Cognitive functioning in glioma patients is related to functional connectivity measures of the non-tumoural hemisphere

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.

Glioblastoma and brain connectivity: the need for a paradigm shift

Despite substantial advances in cancer treatment, for patients with glioblastoma prognosis remains bleak. The emerging field of cancer neuroscience reveals intricate functional interplays between glioblastoma and the cellular architecture of the brain, encompassing neurons, glia, and vessels. New findings underscore the role of structural and functional connections within hierarchical networks, known as the connectome. These connections contribute to the location, spread, and recurrence of a glioblastoma, and a patient's overall survival, revealing a complex interplay between the tumour and the CNS. This mounting evidence prompts a paradigm shift, challenging the perception of glioblastomas as mere foreign bodies within the brain. Instead, these tumours are intricately woven into the structural and functional fabric of the brain. This radical change in thinking holds profound implications for the understanding and treatment of glioblastomas, which could unveil new prognostic factors and surgical strategies and optimise radiotherapy. Additionally, a connectivity approach suggests that non-invasive brain stimulation could disrupt pathological neuron-glioma interactions within specific networks.

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.

Perioperative Neurocognitive Function in Glioma Surgery

PURPOSE OF REVIEW

This review provides a concise overview of the recent literature regarding preoperative and postoperative neurocognitive functioning (NCF) in patients with glioma. Brief discussion also covers contemporary intraoperative brain mapping work, with a focus on potential influence of mapping upon NCF outcomes following awake surgery.

RECENT FINDINGS

Most patients with glioma exhibit preoperative NCF impairment, with severity varying by germ line and tumoral genetics, tumor grade, and lesion location, among other characteristics. Literature regarding postoperative NCF changes is mixed, though numerous studies indicate a majority of patients exhibit immediate and short-term worsening. This is often followed by recovery over several months; however, a substantial portion of patients harbor persisting declines. Decline appears related to surgically-induced structural and functional brain alterations, both local and distal to the tumor and resection cavity. Importantly, NCF decline may be mitigated to some extent by intraoperative brain mapping, including mapping of both language-mediated and nonverbal functions. Research regarding perioperative NCF in patients with glioma has flourished over recent years. While this has increased our understanding of contributors to NCF and risk of decline associated with surgical intervention, more work is needed to better preserve NCF throughout the disease course.

Cognitive functioning in untreated glioma patients: The limited predictive value of clinical variables

BACKGROUND

Previous research identified many clinical variables that are significantly related to cognitive functioning before surgery. It is not clear whether such variables enable accurate prediction for individual patients' cognitive functioning because statistical significance does not guarantee predictive value. Previous studies did not test how well cognitive functioning can be predicted for (yet) untested patients. Furthermore, previous research is limited in that only linear or rank-based methods with small numbers of variables were used.

METHODS

We used various machine learning models to predict preoperative cognitive functioning for 340 patients with glioma across 18 outcome measures. Predictions were made using a comprehensive set of clinical variables as identified from the literature. Model performances and optimized hyperparameters were interpreted. Moreover, Shapley additive explanations were calculated to determine variable importance and explore interaction effects.

RESULTS

Best-performing models generally demonstrated above-random performance. Performance, however, was unreliable for 14 out of 18 outcome measures with predictions worse than baseline models for a substantial number of train-test splits. Best-performing models were relatively simple and used most variables for prediction while not relying strongly on any variable.

CONCLUSIONS

Preoperative cognitive functioning could not be reliably predicted across cognitive tests using the comprehensive set of clinical variables included in the current study. Our results show that a holistic view of an individual patient likely is necessary to explain differences in cognitive functioning. Moreover, they emphasize the need to collect larger cross-center and multimodal data sets.

Working memory performance in glioma patients is associated with functional connectivity between the right dorsolateral prefrontal cortex and default mode network

In healthy subjects, activity in the default mode network (DMN) and the frontoparietal network (FPN) has consistently been associated with working memory (WM). In particular, the dorsolateral prefrontal cortex (DLPFC) is important for WM. The functional-anatomical basis of WM impairment in glioma patients is, however, still poorly understood. We investigated whether WM performance of glioma patients is reflected in resting-state functional connectivity (FC) between the DMN and FPN, additionally focusing on the DLPFC. Resting-state functional MRI data were acquired from 45 glioma patients prior to surgery. WM performance was derived from a pre-operative N-back task. Scans were parcellated into ROIs using both the Gordon and Yeo atlas. FC was calculated as the average Pearson correlation between functional time series. The FC between right DLPFC and DMN was inversely related to WM performance for both the Gordon and Yeo atlas (p = .010). No association was found for FC between left DLPFC and DMN, nor between the whole FPN and DMN. The results are robust and not dependent on atlas choice or tumor location, as they hold for both the Gordon and Yeo atlases, and independently of location variables. Our findings show that WM performance of glioma patients can be quantified in terms of interactions between regions and large-scale networks that can be measured with resting-state fMRI. These group-based results are a necessary step toward development of biomarkers for clinical management of glioma patients, and provide additional evidence that global disruption of the DMN relates to cognitive impairment in glioma patients.

