Brain tumors disrupt the resting-state connectome

More widespread functionality of posterior language area in patients with brain tumors

Damage to the posterior language area (PLA), or Wernicke's area causes cortical reorganization in the corresponding regions of the contralateral hemisphere. However, the details of reorganization within the ipsilateral hemisphere are not fully understood. In this context, direct electrical stimulation during awake surgery can provide valuable opportunities to investigate neuromodulation of the human brain in vivo, which is difficult through the non-invasive approaches. Thus, in this study, we aimed to investigate the characteristics of the cortical reorganization of the PLA within the ipsilateral hemisphere. Sixty-two patients with left hemispheric gliomas were divided into groups depending on whether the lesion extended to the PLA. All patients underwent direct cortical stimulation with a picture-naming task. We further performed functional connectivity analyses using resting-state functional magnetic resonance imaging (MRI) in a subset of patients and calculated betweenness centrality, an index of the network importance of brain areas. During direct cortical stimulation, the regions showing positive (impaired) responses in the non-PLA group were localized mainly in the posterior superior temporal gyrus (pSTG), whereas those in the PLA group were widely distributed from the pSTG to the posterior supramarginal gyrus (pSMG). Notably, the percentage of positive responses in the pSMG was significantly higher in the PLA group (47%) than in the non-PLA group (8%). In network analyses of functional connectivity, the pSMG was identified as a hub region with high betweenness centrality in both the groups. These findings suggest that the language area can spread beyond the PLA to the pSMG, a hub region, in patients with lesion progression to the pSTG. The change in the pattern of the language area may be a compensatory mechanism to maintain efficient brain networks.

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.

Cognitive deficits and altered functional brain network organization in pediatric brain tumor patients

Survivors of pediatric brain tumors experience significant cognitive deficits from their diagnosis and treatment. The exact mechanisms of cognitive injury are poorly understood, and validated predictors of long-term cognitive outcome are lacking. Resting state functional magnetic resonance imaging allows for the study of the spontaneous fluctuations in bulk neural activity, providing insight into brain organization and function. Here, we evaluated cognitive performance and functional network architecture in pediatric brain tumor patients. Forty-nine patients (7-18 years old) with a primary brain tumor diagnosis underwent resting state imaging during regularly scheduled clinical visits. All patients were tested with a battery of cognitive assessments. Extant data from 139 typically developing children were used as controls. We found that obtaining high-quality imaging data during routine clinical scanning was feasible. Functional network organization was significantly altered in patients, with the largest disruptions observed in patients who received propofol sedation. Awake patients demonstrated significant decreases in association network segregation compared to controls. Interestingly, there was no difference in the segregation of sensorimotor networks. With a median follow-up of 3.1 years, patients demonstrated cognitive deficits in multiple domains of executive function. Finally, there was a weak correlation between decreased default mode network segregation and poor picture vocabulary score. Future work with longer follow-up, longitudinal analyses, and a larger cohort will provide further insight into this potential predictor.

The dynamic functional connectivity fingerprint of high-grade gliomas

Resting state fMRI has been used in many studies to investigate the impact of brain tumours on functional connectivity (FC). However, these studies have so far assumed that FC is stationary, disregarding the fact that the brain fluctuates over dynamic states. Here we utilised resting state fMRI data from 33 patients with high-grade gliomas and 33 healthy controls to examine the dynamic interplay between resting-state networks and to gain insights into the impact of brain tumours on functional dynamics. By employing Hidden Markov Models, we demonstrated that functional dynamics persist even in the presence of a high-grade glioma, and that patients exhibited a global decrease of connections strength, as well as of network segregation. Furthermore, through a multivariate analysis, we demonstrated that patients' cognitive scores are highly predictive of pathological dynamics, thus supporting our hypothesis that functional dynamics could serve as valuable biomarkers for better understanding the traits of high-grade gliomas.

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.

Fiber Density and Structural Brain Connectome in Glioblastoma Are Correlated With Glioma Cell Infiltration

BACKGROUND

Glioblastoma (GBM) preferred to infiltrate into white matter (WM) beyond the recognizable tumor margin.

OBJECTIVE

To investigate whether fiber density (FD) and structural brain connectome can provide meaningful information about WM destruction and glioma cell infiltration.

