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

Brain network topology and its cognitive impact in adult glioma survivors

Structural brain network topology can be altered in case of a brain tumor, due to both the tumor itself and its treatment. In this study, we explored the role of structural whole-brain and nodal network metrics and their association with cognitive functioning. Fifty WHO grade 2-3 adult glioma survivors (> 1-year post-therapy) and 50 matched healthy controls underwent a cognitive assessment, covering six cognitive domains. Raw cognitive assessment scores were transformed into w-scores, corrected for age and education. Furthermore, based on multi-shell diffusion-weighted MRI, whole-brain tractography was performed to create weighted graphs and to estimate whole-brain and nodal graph metrics. Hubs were defined based on nodal strength, betweenness centrality, clustering coefficient and shortest path length in healthy controls. Significant differences in these metrics between patients and controls were tested for the hub nodes (i.e. n = 12) and non-hub nodes (i.e. n = 30) in two mixed-design ANOVAs. Group differences in whole-brain graph measures were explored using Mann-Whitney U tests. Graph metrics that significantly differed were ultimately correlated with the cognitive domain-specific w-scores. Bonferroni correction was applied to correct for multiple testing. In survivors, the bilateral putamen were significantly less frequently observed as a hub (pbonf < 0.001). These nodes' assortativity values were positively correlated with attention (r(90) > 0.573, pbonf < 0.001), and proxy IQ (r(90) > 0.794, pbonf < 0.001). Attention and proxy IQ were significantly more often correlated with assortativity of hubs compared to non-hubs (pbonf < 0.001). Finally, the whole-brain graph measures of clustering coefficient (r = 0.685), global (r = 0.570) and local efficiency (r = 0.500) only correlated with proxy IQ (pbonf < 0.001). This study demonstrated potential reorganization of hubs in glioma survivors. Assortativity of these hubs was specifically associated with cognitive functioning, which could be important to consider in future modeling of cognitive outcomes and risk classification in glioma survivors.

Multiscale network neuroscience in neuro-oncology: How tumors, brain networks, and behavior connect across scales

Network neuroscience refers to the investigation of brain networks across different spatial and temporal scales, and has become a leading framework to understand the biology and functioning of the brain. In neuro-oncology, the study of brain networks has revealed many insights into the structure and function of cells, circuits, and the entire brain, and their association with both functional status (e.g., cognition) and survival. This review connects network findings from different scales of investigation, with the combined aim of informing neuro-oncological healthcare professionals on this exciting new field and also delineating the promising avenues for future translational and clinical research that may allow for application of network methods in neuro-oncological care.

Network topology in brain tumor patients with and without structural epilepsy: a prospective MEG study

Background

It was proposed that network topology is altered in brain tumor patients. However, there is no consensus on the pattern of these changes and evidence on potential drivers is lacking.

Objectives

We aimed to characterize neurooncological patients' network topology by analyzing glial brain tumors (GBTs) and brain metastases (BMs) with respect to the presence of structural epilepsy.

Methods

Network topology derived from resting state magnetoencephalography was compared between (1) patients and controls, (2) GBTs and BMs, and (3) patients with (PSEs) and without structural epilepsy (PNSEs). Eligible patients were investigated from February 2019 to March 2021. We calculated whole brain (WB) connectivity in six frequency bands, network topological parameters (node degree, average shortest path length, local clustering coefficient) and performed a stratification, where differences in power were identified. For data analysis, we used Fieldtrip, Brain Connectivity MATLAB toolboxes, and in-house built scripts.

Results

We included 41 patients (21 men), with a mean age of 60.1 years (range 23-82), of those were: GBTs (n = 23), BMs (n = 14), and other histologies (n = 4). Statistical analysis revealed a significantly decreased WB node degree in patients versus controls in every frequency range at the corrected level (p1-30Hz = 0.002, pγ = 0.002, pβ = 0.002, pα = 0.002, pθ = 0.024, and pδ = 0.002). At the descriptive level, we found a significant augmentation for WB local clustering coefficient (p1-30Hz = 0.031, pδ = 0.013) in patients compared to controls, which did not persist the false discovery rate correction. No differences regarding networks of GBTs compared to BMs were identified. However, we found a significant increase in WB local clustering coefficient (pθ = 0.048) and decrease in WB node degree (pα = 0.039) in PSEs versus PNSEs at the uncorrected level.

Conclusion

Our data suggest that network topology is altered in brain tumor patients. Histology per se might not, however, tumor-related epilepsy seems to influence the brain's functional network. Longitudinal studies and analysis of possible confounders are required to substantiate these findings.