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.

The longitudinal relation between executive functioning and multilayer network topology in glioma patients

Many patients with glioma, primary brain tumors, suffer from poorly understood executive functioning deficits before and/or after tumor resection. We aimed to test whether frontoparietal network centrality of multilayer networks, allowing for integration across multiple frequencies, relates to and predicts executive functioning in glioma. Patients with glioma (n = 37) underwent resting-state magnetoencephalography and neuropsychological tests assessing word fluency, inhibition, and set shifting before (T1) and one year after tumor resection (T2). We constructed binary multilayer networks comprising six layers, with each layer representing frequency-specific functional connectivity between source-localized time series of 78 cortical regions. Average frontoparietal network multilayer eigenvector centrality, a measure for network integration, was calculated at both time points. Regression analyses were used to investigate associations with executive functioning. At T1, lower multilayer integration (p = 0.017) and epilepsy (p = 0.006) associated with poorer set shifting (adj. R2 = 0.269). Decreasing multilayer integration (p = 0.022) and not undergoing chemotherapy at T2 (p = 0.004) related to deteriorating set shifting over time (adj. R2 = 0.283). No significant associations were found for word fluency or inhibition, nor did T1 multilayer integration predict changes in executive functioning. As expected, our results establish multilayer integration of the frontoparietal network as a cross-sectional and longitudinal correlate of executive functioning in glioma patients. However, multilayer integration did not predict postoperative changes in executive functioning, which together with the fact that this correlate is also found in health and other diseases, limits its specific clinical relevance in glioma.

Disparity of Primary and Secondary Language Outcomes in Bilingual Patients Undergoing Resection of Glioma of the Speech-Related Regions

BACKGROUND

The existing data about language recovery in bilingual patients come from few studies on acute lesional deficits like stroke or traumatic injury. Still, little is known about the neuroplasticity potential of bilingual patients who undergo resection of gliomas affecting language-eloquent brain regions. In this study, we prospectively evaluated the pre- and postoperative language functions among bilinguals with eloquent region gliomas.

METHODS

We have prospectively collected the preoperative, 3-month and 6-month postoperative data from patients with tumors infiltrating the dominant hemisphere language areas during a 15-month period. Validated Persian/Turkish version of Western Aphasia Battery test and Addenbrooke Cognitive Examination were assessed for main language (L1) and second acquired languages (L2) in each visit.

RESULTS

Twenty-two right-handed bilingual patients were enrolled, and language proficiencies were assessed using mixed model analysis. On baseline and postoperative points, L1 had higher scores in all Addenbrooke Cognitive Examination and Western Aphasia Battery subdomains than L2. Both languages had deterioration at 3-month visit; however, L2 was significantly more deteriorated in all domains. At 6-month visit, both L1 and L2 showed recovery; however, L2 recovered to a less extent than L1. The single most parameter affecting the ultimate language outcome in this study was the preoperative functional level of L1.

CONCLUSIONS

This study shows L1 is less vulnerable to operative insults and L2 may be damaged even when L1 is preserved. We would suggest the more sensitive L2 be used as the screening tool and L1 be used for confirmation of positive responses during language mapping.

Neurotoxicity from Old and New Radiation Treatments for Brain Tumors

Research regarding the mechanisms of brain damage following radiation treatments for brain tumors has increased over the years, thus providing a deeper insight into the pathobiological mechanisms and suggesting new approaches to minimize this damage. This review has discussed the different factors that are known to influence the risk of damage to the brain (mainly cognitive disturbances) from radiation. These include patient and tumor characteristics, the use of whole-brain radiotherapy versus particle therapy (protons, carbon ions), and stereotactic radiotherapy in various modalities. Additionally, biological mechanisms behind neuroprotection have been elucidated.

Factors affecting cognitive functions of patients with high-grade gliomas: a systematic review

BACKGROUND

Gliomas make up approximately 26.5% of all primary CNS tumors and 80.7% of malignant tumors. They are classified according to histology, location, and genetics. Grade III and IV gliomas are considered high-grade gliomas (HGGs). The cognitive signs and symptoms are attributed to mass defects depending on location, growth rapidity, and edema. Our purpose is to review the cognitive status of patients diagnosed with HGGs; the effect of treatments including surgical resection, radiotherapy, and chemotherapy; and the predictors of the cognitive status.