METHODS

GBM cases were collected based on inclusion criteria, and baseline information and preoperative MRI results were obtained. GBM lesions were automatically segmented into necrosis, contrast-enhanced tumor, and edema areas. We obtained the FD map to compute the FD and lnFD values in each subarea and reconstructed the structural brain connectome to obtain the topological metrics in each subarea. We also divided the edema area into a nonenhanced tumor (NET) area and a normal WM area based on the contralesional lnFD value in the edema area, and computed the NET ratio.

RESULTS

Twenty-five GBM cases were included in this retrospective study. The FD/lnFD value and topological metrics (aCp, aLp, aEg, aEloc, and ar) were significantly correlated with GBM subareas, which represented the extent of WM destruction and glioma cell infiltration. The FD/lnFD values and topological parameters were correlated with the NET ratio. In particular, the lnFD value in the edema area was correlated with the NET ratio (coefficient, 0.92). Therefore, a larger lnFD value indicates more severe glioma infiltration in the edema area and suggests an extended resection for better clinical outcomes.

CONCLUSION

The FD and structural brain connectome in this study provide a new insight into glioma infiltration and a different consideration of their clinical application in neuro-oncology.

Glioblastoma remodelling of human neural circuits decreases survival

Gliomas synaptically integrate into neural circuits1,2. Previous research has demonstrated bidirectional interactions between neurons and glioma cells, with neuronal activity driving glioma growth1-4 and gliomas increasing neuronal excitability2,5-8. Here we sought to determine how glioma-induced neuronal changes influence neural circuits underlying cognition and whether these interactions influence patient survival. Using intracranial brain recordings during lexical retrieval language tasks in awake humans together with site-specific tumour tissue biopsies and cell biology experiments, we find that gliomas remodel functional neural circuitry such that task-relevant neural responses activate tumour-infiltrated cortex well beyond the cortical regions that are normally recruited in the healthy brain. Site-directed biopsies from regions within the tumour that exhibit high functional connectivity between the tumour and the rest of the brain are enriched for a glioblastoma subpopulation that exhibits a distinct synaptogenic and neuronotrophic phenotype. Tumour cells from functionally connected regions secrete the synaptogenic factor thrombospondin-1, which contributes to the differential neuron-glioma interactions observed in functionally connected tumour regions compared with tumour regions with less functional connectivity. Pharmacological inhibition of thrombospondin-1 using the FDA-approved drug gabapentin decreases glioblastoma proliferation. The degree of functional connectivity between glioblastoma and the normal brain negatively affects both patient survival and performance in language tasks. These data demonstrate that high-grade gliomas functionally remodel neural circuits in the human brain, which both promotes tumour progression and impairs cognition.

Advanced Neuroimaging Approaches to Pediatric Brain Tumors

Simple Summary

After leukemias, brain tumors are the most common cancers in children, and early, accurate diagnosis is critical to improve patient outcomes. Beyond the conventional imaging methods of computed tomography (CT) and magnetic resonance imaging (MRI), advanced neuroimaging techniques capable of both structural and functional imaging are moving to the forefront to improve the early detection and differential diagnosis of tumors of the central nervous system. Here, we review recent developments in neuroimaging techniques for pediatric brain tumors.

Abstract

Central nervous system tumors are the most common pediatric solid tumors; they are also the most lethal. Unlike adults, childhood brain tumors are mostly primary in origin and differ in type, location and molecular signature. Tumor characteristics (incidence, location, and type) vary with age. Children present with a variety of symptoms, making early accurate diagnosis challenging. Neuroimaging is key in the initial diagnosis and monitoring of pediatric brain tumors. Conventional anatomic imaging approaches (computed tomography (CT) and magnetic resonance imaging (MRI)) are useful for tumor detection but have limited utility differentiating tumor types and grades. Advanced MRI techniques (diffusion-weighed imaging, diffusion tensor imaging, functional MRI, arterial spin labeling perfusion imaging, MR spectroscopy, and MR elastography) provide additional and improved structural and functional information. Combined with positron emission tomography (PET) and single-photon emission CT (SPECT), advanced techniques provide functional information on tumor metabolism and physiology through the use of radiotracer probes. Radiomics and radiogenomics offer promising insight into the prediction of tumor subtype, post-treatment response to treatment, and prognostication. In this paper, a brief review of pediatric brain cancers, by type, is provided with a comprehensive description of advanced imaging techniques including clinical applications that are currently utilized for the assessment and evaluation of pediatric brain tumors.

