratini ◽  
Haosu Zhang ◽  
Claus Zimmer ◽  
Bernhard Meyer ◽  
...  
Keyword(s):  
Transcranial Magnetic Stimulation ◽  
Brain Tumors ◽  
Risk Stratification ◽  
Magnetic Stimulation ◽  
Diffusion Tensor ◽  
Tumor Resection ◽  
Navigated Transcranial Magnetic Stimulation ◽  
Language Mapping ◽  
Significant Difference ◽  
Related Pathway

OBJECTIVENavigated transcranial magnetic stimulation (nTMS) in combination with diffusion tensor imaging fiber tracking (DTI FT) is increasingly used to locate subcortical language-related pathways. The aim of this study was to establish nTMS-based DTI FT for preoperative risk stratification by evaluating associations between lesion-to-tract distances (LTDs) and aphasia and by determining a cut-off LTD value to prevent surgery-related permanent aphasia.METHODSFifty patients with left-hemispheric, language-eloquent brain tumors underwent preoperative nTMS language mapping and nTMS-based DTI FT, followed by tumor resection. nTMS-based DTI FT was performed with a predefined fractional anisotropy (FA) of 0.10, 0.15, 50% of the individual FA threshold (FAT), and 75% FAT (minimum fiber length [FL]: 100 mm). The arcuate fascicle (AF), superior longitudinal fascicle (SLF), inferior longitudinal fascicle (ILF), uncinate fascicle (UC), and frontooccipital fascicle (FoF) were identified in nTMS-based tractography, and minimum LTDs were measured between the lesion and the AF and between the lesion and the closest other subcortical language-related pathway (SLF, ILF, UC, or FoF). LTDs were then associated with the level of aphasia (no/transient or permanent surgery-related aphasia, according to follow-up examinations).RESULTSA significant difference in LTDs was observed between patients with no or only surgery-related transient impairment and those who developed surgery-related permanent aphasia with regard to the AF (FA = 0.10, p = 0.0321; FA = 0.15, p = 0.0143; FA = 50% FAT, p = 0.0106) as well as the closest other subcortical language-related pathway (FA = 0.10, p = 0.0182; FA = 0.15, p = 0.0200; FA = 50% FAT, p = 0.0077). Patients with surgery-related permanent aphasia showed the lowest LTDs in relation to these tracts. Thus, LTDs of ≥ 8 mm (AF) and ≥ 11 mm (SLF, ILF, UC, or FoF) were determined as cut-off values for surgery-related permanent aphasia.CONCLUSIONSnTMS-based DTI FT of subcortical language-related pathways seems suitable for risk stratification and prediction in patients suffering from language-eloquent brain tumors. Thus, the current role of nTMS-based DTI FT might be expanded, going beyond the level of being a mere tool for surgical planning and resection guidance.

scholarly journals Retrospective analysis of hemispheric structural network change as a function of location and size of glioma

2020 ◽  
Author(s):  
Shawn D’Souza ◽  
Lisa Hirt ◽  
David R Ormond ◽  
John A Thompson
Keyword(s):  
Diffusion Tensor Imaging ◽  
White Matter ◽  
Temporal Lobe ◽  
Diffusion Tensor ◽  
Brain Regions ◽  
Structural Network ◽  
Tumour Location ◽  
The Impact ◽  
Tractography Data ◽  
Diffusion Tensor Imaging Tractography

Abstract Gliomas are neoplasms that arise from glial cell origin and represent the largest fraction of primary malignant brain tumours (77%). These highly infiltrative malignant cell clusters modify brain structure and function through expansion, invasion and intratumoral modification. Depending on the growth rate of the tumour, location and degree of expansion, functional reorganization may not lead to overt changes in behaviour despite significant cerebral adaptation. Studies in simulated lesion models and in patients with stroke reveal both local and distal functional disturbances, using measures of anatomical brain networks. Investigations over the last two decades have sought to use diffusion tensor imaging tractography data in the context of intracranial tumours to improve surgical planning, intraoperative functional localization, and post-operative interpretation of functional change. In this study, we used diffusion tensor imaging tractography to assess the impact of tumour location on the white matter structural network. To better understand how various lobe localized gliomas impact the topology underlying efficiency of information transfer between brain regions, we identified the major alterations in brain network connectivity patterns between the ipsilesional versus contralesional hemispheres in patients with gliomas localized to the frontal, parietal or temporal lobe. Results were indicative of altered network efficiency and the role of specific brain regions unique to different lobe localized gliomas. This work draws attention to connections and brain regions which have shared structural susceptibility in frontal, parietal and temporal lobe glioma cases. This study also provides a preliminary anatomical basis for understanding which affected white matter pathways may contribute to preoperative patient symptomology.