METHODS

We utilized the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines as a template for the methodology. A comprehensive literature search was performed from three databases (PubMed, ScienceDirect, and Cochrane Library) for clinical trials and longitudinal studies on patients diagnosed with HGGs assessing their cognitive status.

RESULTS

Thirteen studies were selected among which 9 assessed cognitive function before and after treatment. One assessed the consistency of cognitive complaints and objective cognitive functioning. Three reported factors affecting disease progression and cognitive status. Most HGG patients have impairment in at least one cognitive domain. Treatments including surgical resection or radio-chemotherapy did not impair cognitive status.

DISCUSSION

The cognitive status could be used to assess sub-clinical tumor progression. Factors correlated to cognitive status were tumor location, edema, and grade. Patient characteristics correlated were pre-operative epilepsy, corticosteroid use, and age at the time of diagnosis.

CONCLUSION

Assessment of the cognitive status of HGG patients indicates sub-clinical tumor progression and may be used to assess treatment outcomes.

Presurgical Executive Functioning in Low-Grade Glioma Patients Cannot Be Topographically Mapped

Executive dysfunctions have a high prevalence in low-grade glioma patients and may be the result of structural disconnections of particular subcortical tracts and/or networks. However, little research has focused on preoperative low-grade glioma patients. The frontotemporoparietal network has been closely linked to executive functions and is substantiated by the superior longitudinal fasciculus. The aim of this study was to investigate their role in executive functions in low-grade glioma patients. Patients from two neurological centers were included with IDH-mutated low-grade gliomas. The sets of preoperative predictors were (i) distance between the tumor and superior longitudinal fasciculus, (ii) structural integrity of the superior longitudinal fasciculus, (iii) overlap between tumor and cortical networks, and (iv) white matter disconnection of the same networks. Linear regression and random forest analyses were performed. The group of 156 patients demonstrated significantly lower performance than normative samples and had a higher prevalence of executive impairments. However, both regression and random forest analyses did not demonstrate significant results, meaning that neither structural, cortical network overlap, nor network disconnection predictors explained executive performance. Overall, our null results indicate that there is no straightforward topographical explanation of executive performance in low-grade glioma patients. We extensively discuss possible explanations, including plasticity-induced network-level equipotentiality. Finally, we stress the need for the development of novel methods to unveil the complex and interacting mechanisms that cause executive deficits in low-grade glioma patients.

Presurgical predictors of early cognitive outcome after brain tumor resection in glioma patients

Gliomas are commonly characterized by neurocognitive deficits that strongly impact patients' and caregivers' quality of life. Surgical resection is the mainstay of therapy, and it can also cause cognitive impairment. An important clinical problem is whether patients who undergo surgery will show post-surgical cognitive impairment above and beyond that present before surgery. The relevant rognostic factors are largely unknown. This study aims to quantify the cognitive impairment in glioma patients 1-week after surgery and to compare different pre-surgical information (i.e., cognitive performance, tumor volume, grading, and lesion topography) towards predicting early post-surgical cognitive outcome. We retrospectively recruited a sample of N = 47 patients affected by high-grade and low-grade glioma undergoing brain surgery for tumor resection. Cognitive performance was assessed before and immediately after (∼1 week) surgery with an extensive neurocognitive battery. Multivariate linear regression models highlighted the combination of predictors that best explained post-surgical cognitive impairment. The impact of surgery on cognitive functioning was relatively small (i.e., 85% of test scores across the whole sample indicated no decline), and pre-operative cognitive performance was the main predictor of early post-surgical cognitive outcome above and beyond information from tumor topography and volume. In fact, structural lesion information did not significantly improve the accuracy of prediction made from cognitive data before surgery. Our findings suggest that post-surgery neurocognitive deficits are only partially explained by preoperative brain damage. The present results suggest the possibility to make reliable, individualized, and clinically relevant predictions from relatively easy-to-obtain information.

Hippocampal avoidance prophylactic cranial irradiation (HA-PCI) for small cell lung cancer reduces hippocampal atrophy compared to conventional PCI

BACKGROUND

Reducing radiation dose to the hippocampus with hippocampal avoidance prophylactic cranial irradiation (HA-PCI) is proposed to prevent cognitive decline. It has, however, not been investigated whether hippocampal atrophy is actually mitigated by this approach. Here, we determined whether HA-PCI reduces hippocampal atrophy. Additionally, we evaluated neurotoxicity of (HA-)PCI to other brain regions. Finally, we evaluated associations of hippocampal atrophy and brain neurotoxicity with memory decline.