Brain Functional Connectivity in Low- and High-Grade Gliomas: Differences in Network Dynamics Associated with Tumor Grade and Location

Brain tumors lead to modifications of brain networks. Graph theory plays an important role in clarifying the principles of brain connectivity. Our objective was to investigate network modifications related to tumor grade and location using resting-state functional magnetic resonance imaging (fMRI) and graph theory. We retrospectively studied 30 low-grade (LGG), 30 high-grade (HGG) left-hemispheric glioma patients and 20 healthy controls (HC) with rs-fMRI. Tumor location was labeled as: frontal, temporal, parietal, insular or occipital. We collected patients’ clinical data from records. We analyzed whole-brain and hemispheric networks in all patients and HC. Subsequently, we studied lobar networks in subgroups of patients divided by tumor location. Seven graph-theoretical metrics were calculated (FDR p < 0.05). Connectograms were computed for significant nodes. The two-tailed Student t-test or Mann−Whitney U-test (p < 0.05) were used to compare graph metrics and clinical data. The hemispheric network analysis showed increased ipsilateral connectivity for LGG (global efficiency p = 0.03) and decreased contralateral connectivity for HGG (degree/cost p = 0.028). Frontal and temporal tumors showed bilateral modifications; parietal and insular tumors showed only local effects. Temporal tumors led to a bilateral decrease in all graph metrics. Tumor grade and location influence the pattern of network reorganization. LGG may show more favorable network changes than HGG, reflecting fewer clinical deficits.

A Transparent Ultrasound Array for Real-Time Optical, Ultrasound, and Photoacoustic Imaging

Objective and Impact Statement. Simultaneous imaging of ultrasound and optical contrasts can help map structural, functional, and molecular biomarkers inside living subjects with high spatial resolution. There is a need to develop a platform to facilitate this multimodal imaging capability to improve diagnostic sensitivity and specificity. Introduction. Currently, combining ultrasound, photoacoustic, and optical imaging modalities is challenging because conventional ultrasound transducer arrays are optically opaque. As a result, complex geometries are used to coalign both optical and ultrasound waves in the same field of view. Methods. One elegant solution is to make the ultrasound transducer transparent to light. Here, we demonstrate a novel transparent ultrasound transducer (TUT) linear array fabricated using a transparent lithium niobate piezoelectric material for real-time multimodal imaging. Results. The TUT-array consists of 64 elements and centered at ~6 MHz frequency. We demonstrate a quad-mode ultrasound, Doppler ultrasound, photoacoustic, and fluorescence imaging in real-time using the TUT-array directly coupled to the tissue mimicking phantoms. Conclusion. The TUT-array successfully showed a multimodal imaging capability and has potential applications in diagnosing cancer, neurological, and vascular diseases, including image-guided endoscopy and wearable imaging.

Contralesional Sensorimotor Network Participates in Motor Functional Compensation in Glioma Patients

Background

Some gliomas in sensorimotor areas induce motor deficits, while some do not. Cortical destruction and reorganization contribute to this phenomenon, but detailed reasons remain unclear. This study investigated the differences of the functional connectivity and topological properties in the contralesional sensorimotor network (cSMN) between patients with motor deficit and those with normal motor function.

Methods

We retrospectively reviewed 65 patients (32 men) between 2017 and 2020. The patients were divided into four groups based on tumor laterality and preoperative motor status (deficit or non-deficit). Thirty-three healthy controls (18 men) were enrolled after matching for sex, age, and educational status. Graph theoretical measurement was applied to reveal alterations of the topological properties of the cSMN by analyzing resting-state functional MRI.

Results

The results for patients with different hemispheric gliomas were similar. The clustering coefficient, local efficiency, transitivity, and vulnerability of the cSMN significantly increased in the non-deficit group and decreased in the deficit group compared to the healthy group (p < 0.05). Moreover, the nodes of the motor-related thalamus showed a significantly increased nodal efficiency and nodal local efficiency in the non-deficit group and decreased in the deficit group compared with the healthy group (p < 0.05).

Conclusions

We posited the existence of two stages of alterations of the preoperative motor status. In the compensatory stage, the cSMN sacrificed stability to acquire high efficiency and to compensate for impaired motor function. With the glioma growing and the motor function being totally damaged, the cSMN returned to a stable state and maintained healthy hemispheric motor function, but with low efficiency.