Neuropsychological monitoring of cognitive function and ICF–based mental components in patients with malignant brain tumours

Background

Cognitive deficits are one of the important clinical features of patients with brain tumours, which can affect up to 30–90% of patients before treatment. The consequence is a significant and rapid degradation of the patient’s intellectual functioning, seizures, paralysis and other symptoms that prevent independent functioning. This results in a reduced quality of life and a psychological crisis not only for the patient but also for their relatives. Maintaining the patient’s function at the highest level for as long as possible is particularly important, given that long-term remission or a cure is unlikely or accompanied by significant disability.

Purpose

This paper aims to provide a narrative review to the neuropsychological procedure for monitoring cognitive function in patients with brain tumours, which may be helpful in developing adequate clinical practice and appropriate management procedures.

Methods

A narrative review was applied to search broadly across disciplines, retrieving literature from several databases (PubMed, Web of Science, and EBSCOhost).

Results

(1) discussing the methodological aspects of neuropsychological tools for monitoring cognitive function in brain tumour patients, (2) identifying the most commonly used tools and (3) their practical applicability according to the cognitive function components of the International Classification of Functioning, Disability and Health (ICF).

Conclusion

This article points to the need to systematise research tools or develop new ones, adapted to diagnostic needs with high psychometric characteristics, with particular attention to memory processes and learning effect. Rehabilitation of patients is also an important issue, which requires the use of adequate tools to assess functional disability. The International Classification of Functioning, Disability and Health (ICF) seems to be useful in this respect. The ICF has the advantage of targeting actions to improve the condition of the individual and to keep them as long as possible in a state of well-being that allows them to function effectively in society or to return to work. This is particularly important in view of the ageing population and the increasing number of diagnoses related to brain tumours.

Network analysis shows decreased ipsilesional structural connectivity in glioma patients

Gliomas that infiltrate networks and systems, such as the motor system, often lead to substantial functional impairment in multiple systems. Network-based statistics (NBS) allow to assess local network differences and graph theoretical analyses enable investigation of global and local network properties. Here, we used network measures to characterize glioma-related decreases in structural connectivity by comparing the ipsi- with the contralesional hemispheres of patients and correlated findings with neurological assessment. We found that lesion location resulted in differential impairment of both short and long connectivity patterns. Network analysis showed reduced global and local efficiency in the ipsilesional hemisphere compared to the contralesional hemispheric networks, which reflect the impairment of information transfer across different regions of a network.

Tumors and their location distinctly alter both local and global brain connectivity within the ipsilesional hemisphere of glioma patients.

Modified Diffusion Tensor Image Processing Pipeline for Archived Studies of Patients With Leukoencephalopathy

BACKGROUND

In archived diffusion tensor imaging (DTI) studies, a reversed-phase encoding (PE) scan required to correct the distortion in single-shot echo-planar imaging (EPI) may not have been acquired. Furthermore, DTI tractography is adversely affected by incorrect white matter segmentation due to leukoencephalopathy (LE). All these issues need to be addressed.

PURPOSE

To propose and evaluate a modified DTI processing pipeline with DIstortion COrrection using pseudo T₂ -weighted images (DICOT) to overcome limitations in existing acquisition protocols.

STUDY TYPE

Retrospective feasibility.

SUBJECTS

DICOT was assessed in simulated data and 84 acute lymphoblastic leukemia (ALL) patients with reversed PE acquired. The pipeline was then tested in 522 scans from 261 ALL patients without a reversed PE acquired.

FIELD STRENGTH/SEQUENCE

A 3 T; diffusion-weighted EPI; 3D magnetization prepared rapid acquisition gradient echo (MPRAGE).

STATISTICAL TESTS

Repeated measures analysis of variance and Tukey post hoc tests were performed to compare fractional anisotropy (FA) values obtained by different methods.

ASSESSMENT

FA and corresponding absolute error maps were obtained using TOPUP, DICOT, INVERSION (Inverse contrast Normalization for VERy Simple registratION) and NO CORR (no correction). Each method was assessed by comparing to TOPUP. The pipeline in the ALL patients was evaluated based on the failure rate of the distortion correction using the global correlation values.

RESULTS

Using DICOT reduced the mean absolute errors by an average of 32% in FA in simulation datasets. In 84 patients, the error reductions were approximately 15% in FA with DICOT, while it was 5% with INVERSION. No significant differences between the TOPUP and DICOT were observed in FA with P = 0.090/0.894(AP/PA). Only 15 of 516 examinations requiring any additional manual intervention.

CONCLUSION

This modified pipeline produced better results than the INVERSION. Furthermore, robust performance was demonstrated in archived patient scans acquired without an inverse PE necessary for TOPUP correction.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 2.