METHODS

High-quality research MRI scans were acquired in the multicenter, randomized phase 3 trial NCT01780675. Hippocampal atrophy was evaluated for 4 months (57 HA-PCI patients and 46 PCI patients) and 12 months (28 HA-PCI patients and 27 PCI patients) after (HA-)PCI. We additionally studied multimodal indices of brain injury. Memory was assessed with the Hopkins Verbal Learning Test-Revised (HVLT-R).

RESULTS

HA-PCI reduced hippocampal atrophy at 4 months (1.8% for HA-PCI and 3.0% for PCI) and at 12 months (3.0% for HA-PCI and 5.8% for PCI). Both HA-PCI and PCI were associated with considerable reductions in gray matter and normal-appearing white matter, increases in white matter hyperintensities, and brain aging. There were no significant associations between hippocampal atrophy and memory.

CONCLUSIONS

HA-PCI reduces hippocampal atrophy at 4 and 12 months compared to regular PCI. Both types of radiotherapy are associated with considerable brain injury. We did not find evidence for excessive brain injury after HA-PCI relative to PCI. Hippocampal atrophy was not associated with memory decline in this population as measured with HVLT-R. The usefulness of HA-PCI is still subject to debate.

Probing individual-level structural atrophy in frontal glioma patients

Although every glioma patient varies in tumor size, location, histological grade and molecular biomarkers, non-tumoral morphological abnormalities are commonly detected by a statistical comparison among patient groups, missing the information of individual morphological alterations. In this study, we introduced an individual-level structural abnormality detection method for glioma patients and proposed several abnormality indexes to depict individual atrophy patterns. Forty-five patients with a glioma in the frontal lobe and fifty-one age-matched healthy controls participated in the study. Individual structural abnormality maps (SAM) were generated using patients' preoperative T1 images, by calculating the degree of deviation of voxel volume in each patient with the normative model built from healthy controls. Based on SAM, a series of individual abnormality indexes were computed, and their relationship with glioma characteristics was explored. The results demonstrated that glioma patients showed unique non-tumoral atrophy patterns with overlapping atrophy regions mainly located at hippocampus, parahippocampus, amygdala, insula, middle temporal gyrus and inferior temporal gyrus, which are closely related to the human cognitive functions. The abnormality indexes were associated with several molecular biomarkers including isocitrate dehydrogenase (IDH) mutation, 1p/19q co-deletion and telomerase reverse transcriptase (TERT) promoter mutation. Our study provides an effective way to access the individual-level non-tumoral structural abnormalities in glioma patients, which has the potential to significantly improve individualized precision medicine.

Widespread cortical functional disconnection in gliomas: an individual network mapping approach

Assessment of impaired/preserved cortical regions in brain tumours is typically performed via intraoperative direct brain stimulation of eloquent areas or task-based functional MRI. One main limitation is that they overlook distal brain regions or networks that could be functionally impaired by the tumour.

This study aims: 1) to investigate the impact of brain tumours on the cortical synchronization of brain networks measured with resting-state functional magnetic resonance imaging (resting-state networks) both near the lesion and remotely; 2) to test whether potential changes in resting state networks correlate with cognitive status.

The sample included twenty-four glioma patients (mean age 58.1 ± 16.4y) with different pathological staging. We developed a new method for single subject localization of resting state networks abnormalities. First, we derived the spatial pattern of the main resting state networks by means of the group guided independent component analysis. This was informed by a high-resolution resting state networks template derived from an independent sample of healthy controls. Second, we developed a spatial similarity index to measure differences in network topography and strength between healthy controls and individual brain tumour patients. Next, we investigated the spatial relationship between altered networks and tumour location. Finally, multivariate analyses related cognitive scores across multiple cognitive domains (attention, language, memory, decision making) with patterns of multi-network abnormality.

We found that brain gliomas cause broad alterations of resting state networks topography that occurred mainly in structurally normal regions outside the tumour and oedema region. Cortical regions near the tumour often showed normal synchronization. Finally, multi-network abnormalities predicted attention deficits.

Overall, we present a novel method for the functional localization of resting state networks abnormalities in individual glioma patients. These abnormalities partially explain cognitive disabilities and shall be carefully navigated during surgery.