Alternations and Applications of the Structural and Functional Connectome in Gliomas: A Mini-Review

In the central nervous system, gliomas are the most common, but complex primary tumors. Genome-based molecular and clinical studies have revealed different classifications and subtypes of gliomas. Neuroradiological approaches have non-invasively provided a macroscopic view for surgical resection and therapeutic effects. The connectome is a structural map of a physical object, the brain, which raises issues of spatial scale and definition, and it is calculated through diffusion magnetic resonance imaging (MRI) and functional MRI. In this study, we reviewed the basic principles and attributes of the structural and functional connectome, followed by the alternations of connectomes and their influences on glioma. To extend the applications of connectome, we demonstrated that a series of multi-center projects still need to be conducted to systemically investigate the connectome and the structural–functional coupling of glioma. Additionally, the brain–computer interface based on accurate connectome could provide more precise structural and functional data, which are significant for surgery and postoperative recovery. Besides, integrating the data from different sources, including connectome and other omics information, and their processing with artificial intelligence, together with validated biological and clinical findings will be significant for the development of a personalized surgical strategy.

Tumor Connectomics: Mapping the Intra-Tumoral Complex Interaction Network Using Machine Learning

The high-level relationships that form complex networks within tumors and between surrounding tissue is challenging and not fully understood. To better understand these tumoral networks, we developed a tumor connectomics framework (TCF) based on graph theory with machine learning to model the complex interactions within and around the tumor microenvironment that are detectable on imaging. The TCF characterization model was tested with independent datasets of breast, brain, and prostate lesions with corresponding validation datasets in breast and brain cancer. The TCF network connections were modeled using graph metrics of centrality, average path length (APL), and clustering from multiparametric MRI with IsoSVM. The Matthews Correlation Coefficient (MCC), Area Under the Curve-ROC, and Precision-Recall (AUC-ROC and AUC-PR) were used for statistical analysis. The TCF classified the breast and brain tumor cohorts with an IsoSVM AUC-PR and MCC of 0.86, 0.63 and 0.85, 0.65, respectively. The TCF benign breast lesions had a significantly higher clustering coefficient and degree centrality than malignant TCFs. Grade 2 brain tumors demonstrated higher connectivity compared to Grade 4 tumors with increased degree centrality and clustering coefficients. Gleason 7 prostate lesions had increased betweenness centrality and APL compared to Gleason 6 lesions with AUC-PR and MCC ranging from 0.90 to 0.99 and 0.73 to 0.87, respectively. These TCF findings were similar in the validation breast and brain datasets. In conclusion, we present a new method for tumor characterization and visualization that results in a better understanding of the global and regional connections within the lesion and surrounding tissue.

Characterization of cortical hemodynamic changes following sensory, visual, and speech activation by intraoperative optical imaging utilizing phase-based evaluation methods

Alterations within cerebral hemodynamics are the intrinsic signal source for a wide variety of neuroimaging techniques. Stimulation of specific functions leads due to neurovascular coupling, to changes in regional cerebral blood flow, oxygenation and volume. In this study, we investigated the temporal characteristics of cortical hemodynamic responses following electrical, tactile, visual, and speech activation for different stimulation paradigms using Intraoperative Optical Imaging (IOI). Image datasets from a total of 22 patients that underwent surgical resection of brain tumors were evaluated. The measured reflectance changes at different light wavelength bands, representing alterations in regional cortical blood volume (CBV), and deoxyhemoglobin (HbR) concentration, were assessed by using Fourier-based evaluation methods. We found a decrease of CBV connected to an increase of HbR within the contralateral primary sensory cortex (SI) in patients that were prolonged (30 s/15 s) electrically stimulated. Additionally, we found differences in amplitude as well as localization of activated areas for different stimulation patterns. Contrary to electrical stimulation, prolonged tactile as well as prolonged visual stimulation are provoking increases in CBV within the corresponding activated areas (SI, visual cortex). The processing of the acquired data from awake patients performing speech tasks reveals areas with increased, as well as areas with decreased CBV. The results lead us to the conclusion, that the CBV decreases in connection with HbR increases in SI are associated to processing of nociceptive stimuli and that stimulation type, as well as paradigm have a nonnegligible impact on the temporal characteristics of the following hemodynamic response.

Tumor BOLD connectivity profile correlates with glioma patients' survival

BACKGROUND

Presence of residual neurovascular activity within glioma lesions have been recently demonstrated via functional MRI (fMRI) along with active electrical synapses between glioma cells and healthy neurons that influence survival. In this study, we aimed to investigate whether gliomas demonstrate synchronized neurovascular activity with the rest of the brain, by measuring Blood Oxygen Level Dependent (BOLD) signal synchronization, that is, functional connectivity (FC), while also testing whether the strength of such connectivity might predict patients' overall survival (OS).