scholarly journals White matter network damage mediates association between cerebrovascular disease and cognition

2021 ◽  
pp. 0271678X2199098
Author(s):  
Saima Hilal ◽  
Siwei Liu ◽  
Tien Yin Wong ◽  
Henri Vrooman ◽  
Ching-Yu Cheng ◽  
...  
Keyword(s):  
White Matter ◽  
Cerebrovascular Disease ◽  
Verbal Memory ◽  
Visual Memory ◽  
Diffusion Tensor ◽  
Mean Diffusivity ◽  
Domain Specific ◽  
Epidemiology Of Dementia ◽  
Z Scores ◽  
White Matter Connectivity

To determine whether white matter network disruption mediates the association between MRI markers of cerebrovascular disease (CeVD) and cognitive impairment. Participants (n = 253, aged ≥60 years) from the Epidemiology of Dementia in Singapore study underwent neuropsychological assessments and MRI. CeVD markers were defined as lacunes, white matter hyperintensities (WMH), microbleeds, cortical microinfarcts, cortical infarcts and intracranial stenosis (ICS). White matter microstructure damage was measured as fractional anisotropy and mean diffusivity by tract based spatial statistics from diffusion tensor imaging. Cognitive function was summarized as domain-specific Z-scores. Lacunar counts, WMH volume and ICS were associated with worse performance in executive function, attention, language, verbal and visual memory. These three CeVD markers were also associated with white matter microstructural damage in the projection, commissural, association, and limbic fibers. Path analyses showed that lacunar counts, higher WMH volume and ICS were associated with executive and verbal memory impairment via white matter disruption in commissural fibers whereas impairment in the attention, visual memory and language were mediated through projection fibers. Our study shows that the abnormalities in white matter connectivity may underlie the relationship between CeVD and cognition. Further longitudinal studies are needed to understand the cause-effect relationship between CeVD, white matter damage and cognition.

Preoperative identification of the facial nerve in patients with large cerebellopontine angle tumors using high-density diffusion tensor imaging

2012 ◽  
Vol 116 (4) ◽  
pp. 697-702 ◽  
Author(s):  
Neil Roundy ◽  
Johnny B. Delashaw ◽  
Justin S. Cetas
Keyword(s):  
Diffusion Tensor Imaging ◽  
Facial Nerve ◽  
Cerebellopontine Angle ◽  
Diffusion Tensor ◽  
Tumor Resection ◽  
High Density ◽  
Imaging Method ◽  
Study Objective ◽  
Nerve Preservation ◽  
Imaging Results

Object Facial nerve paresis can be a devastating complication following resection of large (> 2.5 cm) cerebellopontine angle (CPA) tumors. The authors have developed and used a new high-density diffusion tensor imaging (HD-DT imaging) method, aimed at preoperatively identifying the location and course of the facial nerve in relation to large CPA tumors. Their study objective was to preoperatively identify the facial nerve in patients with large CPA tumors and compare their HD-DT imaging method with a traditional standard DT imaging method and correlate with intraoperative findings. Methods The authors prospectively studied 5 patients with large (> 2.5 cm) CPA tumors. All patients underwent preoperative traditional standard- and HD-DT imaging. Imaging results were correlated with intraoperative findings. Results Utilizing their HD-DT imaging method, the authors positively identified the location and course of the facial nerve in all patients. In contrast, using a standard DT imaging method, the authors were unable to identify the facial nerve in 4 of the 5 patients. Conclusions The HD-DT imaging method that the authors describe and use has proven to be a powerful, accurate, and rapid method for preoperatively identifying the facial nerve in relation to large CPA tumors. Routine integration of HD-DT imaging in preoperative planning for CPA tumor resection could lead to improved facial nerve preservation.