Functional reorganization of contralesional networks varies according to isocitrate dehydrogenase 1 mutation status in patients with left frontal lobe glioma

PURPOSE

The study aimed to assess how isocitrate dehydrogenase 1 (IDH1) mutation status in patients with glioma may alter functional connectivity (FC) in the default mode network (DMN) and fronto-parietal network (FPN).

METHODS

Using resting-state functional magnetic resonance imaging, a seed-based FC analysis was employed to investigate connectivity within and between networks in seventeen patients with IDH1-mutant glioma (IDH1-M), eleven patients with IDH1-wildtype glioma (IDH1-WT), and nineteen healthy controls (HC).

RESULTS

For FC within the DMN, compared to HC, both IDH1-M and IDH1-WT exhibited significantly increased FC between the posterior cingulate cortex (PCC) and the right retrosplenial cortex, right precuneus/cuneus, and right middle cingulate cortex and between the right lateral parietal cortex (LP_R) and the right middle temporal gyrus. For FC within the FPN, compared with HC, IDH1-M showed significantly greater FC between the right posterior parietal cortex (PPC_R) and the right inferior, right medial, and right middle frontal gyrus, and IDH1-WT showed significantly increased FC between the PPC_R and the right middle frontal gyrus. For FC between the DMN and FPN, relative to IDH1-WT and HC, IDH1-M exhibited significantly increased FC between the LP_R and the right superior frontal gyrus and between the PPC_R and the right precuneus/cuneus. In contrast, compared to IDH1-M and HC, IDH1-WT showed significantly reduced FC between the PPC_R and the right angular gyrus.

CONCLUSION

The preliminary findings revealed that there should be differences in the patterns of network reorganization between IDH1-M and IDH1-WT with different growth kinetics.

Individual-specific networks for prediction modelling – A scoping review of methods

Background

Recent advances in biotechnology enable the acquisition of high-dimensional data on individuals, posing challenges for prediction models which traditionally use covariates such as clinical patient characteristics. Alternative forms of covariate representations for the features derived from these modern data modalities should be considered that can utilize their intrinsic interconnection. The connectivity information between these features can be represented as an individual-specific network defined by a set of nodes and edges, the strength of which can vary from individual to individual. Global or local graph-theoretical features describing the network may constitute potential prognostic biomarkers instead of or in addition to traditional covariates and may replace the often unsuccessful search for individual biomarkers in a high-dimensional predictor space.

Methods

We conducted a scoping review to identify, collate and critically appraise the state-of-art in the use of individual-specific networks for prediction modelling in medicine and applied health research, published during 2000–2020 in the electronic databases PubMed, Scopus and Embase.

Results

Our scoping review revealed the main application areas namely neurology and pathopsychology, followed by cancer research, cardiology and pathology (N = 148). Network construction was mainly based on Pearson correlation coefficients of repeated measurements, but also alternative approaches (e.g. partial correlation, visibility graphs) were found. For covariates measured only once per individual, network construction was mostly based on quantifying an individual’s contribution to the overall group-level structure. Despite the multitude of identified methodological approaches for individual-specific network inference, the number of studies that were intended to enable the prediction of clinical outcomes for future individuals was quite limited, and most of the models served as proof of concept that network characteristics can in principle be useful for prediction.

Conclusion

The current body of research clearly demonstrates the value of individual-specific network analysis for prediction modelling, but it has not yet been considered as a general tool outside the current areas of application. More methodological research is still needed on well-founded strategies for network inference, especially on adequate network sparsification and outcome-guided graph-theoretical feature extraction and selection, and on how networks can be exploited efficiently for prediction modelling.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12874-022-01544-6.

Neurocognition and Health-Related Quality of Life Among Patients with Brain Tumors

Patients with brain tumors experience great symptom burden across various domains of functioning, with associated decreases in health-related quality of life and general well-being. Impaired neurocognitive functioning is among the primary concerns of these patients. Unfortunately, most patients will experience such impairment at some point in the disease. However, impaired neurocognitive functioning, symptom burden, and well-being vary according numerous patient-, tumor-, and treatment-related factors. Recent work has furthered our understanding of these contributors to patient functioning and health-related quality of life and also points to various potential targets for prevention and intervention strategies, though more efficacious treatments remain needed.