METHODS

Resting-state fMRI scans of patients who underwent pre-surgical brain mapping were analyzed (total sample, n = 54; newly diagnosed patients, n = 18; recurrent glioma group, n = 36). A seed-to-voxel analysis was conducted to estimate the FC signal profile of the tumor mass. A regression model was then built to investigate the potential correlation between tumor FC and individual OS. Finally, an unsupervised, cross-validated clustering analysis was performed including tumor FC and clinical OS predictors (e.g., Karnofsky Performance Status - KPS - score, tumor volume, and genetic profile) to verify the performance of tumor FC in predicting OS with respect to validated radiological, demographic, genetic and clinical prognostic factors.

RESULTS

In both newly diagnosed and recurrent glioma patients a significant pattern of BOLD synchronization between the solid tumor and distant brain regions was found. Crucially, glioma-brain FC positively correlated with variance in individual survival in both newly diagnosed glioma group (r = 0.90-0.96; P < .001; R ² = 81-92%) and in the recurrent glioma group (r = 0.72; P < .001; R ² = 52%), outperforming standard clinical, radiological and genetic predictors.

CONCLUSIONS

Results suggest glioma's synchronization with distant brain regions should be further explored as a possible diagnostic and prognostic biomarker.

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.

Resting-state fMRI detects alterations in whole brain connectivity related to tumor biology in glioma patients

BACKGROUND

Systemic infiltration of the brain by tumor cells is a hallmark of glioma pathogenesis which may cause disturbances in functional connectivity. We hypothesized that aggressive high-grade tumors cause more damage to functional connectivity than low-grade tumors.

METHODS

We designed an imaging tool based on resting-state functional (f)MRI to individually quantify abnormality of functional connectivity and tested it in a prospective cohort of patients with newly diagnosed glioma.

RESULTS

Thirty-four patients were analyzed (World Health Organization [WHO] grade II, n = 13; grade III, n = 6; grade IV, n = 15; mean age, 48.7 y). Connectivity abnormality could be observed not only in the lesioned brain area but also in the contralateral hemisphere with a close correlation between connectivity abnormality and aggressiveness of the tumor as indicated by WHO grade. Isocitrate dehydrogenase 1 (IDH1) mutation status was also associated with abnormal connectivity, with more alterations in IDH1 wildtype tumors independent of tumor size. Finally, deficits in neuropsychological performance were correlated with connectivity abnormality.

CONCLUSION

Here, we suggested an individually applicable resting-state fMRI marker in glioma patients. Analysis of the functional connectome using this marker revealed that abnormalities of functional connectivity could be detected not only adjacent to the visible lesion but also in distant brain tissue, even in the contralesional hemisphere. These changes were associated with tumor biology and cognitive function. The ability of our novel method to capture tumor effects in nonlesional brain suggests a potential clinical value for both individualizing and monitoring glioma therapy.

Glioma-Induced Disruption of Resting-State Functional Connectivity and Amplitude of Low-Frequency Fluctuations in the Salience Network

BACKGROUND AND PURPOSE

Cognitive challenges are prevalent in survivors of glioma, but their neurobiology is incompletely understood. The purpose of this study was to investigate the effect of glioma presence and tumor characteristics on resting-state functional connectivity and amplitude of low-frequency fluctuations of the salience network, a key neural network associated with cognition.

MATERIALS AND METHODS

Sixty-nine patients with glioma (mean age, 48.74 [SD, 14.32] years) who underwent resting-state fMRI were compared with 31 healthy controls (mean age, 49.68 [SD, 15.54] years). We identified 4 salience network ROIs: left/right dorsal anterior cingulate cortex and left/right anterior insula. Average salience network resting-state functional connectivity and amplitude of low-frequency fluctuations within the 4 salience network ROIs were computed.

