Shared and malignancy-specific functional plasticity of dynamic brain properties for patients with left frontal glioma.

The time-varying brain activity may parallel the disease progression of cerebral glioma. Assessment of brain dynamics would better characterize the pathological profile of glioma and the relevant functional remodeling. This study aims to investigate the dynamic properties of functional networks based on sliding-window approach for patients with left frontal glioma. The generalized functional plasticity due to glioma was characterized by reduced dynamic amplitude of low-frequency fluctuation of somatosensory networks, reduced dynamic functional connectivity between homotopic regions mainly involving dorsal attention network and subcortical nuclei, and enhanced subcortical dynamic functional connectivity. Malignancy-specific functional remodeling featured a chaotic modification of dynamic amplitude of low-frequency fluctuation and dynamic functional connectivity for low-grade gliomas, and attenuated dynamic functional connectivity of the intrahemispheric cortico-subcortical connections and reduced dynamic amplitude of low-frequency fluctuation of the bilateral caudate for high-grade gliomas. Network dynamic activity was clustered into four distinct configuration states. The occurrence and dwell time of the weakly connected state were reduced in patients' brains. Support vector machine model combined with predictive dynamic features achieved an averaged accuracy of 87.9% in distinguishing low- and high-grade gliomas. In conclusion, dynamic network properties are highly predictive of the malignant grade of gliomas, thus could serve as new biomarkers for disease characterization.

Multi-scale brain attributes contribute to the distribution of diffuse glioma subtypes.

Gliomas are primary brain tumors and are among the most malignant types. Adult-type diffuse gliomas can be classified based on their histological and molecular signatures as IDH-wildtype glioblastoma, IDH-mutant astrocytoma, and IDH-mutant and 1p/19q-codeleted oligodendroglioma. Recent studies have shown that each subtype of glioma has its own specific distribution pattern. However, the mechanisms underlying the specific distributions of glioma subtypes are not entirely clear despite partial explanations such as cell origin. To investigate the impact of multi-scale brain attributes on glioma distribution, we constructed cumulative frequency maps for diffuse glioma subtypes based on T1w structural images and evaluated the spatial correlation between tumor frequency and diverse brain attributes, including postmortem gene expression, functional connectivity metrics, cerebral perfusion, glucose metabolism, and neurotransmitter signaling. Regression models were constructed to evaluate the contribution of these factors to the anatomic distribution of different glioma subtypes. Our findings revealed that the three different subtypes of gliomas had distinct distribution patterns, showing spatial preferences toward different brain environmental attributes. Glioblastomas were especially likely to occur in regions enriched with synapse-related pathways and diverse neurotransmitter receptors. Astrocytomas and oligodendrogliomas preferentially occurred in areas enriched with genes associated with neutrophil-mediated immune responses. The functional network characteristics and neurotransmitter distribution also contributed to oligodendroglioma distribution. Our results suggest that different brain transcriptomic, neurotransmitter, and connectomic attributes are the factors that determine the specific distributions of glioma subtypes. These findings highlight the importance of bridging diverse scales of biological organization when studying neurological dysfunction.

Structural changes in eloquent cortex secondary to glioma in sensorimotor area.

This study aims to investigate the structural reorganization in the sensorimotor area of the brain in patients with gliomas, distinguishing between those with impaired and unimpaired strength. Using voxel-based morphometry (VBM) and region of interest (ROI) analysis, gray matter volumes (GMV) were compared in the contralesional primary motor gyrus, primary sensory gyrus, premotor area, bilateral supplementary motor area, and medial Brodmann area 8 (BA8). The results revealed that in patients with right hemisphere gliomas, the right medial BA8 volume was significantly larger in the impaired group than in the unimpaired group, with both groups exceeding the volume in 16 healthy controls (HCs). In patients with left hemisphere gliomas, the right supplementary motor area (SMA) was more pronounced in the impaired group compared to the unimpaired group, and both groups were greater than HCs. Additionally, the volumes of the right medial BA8 in both the impaired group were greater than HCs. Contralateral expansions in the gray matter of hand- and trunk-related cortices of the premotor area, precentral gyrus, and postcentral gyrus were observed compared to HCs. Furthermore, a negative correlation was found between hand Medical Research Council (MRC) score and volumes of the contralateral SMA and bilateral medial BA8. Notably, our findings reveal consistent results across both analytical approaches in identifying significant structural reorganizations within the sensorimotor cortex. These consistent findings underscore the adaptive neuroplastic responses to glioma presence, highlighting potential areas of interest for further neurosurgical planning and rehabilitation strategies.

Decreasing distance from tumor to the language network causes language deficit.