CNTM-01. Evaluating Traditional and Non-Traditional Eloquent Areas in Patients with Brain Tumors: Large-scale Network Analysis Using a Machine Learning-Based Platform

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi224-vi224
Author(s):  
Alexis Morell ◽  
Daniel Eichberg ◽  
Ashish Shah ◽  
Evan Luther ◽  
Victor Lu ◽  
...  
Keyword(s):  
Machine Learning ◽  
Brain Tumors ◽  
Large Scale ◽  
Diffusion Tensor ◽  
Brain Networks ◽  
Tumor Resection ◽  
Central Executive ◽  
Default Mode ◽  
Eloquent Areas ◽  
Neurologic Deficits

Abstract BACKGROUND Developing mapping tools that allow identification of traditional or non-traditional eloquent areas is necessary to minimize the risk of postoperative neurologic deficits. The objective of our study is to evaluate the use of a novel cloud-based platform that uses machine learning to identify cerebral networks in patients with brain tumors. METHODS We retrospectively included all adult patients who underwent surgery for brain tumor resection or thermal ablation at our Institution between the 16th of February and the 15th of May of 2021. Pre and postoperative contrast-enhanced MRI with T1-weighted and high-resolution Diffusion Tensor Imaging (DTI) sequences were uploaded into the Quicktome platform. After processing the data, we categorized the integrity of seven large-scale brain networks: sensorimotor, visual, ventral attention, central executive, default mode, dorsal attention and limbic. Affected networks were correlated with pre and postoperative clinical data, including neurologic deficits. RESULTS Thirty-five (35) patients were included in the study. The average age of the sample was 63.2 years, and 51.4% (n=18) were females. The most affected network was the central executive network (40%), followed by the dorsal attention and default mode networks (31.4%), while the least affected were the visual (11%) and ventral attention networks (17%). Patients with preoperative deficits showed a significantly higher number of altered networks before the surgery (p=0.021), compared to patients without deficits. In addition, we found that patients without neurologic deficits had an average of 2.06 large-scale networks affected, with 75% of them not being related to traditional eloquent areas as the sensorimotor, language or visual circuits. CONCLUSIONS The Quicktome platform is a practical tool that allows automatic visualization of large-scale brain networks in patients with brain tumors. Although further studies are needed, it may assist in the surgical management of traditional and non-traditional eloquent areas.

scholarly journals A preliminary study of the clinical application of optic pathway diffusion tensor tractography in suprasellar tumor surgery: preoperative, intraoperative, and postoperative assessment

2016 ◽  
Vol 125 (3) ◽  
pp. 759-765 ◽  
Author(s):  
Mohamadreza Hajiabadi ◽  
Madjid Samii ◽  
Rudolf Fahlbusch
Keyword(s):  
Visual Acuity ◽  
Visual Field ◽  
Diffusion Tensor ◽  
Tumor Resection ◽  
Visual Pathway ◽  
Optic Chiasm ◽  
Control Group ◽  
Optic Pathway ◽  
Dti Tractography ◽  
Mass Lesions

OBJECT Visual impairments are the most common objective manifestations of suprasellar lesions. Diffusion tensor imaging (DTI) is a noninvasive MRI modality that depicts the subcortical white matter tracts in vivo. In this study the authors tested the value of visual pathway tractography in comparison with visual field and visual acuity analyses. METHODS This prospective study consisted of 25 patients with progressive visual impairment due to suprasellar mass lesions and 6 control patients with normal vision without such lesions. Visual acuity, visual field, and the optic fundus were examined preoperatively and repeated 1 week and 3 months after surgery. Visual pathway DTI tractography was performed preoperatively, intraoperatively immediately after tumor resection, and 1 week and 3 months after surgery. RESULTS In the control group, pre- and postoperative visual status were normal and visual pathway tractography revealed fibers crossing the optic chiasm without any alteration. In patients with suprasellar lesions, vision improved in 24 of 25. The mean distance between optic tracts in tractography decreased after tumor resection and detectable fibers crossing the optic chiasm increased from 12% preoperatively to 72% postoperatively 3 months after tumor resection, and undetectable fibers crossing the optic chiasm decreased from 88% preoperatively to 27% postoperatively 3 months after tumor resection. Visual improvement after tumor removal 1 week and 3 months after surgery was significantly correlated with the distance between optic tracts in intraoperative tractography (p < 0.01). CONCLUSIONS Visual pathway DTI tractography appears to be a promising adjunct to the standard clinical and paraclinical visual examinations in patients with suprasellar mass lesions. The intraoperative findings, in particular the distance between optic tract fibers, can predict visual outcome after tumor resection. Furthermore, postoperative application of this technique may be useful in following anterior optic pathway recovery.