Dissociation of structural and functional connectomic coherence in glioma patients

With diffuse infiltrative glioma being increasingly recognized as a systemic brain disorder, the macroscopically apparent tumor lesion is suggested to impact on cerebral functional and structural integrity beyond the apparent lesion site. We investigated resting-state functional connectivity (FC) and diffusion-MRI-based structural connectivity (SC) (comprising edge-weight (EW) and fractional anisotropy (FA)) in isodehydrogenase mutated (IDHmut) and wildtype (IDHwt) patients and healthy controls. SC and FC were determined for whole-brain and the Default-Mode Network (DMN), mean intra- and interhemispheric SC and FC were compared across groups, and partial correlations were analyzed intra- and intermodally. With interhemispheric EW being reduced in both patient groups, IDHwt patients showed FA decreases in the ipsi- and contralesional hemisphere, whereas IDHmut patients revealed FA increases in the contralesional hemisphere. Healthy controls showed strong intramodal connectivity, each within the structural and functional connectome. Patients however showed a loss in structural and reductions in functional connectomic coherence, which appeared to be more pronounced in IDHwt glioma patients. Findings suggest a relative dissociation of structural and functional connectomic coherence in glioma patients at the time of diagnosis, with more structural connectomic aberrations being encountered in IDHwt glioma patients. Connectomic profiling may aid in phenotyping and monitoring prognostically differing tumor types.

Hemisphere-Specific Functional Remodeling and Its Relevance to Tumor Malignancy of Cerebral Glioma Based on Resting-State Functional Network Analysis

BACKGROUND

Functional remodeling may vary with tumor aggressiveness of glioma. Investigation of the functional remodeling is expected to provide scientific relevance of tumor characterization and disease management of glioma. In this study, we aimed to investigate the functional remodeling of the contralesional hemisphere and its utility in predicting the malignant grade of glioma at the individual level with multivariate logistic regression (MLR) analysis.

SUBJECTS AND METHODS

One hundred and twenty-six right-handed subjects with histologically confirmed cerebral glioma were included with 80 tumors located in the left hemisphere (LH) and 46 tumors located in the right hemisphere (RH). Resting-state functional networks of the contralesional hemisphere were constructed using the human brainnetome atlas based on resting-state fMRI data. Functional connectivity and topological features of functional networks were quantified. The performance of functional features in predicting the glioma grade was evaluated using area under (AUC) the receiver operating characteristic curve (ROC). The dataset was divided into training and validation datasets. Features with high AUC values in malignancy classification in the training dataset were determined as predictive features. An MLR model was constructed based on predictive features and its classification performance was evaluated on the training and validation datasets with 10-fold cross validation.

RESULTS

Predictive functional features showed apparent hemispheric specifications. MLR classification models constructed with age and predictive functional connectivity features (AUC of 0.853 ± 0.079 and 1.000 ± 0.000 for LH and RH group, respectively) and topological features (AUC of 0.788 ± 0.150 and 0.897 ± 0.165 for LH and RH group, respectively) achieved efficient performance in predicting the malignant grade of gliomas.

CONCLUSION

Functional remodeling of the contralesional hemisphere was hemisphere-specific and highly predictive of the malignant grade of glioma. Network approach provides a novel pathway that may innovate glioma characterization and management at the individual level.

Distributed changes of the functional connectome in patients with glioblastoma

Glioblastoma might have widespread effects on the neural organization and cognitive function, and even focal lesions may be associated with distributed functional alterations. However, functional changes do not necessarily follow obvious anatomical patterns and the current understanding of this interrelation is limited. In this study, we used resting-state functional magnetic resonance imaging to evaluate changes in global functional connectivity patterns in 15 patients with glioblastoma. For six patients we followed longitudinal trajectories of their functional connectome and structural tumour evolution using bi-monthly follow-up scans throughout treatment and disease progression. In all patients, unilateral tumour lesions were associated with inter-hemispherically symmetric network alterations, and functional proximity of tumour location was stronger linked to distributed network deterioration than anatomical distance. In the longitudinal subcohort of six patients, we observed patterns of network alterations with initial transient deterioration followed by recovery at first follow-up, and local network deterioration to precede structural tumour recurrence by two months. In summary, the impact of focal glioblastoma lesions on the functional connectome is global and linked to functional proximity rather than anatomical distance to tumour regions. Our findings further suggest a relevance for functional network trajectories as a possible means supporting early detection of tumour recurrence.