Preoperative language deficits are associated with alterations in the language networks of patients with gliomas. This study investigated how gliomas affect language performance by altering the language network. Ninety patients with lower-grade gliomas were included, and their preoperative language performance was evaluated using the Western Aphasia Battery. We also calculated the topological properties based on resting state functional magnetic resonance imaging. All patients were classified according to aphasia quotient (AQ) into the aphasia (AQ < 93.8), mild anomia (AQ > 93.8 and naming section <9.8), and normal groups (AQ > 93.8). The shortest distance from the tumor to the language network (SDTN) was evaluated to identify the effect on language performance induced by the tumor. One-way analysis of variance and post hoc analysis with Sidak correction were used to analyze the differences in topological properties among the three groups. Causal mediation analysis was used to identify indirectly affected mediators. Compared with the mild anomia group, longer shortest path length (p = .0016), lower vulnerability (p = .0331), and weaker nodal efficiencies of three nodes (right caudal Brodmann area [BA] 45, right caudal BA 22, and left BA 41/42, all p < .05) were observed in the aphasia group. The SDTN mediated nodal degree centrality and nodal vulnerability (left rostroventral BA 39), which negatively affected the AQs. Conventional language eloquent and mirrored areas participated in the language network alterations induced by gliomas. The SDTN was a mediator that affected the preoperative language status in patients with gliomas.

Personalized fMRI Delineates Functional Regions Preserved within Brain Tumors.

OBJECTIVE: Accumulating evidence from invasive cortical stimulation mapping and noninvasive neuroimaging studies indicates that brain function may be preserved within brain tumors. However, a noninvasive approach to accurately and comprehensively delineate individual-specific functional networks in the whole brain, especially in brain tissues within and surrounding tumors, is still lacking. The purpose of the study is to develop a clinically useful technique that can map functional regions within tumoral brains. METHODS: We developed an individual-specific functional network parcellation approach using resting state functional magnetic resonance imaging (rsfMRI) that effectively captured functional networks within and nearby tumors in 20 patients. We examined the accuracy of the functional maps using invasive cortical stimulation and task response. RESULTS: We found that approximately 33.2% of the tumoral mass appeared to be functionally active and demonstrated robust functional connectivity with non-tumoral brain regions. Functional networks nearby tumors were validated by invasive cortical stimulation mapping. Intratumoral sensorimotor networks mapped by our technique could be distinguished by their distinct cortico-cerebellar connectivity patterns and were consistent with hand movement evoked fMRI task activations. Furthermore, in some patients, cognitive networks that were detected in the tumor mass showed long-distance and distributed functional connectivity. INTERPRETATION: Our noninvasive approach to mapping individual-specific functional networks using rsfMRI represents a promising new tool for identifying regions with preserved functional connectivity within and surrounding brain tumors, and could be used as a complement to presurgical planning for patients undergoing tumor resection surgery. ANN NEUROL 2022;91:353-366.

Development of an integrated predictive model for postoperative glioma-related epilepsy using gene-signature and clinical data.

BACKGROUND: This study aimed to develop an integrated model for predicting the occurrence of postoperative seizures in patients with diffuse high-grade gliomas (DHGGs) using clinical and RNA-seq data. METHODS: Patients with DHGGs, who received prophylactic anti-epileptic drugs (AEDs) for three months following surgery, were enrolled into the study. The patients were assigned randomly into training (n = 166) and validation (n = 42) cohorts. Differentially expressed genes (DEGs) were identified based on preoperative glioma-related epilepsy (GRE) history. Least absolute shrinkage and selection operator (LASSO) logistic regression analysis was used to construct a predictive gene-signature for the occurrence of postoperative seizures. The final integrated prediction model was generated using the gene-signature and clinical data. Receiver operating characteristic analysis and calibration curve method were used to evaluate the accuracy of the gene-signature and prediction model using the training and validation cohorts. RESULTS: A seven-gene signature for predicting the occurrence of postoperative seizures was developed using LASSO logistic regression analysis of 623 DEGs. The gene-signature showed satisfactory predictive capacity in the training cohort [area under the curve (AUC) = 0.842] and validation cohort (AUC = 0.751). The final integrated prediction model included age, temporal lobe involvement, preoperative GRE history, and gene-signature-derived risk score. The AUCs of the integrated prediction model were 0.878 and 0.845 for the training and validation cohorts, respectively. CONCLUSION: We developed an integrated prediction model for the occurrence of postoperative seizures in patients with DHGG using clinical and RNA-Seq data. The findings of this study may contribute to the development of personalized management strategies for patients with DHGGs and improve our understanding of the mechanisms underlying GRE in these patients.

Decision system for extent of resection in WHO grade 3 gliomas: a Chinese Glioma Genome Atlas database analysis.