RESULTS

Patients with gliomas showed decreased overall salience network resting-state functional connectivity (P = .001) and increased amplitude of low-frequency fluctuations in all salience network ROIs (P < .01) except in the left dorsal anterior cingulate cortex. Compared with controls, patients with left-sided gliomas showed increased amplitude of low-frequency fluctuations in the right dorsal anterior cingulate cortex (P = .002) and right anterior insula (P < .001), and patients with right-sided gliomas showed increased amplitude of low-frequency fluctuations in the left anterior insula (P = .002). Anterior tumors were associated with decreased salience network resting-state functional connectivity (P < .001) and increased amplitude of low-frequency fluctuations in the right anterior insula, left anterior insula, and right dorsal anterior cingulate cortex. Patients with high-grade gliomas had decreased salience network resting-state functional connectivity compared with healthy controls (P < .05). The right anterior insula showed increased amplitude of low-frequency fluctuations in patients with grade II and IV gliomas compared with controls (P < .01).

CONCLUSIONS

By demonstrating decreased resting-state functional connectivity and an increased amplitude of low-frequency fluctuations related to the salience network in patients with glioma, this study adds to our understanding of the neurobiology underpinning observable cognitive deficits in these patients. In addition to more conventional functional connectivity, amplitude of low-frequency fluctuations is a promising functional-imaging biomarker of tumor-induced vascular and neural pathology.

The utilisation of resting-state fMRI as a pre-operative mapping tool in patients with brain tumours in comparison to task-based fMRI and intraoperative mapping: A systematic review

PURPOSE

Resting-state functional Magnetic Resonance Imaging (rs-fMRI) is suggested to be a viable option for pre-operative mapping for patients with brain tumours. However, it remains an open issue whether the tool is useful in the clinical setting compared to task-based fMRI (T-fMRI) and intraoperative mapping. Thus, a systematic review was conducted to investigate the usefulness of this technique.

METHODS

A systematic literature search of rs-fMRI methods applied as a pre-operative mapping tool was conducted using the PubMed/MEDLINE and Cochrane Library electronic databases following PRISMA guidelines.

RESULTS

Results demonstrated that 50% (six out of twelve) of the studies comparing rs-fMRI and T-fMRI showed good concordance for both language and sensorimotor networks. In comparison to intraoperative mapping, 86% (six out of seven) studies found a good agreement to rs-fMRI. Finally, 87% (twenty out of twenty-three) studies agreed that rs-fMRI is a suitable and useful pre-operative mapping tool.

CONCLUSIONS

rs-fMRI is a promising technique for pre-operative mapping in assessing the functional brain areas. However, the agreement between rs-fMRI with other techniques, including T-fMRI and intraoperative maps, is not yet optimal. Studies to ascertain and improve the sophistication in pre-processing of rs-fMRI imaging data are needed.

Alterations in Functional Connectomics Associated With Neurocognitive Changes Following Glioma Resection

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.

Effect of brain normalization methods on the construction of functional connectomes from resting-state functional MRI in patients with gliomas

PURPOSE

Spatial normalization is an essential step in resting-state functional MRI connectomic analysis with atlas-based parcellation, but brain lesions can confound it. Cost-function masking (CFM) is a popular compensation approach, but may not benefit modern normalization methods. This study compared three normalization methods with and without CFM and determined their impact on connectomic measures in patients with glioma.

METHODS

Fifty patients with glioma were included. T₁ -weighted images were normalized using three different methods in SPM12, with and without CFM, which were then overlaid on the ICBM152 template and scored by two neuroradiologists. The Dice coefficient of gray-matter correspondence was also calculated. Normalized resting-state functional MRI data were parcellated using the AAL90 atlas to construct an individual connectivity matrix and calculate connectomic measures. The R² among the different normalization methods was calculated for the connectivity matrices and connectomic measures.

RESULTS

The older method (Original) performed significantly worse than the modern methods (Default and DARTEL; P < .005 in observer ranking). The use of CFM did not significantly improve the normalization results. The Original method had lower correlation with the Default and DARTEL methods (R² = 0.71-0.74) than Default with DARTEL (R² = 0.96) in the connectivity matrix. The clustering coefficient appears to be the most, and modularity the least, sensitive connectomic measures to normalization performance.

CONCLUSION

The spatial normalization method can have an impact on resting-state functional MRI connectome and connectomic measures derived using atlas-based brain parcellation. In patients with glioma, this study demonstrated that Default and DARTEL performed better than the Original method, and that CFM made no significant difference.

Homotopic redistribution of functional connectivity in insula-centered diffuse low-grade glioma

OBJECTIVE

In the event of neural injury, the homologous contralateral brain areas may play a compensatory role to avoid or limit the functional loss. However, this dynamic strategy of functional redistribution is not clearly established, especially in the pathophysiological context of diffuse low-grade glioma. Our aim here was to assess the extent to which unilateral tumor infiltration of the insula dynamically modulates the functional connectivity of the contralesional one.