Brain Functional Network in Chronic Asymptomatic Carotid Artery Stenosis and Occlusion: Changes and Compensation

Asymptomatic carotid artery stenosis (CAS) and occlusion (CAO) disrupt cerebral hemodynamics. There are few studies on the brain network changes and compensation associated with the progression from chronic CAS to CAO. In the current study, our goal is to improve the understanding of the specific abnormalities and compensatory phenomena associated with the functional connection in patients with CAS and CAO. In this prospective study, 27 patients with CAO, 29 patients with CAS, and 15 healthy controls matched for age, sex, education, handedness, and risk factors underwent neuropsychological testing and resting-state functional magnetic resonance (rs-fMRI) imaging simultaneously; graph theoretical analysis of brain networks was performed to determine the relationship between changes in brain network connectivity and the progression from internal CAS to CAO. The global properties of the brain network assortativity (p = 0.002), hierarchy (p = 0.002), network efficiency (p = 0.011), and small-worldness (p = 0.009) were significantly more abnormal in the CAS group than in the control and CAO groups. In patients with CAS and CAO, the nodal efficiency of key nodes in multiple brain regions decreased, while the affected hemisphere lost many key functional connections. In this study, we found that patients with CAS showed grade reconstruction, invalid connections, and other phenomena that impaired the efficiency of information transmission in the brain network. A compensatory functional connection in the contralateral cerebral hemisphere of patients with CAS and CAO may be an important mechanism that maintains clinical asymptomatic performance. This study not only reveals the compensation mechanism of cerebral hemisphere ischemia but also validates previous explanations for brain function connectivity, which can help provide interventions in advance and reduce the impairment of higher brain functions. This trial is registered with Clinical Trial Registration-URL http://www.chictr.org.cn and Unique identifier ChiCTR1900023610.

Impaired neurocognitive function in glioma patients: from pathophysiology to novel intervention strategies

PURPOSE OF REVIEW

This review succinctly summarizes the recent literature regarding etiological contributors to impaired neurocognitive function (NCF) in adult patients with glioma. A brief overview of intervention and prevention strategies is also provided.

RECENT FINDINGS

A majority of patients with glioma exhibit NCF deficits, most frequently in memory and executive functioning. Impairments are often disabling and associated with reduced quality of life and survival. Cause is multifactorial and includes the tumour itself, treatments received and associated comorbidities. Although modern techniques such as brain mapping, dosing modifications and prophylactic medication aim to improve the NCF outcomes following neurosurgical resection and radiation therapy, a sizeable proportion of patients continue to evidence treatment-related NCF declines related to adverse effects to both local and distributed cerebral networks. Numerous patient and tumour characteristics, including genetic markers and sociodemographic factors, influence the pattern and severity of NCF impairment. Some rehabilitative and pharmacologic approaches show promise in mitigating NCF impairment in this population, though benefits are somewhat modest and larger scale intervention studies are needed.

SUMMARY

Research regarding NCF in patients with glioma has dramatically proliferated, providing insights into the mechanisms underlying impaired NCF and pointing to potential interventions, though further work is needed.

Asymmetric tumor-related alterations of network-specific intrinsic functional connectivity in glioma patients

Resting-state functional MRI (rs-fMRI) allows mapping temporally coherent brain networks, and intra- and inter-network alterations have been described in different diseases. This prospective study investigated hemispheric resting-state functional connectivity (RSFC) differences in the default-mode network (DMN) and fronto-parietal network (FPN) between patients with left- and right-hemispheric gliomas (LH PAT, RH PAT), addressing asymmetry effects the tumor might have on network-specific intrinsic functional connectivity under consideration of the prognostically relevant isocitrate-dehydrogenase (IDH) mutation status. Twenty-seven patients (16 LH PAT, 12 IDH-wildtype) and 27 healthy controls underwent anatomical and rs-fMRI as well as neuropsychological assessment. Independent component analyses were performed to identify the DMN and FPN. Hemispheric DMN- and FPN-RSFC were computed, compared across groups, and correlated with cognitive performance. Patient groups did not differ in tumor volume, grade or location. RH PAT showed higher contra-tumoral DMN-RSFC than controls and LH PAT. With regard to the FPN, contra-tumoral RSFC was increased in both patient groups as compared to controls. Higher contra-tumoral RSFC was associated with worse cognitive performance in patients, which, however, seemed to apply mainly to IDH-wildtype patients. The benefit of RSFC alterations for cognitive performance varied depending on the affected hemisphere, cognitive demand, and seemed to be altered by IDH-mutation status. At the time of study initiation, a clinical trial registration was not mandatory at our faculty, but it can be applied for if requested.

Presurgical Identification of Patients With Glioblastoma at Risk for Cognitive Impairment at 3-Month Follow-up

BACKGROUND

Pre- and postoperative cognitive deficits have repeatedly been demonstrated in patients with glioblastoma (GBM).

OBJECTIVE

To identify presurgical risk factors that facilitate the identification of GBM patients at risk for postoperative cognitive impairment.