BACKGROUND: Extensive surgical resection has been found to be associated with longer survival in patients with gliomas, but the interactive prognostic value of molecular pathology of the surgical resection is unclear. This study evaluated the impact of molecular pathology and clinical characteristics on the surgical benefit in WHO grade 3 IDH-mutant gliomas. METHODS: Clinical and pathological information of 246 patients with WHO grade 3 IDH-mutant gliomas were collected from the Chinese Glioma Genome Atlas database (2006-2020). The role of the extent of resection on overall survival, stratified by molecular pathology and clinical characteristics, was investigated. We then assessed prognostic factors using a univariate log-rank test and multivariate Cox proportional hazards model in the subgroups. RESULTS: The extent of resection was an independent prognostic factor in the entire cohort, even when adjusted for molecular pathology. Gross total resection was found to be associated with longer survival in all patients and in the astrocytoma group but not in the oligodendroglioma group. Compared with subtotal resections, gross total resections resulted in a longer survival time for astrocytoma patients aged ≤ 45 years. However, there was no survival benefit from total resection in patients with astrocytoma aged > 45 years. CONCLUSIONS: Extensive resection benefits only a proportion of patients with WHO grade 3 IDH-mutant gliomas. Younger patients with astrocytomas had survival benefits from extensive resection. In addition to clinical characteristics (especially age), molecular pathology impacted prognosis in patients with gliomas. Our findings provide guiding information to neurosurgeons while planning surgeries.

Epilepsy-related white matter network changes in patients with frontal lobe glioma.

PURPOSE: Epilepsy is a common symptom in patients with frontal lobe glioma. Tumor-related epilepsy was recently considered a type of network disease. Glioma can severely influence the integrity of the white matter network. The association between white matter network changes and presurgical epilepsy remains unclear in glioma patients. This study aims to identify alterations to the subcortical brain networks caused by glioma and glioma-related epilepsy. METHODS: Sixty-one patients with frontal lobe gliomas were enrolled and stratified into the epileptic and non-epileptic groups. Additionally, 14 healthy participants were enrolled after matching for age, sex, and education level. All participants underwent diffusion tensor imaging. Graph theoretical analysis was applied to reveal topological changes in their white matter networks. Regions affected by tumors were excluded from the analysis. RESULTS: Global efficiency was significantly decreased (p = 0.008), while the shortest path length increased (p = 0.02) in the left and right non-epileptic groups compared to the controls. A total of five edges exhibited decreased fiber count in the non-epileptic group (p < 0.05, false discovery rate-corrected). The topological properties and connectional edges showed no significant differences when comparing the epileptic groups and the controls. Additionally, the degree centrality of several nodes connected to the alternated edges was also diminished. CONCLUSIONS: Compared to the controls, the epilepsy groups showed raletively intact WM networks, while the non-epileptsy groups had damaged network with lower efficiency and longer path length. These findings indicated that the occurrence of glioma related epilepsy have association with white matter network intergrity.

Increasing nodal vulnerability and nodal efficiency implied recovery time prolonging in patients with supplementary motor area syndrome.

Supplementary motor area (SMA) syndrome is a surgery-related complication that commonly occurs after removing SMA glioma, and needs weeks to recover. However, susceptible factors of patients suffering from SMA syndrome remain unknown. Graphic theory was applied to reveal topological properties of sensorimotor network (SMN) by processing resting-state functional magnetic resonance images in 66 patients with SMA gliomas. Patients were classified into SMA and non-SMA groups based on whether they suffered from SMA syndrome. We collected recovery time and used causal mediation analysis to find association between topological properties and recovery time. Compared with the non-SMA group, higher vulnerability (left: p = .0018; right: p = .0033) and lower fault tolerance (left: p = .0022; right: p = .0248) of the whole SMN were found in the SMA group. Moreover, higher nodal properties of lesional-hemispheric cingulate cortex (nodal efficiency: left, p = .0389; right, p = .0169; nodal vulnerability: left, p = .0185; right, p = .0085) and upper limb region of primary motor cortex (PMC; nodal efficiency: left, p = .0132; right, p = .0001; nodal vulnerability: left, p = .0091; right, p = .0209) were found in the SMA group. Nodal efficiency and nodal vulnerability of cingulate cortex and upper limb region of PMC were important predictors for SMA syndrome occurring and recovery time prolonging. Neurosurgeons should carefully deal with upper limb region of PMC and cingulate cortex, and protect them if these two region were unnecessary to damage during SMA glioma resection.

Micro-Nanocarriers Based Drug Delivery Technology for Blood-Brain Barrier Crossing and Brain Tumor Targeting Therapy.

The greatest obstacle to using drugs to treat brain tumors is the blood-brain barrier (BBB), making it difficult for conventional drug molecules to enter the brain. Therefore, how to safely and effectively penetrate the BBB to achieve targeted drug delivery to brain tumors has been a challenging research problem. With the intensive research in micro- and nanotechnology in recent years, nano drug-targeted delivery technologies have shown great potential to overcome this challenge, such as inorganic nanocarriers, organic polymer-carriers, liposomes, and biobased carriers, which can be designed in different sizes, shapes, and surface functional groups to enhance their ability to penetrate the BBB and targeted drug delivery for brain tumors. In this review, the composition and overcoming patterns of the BBB are detailed, and then the hot research topics of drug delivery carriers for brain tumors in recent years are summarized, and their mechanisms of action on the BBB and the factors affecting drug delivery are described in detail, and the effectiveness of targeted therapy for brain tumors is evaluated. Finally, the challenges and dilemmas in developing brain tumor drug delivery systems are discussed, which will be promising in the future for targeted drug delivery to brain tumors based on micro-nanocarriers technology.