METHODS

Using resting-state functional connectivity MRI, a seed-to-ROI approach was employed in 52 insula-centered glioma patients (n = 30 left and 22 right) compared with 19 age-matched healthy controls.

RESULTS

Unsurprisingly, a significant decrease of the inter-insular connectivity was observed in both patient groups. More importantly, the analyses revealed a significant increase of the contralesional insular connectivity towards both cerebral hemispheres, especially in cortical areas forming the visual and the sensorimotor networks. This functional redistribution was not identified when the analyses were performed on three control regions for which the homologous area was not impaired by the tumor. This overall pattern of results indicates that massive infiltration of the insular cortex causes a significant redeployment of the contralesional functional connectivity.

CONCLUSION

This general finding suggests that the undamaged insula plays a role in the functional compensation usually observed in this patient population, and thus provides compelling support for the concept of homotopic functional plasticity in brain-damaged patients.

The Problem of Neurovascular Uncoupling

Neurovascular uncoupling (NVU) is one of the most important confounds of blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMR imaging) in the setting of focal brain lesions such as brain tumors. This article reviews the assessment of NVU related to focal brain lesions with emphasis on the use of cerebrovascular reactivity mapping measurement methods and resting state BOLD fMR imaging metrics in the detection of NVU, as well as the use of amplitude of low-frequency fluctuation metrics to mitigate the effects of NVU on clinical fMR imaging activation.

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.

Glioma-Induced Alterations in Neuronal Activity and Neurovascular Coupling during Disease Progression

Diffusely infiltrating gliomas are known to cause alterations in cortical function, vascular disruption, and seizures. These neurological complications present major clinical challenges, yet their underlying mechanisms and causal relationships to disease progression are poorly characterized. Here, we follow glioma progression in awake Thy1-GCaMP6f mice using in vivo wide-field optical mapping to monitor alterations in both neuronal activity and functional hemodynamics. The bilateral synchrony of spontaneous neuronal activity gradually decreases in glioma-infiltrated cortical regions, while neurovascular coupling becomes progressively disrupted compared to uninvolved cortex. Over time, mice develop diverse patterns of high amplitude discharges and eventually generalized seizures that appear to originate at the tumors' infiltrative margins. Interictal and seizure events exhibit positive neurovascular coupling in uninfiltrated cortex; however, glioma-infiltrated regions exhibit disrupted hemodynamic responses driving seizure-evoked hypoxia. These results reveal a landscape of complex physiological interactions occurring during glioma progression and present new opportunities for exploring novel biomarkers and therapeutic targets.

HemoSYS: A Toolkit for Image-based Systems Biology of Tumor Hemodynamics

Abnormal tumor hemodynamics are a critical determinant of a tumor’s microenvironment (TME), and profoundly affect drug delivery, therapeutic efficacy and the emergence of drug and radio-resistance. Since multiple hemodynamic variables can simultaneously exhibit transient and spatiotemporally heterogeneous behavior, there is an exigent need for analysis tools that employ multiple variables to characterize the anomalous hemodynamics within the TME. To address this, we developed a new toolkit called HemoSYS for quantifying the hemodynamic landscape within angiogenic microenvironments. It employs multivariable time-series data such as in vivo tumor blood flow (BF), blood volume (BV) and intravascular oxygen saturation (Hb_sat) acquired concurrently using a wide-field multicontrast optical imaging system. The HemoSYS toolkit consists of propagation, clustering, coupling, perturbation and Fourier analysis modules. We demonstrate the utility of each module for characterizing the in vivo hemodynamic landscape of an orthotropic breast cancer model. With HemoSYS, we successfully described: (i) the propagation dynamics of acute hypoxia; (ii) the initiation and dissolution of distinct hemodynamic niches; (iii) tumor blood flow regulation via local vasomotion; (iv) the hemodynamic response to a systemic perturbation with carbogen gas; and (v) frequency domain analysis of hemodynamic heterogeneity in the TME. HemoSYS (freely downloadable via the internet) enables vascular phenotyping from multicontrast in vivo optical imaging data. Its modular design also enables characterization of non-tumor hemodynamics (e.g. brain), other preclinical disease models (e.g. stroke), vascular-targeted therapeutics, and hemodynamic data from other imaging modalities (e.g. MRI).