METHODS

Patients underwent neuropsychological assessment using Central Nervous System Vital Signs 1 d before (T0) and 3 mo after surgery (T3). Patients’ standardized scores on 7 cognitive domains were compared to a normative sample using one-sample z tests. Reliable change indices with correction for practice effects were calculated to assess cognitive changes in individual patients over time. Logistic regression models were performed to assess presurgical sociodemographic, clinical, psychological, and cognitive risk factors for postoperative cognitive impairments.

RESULTS

At T0, 208 patients were assessed, and 136 patients were retested at T3. Patients showed significantly lower performance both prior to and 3 mo after surgery on all cognitive domains compared to healthy controls. Improvements and declines over time occurred respectively in 11% to 32% and 6% to 26% of the GBM patients over the domains. The regression models showed that low preoperative cognitive performance posits a significant risk factor for postoperative cognitive impairment on all domains, and female sex was a risk factor for postoperative impairments in Visual Memory.

CONCLUSION

We demonstrated preoperative cognitive risk factors that enable the identification of GBM patients who are at risk for cognitive impairment 3 mo after surgery. This information can help to inform patients and clinicians at an early stage, and emphasizes the importance of recognizing, assessing, and actively dealing with cognitive functioning in the clinical management of GBM patients.

Role of the default mode resting-state network for cognitive functioning in malignant glioma patients following multimodal treatment

BACKGROUND

Progressive cognitive decline following multimodal neurooncological treatment is a common observation in patients suffering from malignant glioma. Alterations of the default-mode network (DMN) represent a possible source of impaired neurocognitive functioning and were analyzed in these patients.

METHODS

Eighty patients (median age, 51 years) with glioma (WHO grade IV glioblastoma, n = 57; WHO grade III anaplastic astrocytoma, n = 13; WHO grade III anaplastic oligodendroglioma, n = 10) and ECOG performance score 0-1 underwent resting-state functional MRI (rs-fMRI) and neuropsychological testing at a median interval of 13 months (range, 1-114 months) after initiation of therapy. For evaluation of structural and metabolic changes after treatment, anatomical MRI and amino acid PET using O-(2-[18F]fluoroethyl)-L-tyrosine (FET) were simultaneously acquired to rs-fMRI on a hybrid MR/PET scanner. A cohort of 80 healthy subjects matched for gender, age, and educational status served as controls.

RESULTS

The connectivity pattern within the DMN (12 nodes) of the glioma patients differed significantly from that of the healthy subjects but did not depend on age, tumor grade, time since treatment initiation, presence of residual/recurrent tumor, number of chemotherapy cycles received, or anticonvulsive medication. Small changes in the connectivity pattern were observed in patients who had more than one series of radiotherapy. In contrast, structural tissue changes located at or near the tumor site (including resection cavities, white matter lesions, edema, and tumor tissue) had a strong negative impact on the functional connectivity of the adjacent DMN nodes, resulting in a marked dependence of the connectivity pattern on tumor location. In the majority of neurocognitive domains, glioma patients performed significantly worse than healthy subjects. Correlation analysis revealed that reduced connectivity in the left temporal and parietal DMN nodes was associated with low performance in language processing and verbal working memory. Furthermore, connectivity of the left parietal DMN node also correlated with processing speed, executive function, and verbal as well as visual working memory. Overall DMN connectivity loss and cognitive decline were less pronounced in patients with higher education.

CONCLUSION

Personalized treatment strategies for malignant glioma patients should consider the left parietal and temporal DMN nodes as vulnerable regions concerning neurocognitive outcome.

Cognitive functioning in glioma patients is related to functional connectivity measures of the non-tumoural hemisphere

Previous studies have shown that cognitive functioning in patients with brain tumour is associated with the functional network characteristics of specific resting‐state networks or with whole‐brain network characteristics. These studies, however, did not acknowledge the functional contribution of areas in the contralesional, non‐tumoural hemisphere, even though these healthy remote areas likely play a critical role in compensating for the loss of function in damaged tissue. In the current study, we examined whether there is an association between cognitive performance and functional network features of the contralesional hemisphere of patients with glioma. We found that local efficiency of the contralesional hemisphere was associated with performance on the reaction time domain, whereas contralesional assortativity was associated with complex attention and cognitive flexibility scores. Our results suggest that a less segregated organization of the contralesional hemisphere is associated with better reaction time scores, whereas a better spread of information over the contralesional hemisphere through mutually interconnected contralesional hubs is associated with better cognitive flexibility and better complex attention scores. These findings urge researchers to recognize the functional contribution of remote, undamaged regions and to focus more on the graph metrics of the contralesional hemisphere in the search for predictors of cognitive functioning in patients with brain tumour.