scholarly journals Multi-scale dynamic mean field model (MDMF) relates resting-state brain dynamics with local cortical excitatory–inhibitory neurotransmitter homeostasis

2021 ◽  
pp. 1-55
Author(s):  
Amit Naskar ◽  
Anirudh Vattikonda ◽  
Gustavo Deco ◽  
Dipanjan Roy ◽  
Arpan Banerjee
Keyword(s):  
Resting State ◽  
Computational Models ◽  
Field Model ◽  
Diffusion Tensor ◽  
Brain Activity ◽  
Mean Field ◽  
Clustering Coefficient ◽  
Brain Dynamics ◽  
Mean Field Model ◽  
Multi Scale

Abstract Previous computational models have related spontaneous resting-state brain activity with local excitatory−inhibitory balance in neuronal populations. However, how underlying neurotransmitter kinetics associated with E-I balance governs resting state spontaneous brain dynamics remains unknown. Understanding the mechanisms by virtue of which fluctuations in neurotransmitter concentrations, a hallmark of a variety of clinical conditions relate to functional brain activity is of critical importance. We propose a multi-scale dynamic mean field model (MDMF) – a system of coupled differential equations for capturing the synaptic gating dynamics in excitatory and inhibitory neural populations as a function of neurotransmitter kinetics. Individual brain regions are modelled as population of MDMF and are connected by realistic connection topologies estimated from Diffusion Tensor Imaging data. First, MDMF successfully predicts resting-state functionalconnectivity. Second, our results show that optimal range of glutamate and GABA neurotransmitter concentrations subserve as the dynamic working point of the brain, that is, the state of heightened metastability observed in empirical blood-oxygen-level dependent signals. Third, for predictive validity the network measures of segregation (modularity and clustering coefficient) and integration (global efficiency and characteristic path length) from existing healthy and pathological brain network studies could be captured by simulated functional connectivity from MDMF model.

Abstract 17426: Pulmonary Vein Isolation ‘Rewires’ Electrical Communications to Enhance Small-world Network Topology During Atrial Fibrillation

Circulation ◽  
2015 ◽  
Vol 132 (suppl_3) ◽  
Author(s):  
Hiroshi Ashikaga ◽  
Jonathan Chrispin ◽  
Degang Wu ◽  
Joshua Garland
Keyword(s):  
Atrial Fibrillation ◽  
Communication Network ◽  
Mutual Information ◽  
Path Length ◽  
Random Network ◽  
Small World ◽  
Clustering Coefficient ◽  
Small World Network ◽  
Z Score ◽  
Network Properties

Recent evidence suggests that pulmonary vein isolation (PVI) may perturb the electrophysiological substrate for maintenance of atrial fibrillation (AF). Our previous work indicates that information theory metrics can quantify electrical communications during arrhythmia. We hypothesized that PVI ‘rewires’ the electrical communication network during AF such that the topology exhibits higher levels of small-world network properties, with higher clustering coefficient and lower path length, than would be expected by chance. Thirteen consecutive patients (n=6 with prior PVI and n=7 without) underwent AF ablation using a 64-electrode basket catheter in the left atrium. Multielectrode recording was performed during AF for 60 seconds, followed by PVI. Mutual information was calculated from the time series between each pair of electrodes using the Kraskov-Stögbauer-Grassberger estimator. The all-to-all mutual information matrix (64x64; Figure, upper panels) was thresholded by the median and standard deviations of mutual information to build a binary adjacency matrix for electrical communication networks. The properties of small-world network ( swn ; ‘small-world-ness’) were quantified by the ratio of the observed average clustering coefficient to that of a random network over the ratio of the observed average path length to that of a random network. swn was expressed in normal Z standard deviation units. As the binarizing threshold increased, the Z-score of swn decreased (Figure, lower panel). However, the Z-score at each threshold value was consistently higher with prior PVI than those without (p<0.05). In conclusion, electrical communication network during AF with prior PVI is associated with higher levels of small-world network properties than those without. This finding supports the concept that PVI perturbs the underlying substrate. In addition, swn of electrical communication network may be a promising metric to quantify substrate modification.

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