Individual cerebellar metabolic connectome in patients with MTLE and NTLE associated with surgical prognosis.

PURPOSE: This study aimed to comprehensively explore the different metabolic connectivity topological changes in MTLE and NTLE, as well as their association with surgical outcomes. METHODS: This study enrolled a cohort of patients with intractable MTLE and NTLE. Each individual's metabolic connectome, as determined by Kullback-Leibler divergence similarity estimation for the [18F]FDG PET image, was employed to conduct a comprehensive analysis of the cerebral metabolic network. Alterations in network connectivity were assessed by extracting and evaluating the strength of edge and weighted connectivity. By utilizing these two connectivity strength metrics with the cerebellum, we explored the network properties of connectivity and its association with prognosis in surgical patients. RESULTS: Both MTLE and NTLE patients exhibited substantial alterations in the connectivity of the metabolic network at the edge and nodal levels (p < 0.01, FDR corrected). The key disparity between MTLE and NTLE was observed in the cerebellum. In MTLE, there was a predominance of increased connectivity strength in the cerebellum. Whereas, a decrease in cerebellar connectivity was identified in NTLE. It was found that in MTLE, higher edge connectivity and weighted connectivity strength in the contralateral cerebellar hemisphere correlated with improved surgical outcomes. Conversely, in NTLE, a higher edge metabolic connectivity strength in the ipsilateral cerebellar hemisphere suggested a worse surgical prognosis. CONCLUSION: The cerebellum exhibits distinct topological characteristics in the metabolic networks between MTLE and NTLE. The hyper- or hypo-metabolic connectivity in the cerebellum may be a prognostic biomarker of surgical prognosis, which might aid in therapeutic decision-making for TLE individuals.

Preoperative structural-functional coupling at the default mode network predicts surgical outcomes of temporal lobe epilepsy.

OBJECTIVE: Structural-functional coupling (SFC) has shown great promise in predicting postsurgical seizure recurrence in patients with temporal lobe epilepsy (TLE). In this study, we aimed to clarify the global alterations in SFC in TLE patients and predict their surgical outcomes using SFC features. METHODS: This study analyzed presurgical diffusion and functional magnetic resonance imaging data from 71 TLE patients and 48 healthy controls (HCs). TLE patients were categorized into seizure-free (SF) and non-seizure-free (nSF) groups based on postsurgical recurrence. Individual functional connectivity (FC), structural connectivity (SC), and SFC were quantified at the regional and modular levels. The data were compared between the TLE and HC groups as well as among the TLE, SF, and nSF groups. The features of SFC, SC, and FC were categorized into three datasets: the modular SFC dataset, regional SFC dataset, and SC/FC dataset. Each dataset was independently integrated into a cross-validated machine learning model to classify surgical outcomes. RESULTS: Compared with HCs, the visual and subcortical modules exhibited decoupling in TLE patients (p < .05). Multiple default mode network (DMN)-related SFCs were significantly higher in the nSF group than in the SF group (p < .05). Models trained using the modular SFC dataset demonstrated the highest predictive performance. The final prediction model achieved an area under the receiver operating characteristic curve of .893 with an overall accuracy of .887. SIGNIFICANCE: Presurgical hyper-SFC in the DMN was strongly associated with postoperative seizure recurrence. Furthermore, our results introduce a novel SFC-based machine learning model to precisely classify the surgical outcomes of TLE.

Bilateral glymphatic dysfunction and its association with disease duration in unilateral temporal lobe epilepsy patients with hippocampal sclerosis.

OBJECTIVE: In this study, the diffusion tensor imaging along perivascular space analysis (DTI-ALPS) technique was utilized to evaluate the functional changes in the glymphatic system of the bilateral hemispheres in patients with unilateral temporal lobe epilepsy (TLE) accompanied by hippocampal sclerosis (HS). The aim was to gain insights into the alterations in the glymphatic system function in TLE patients. METHODS: A total of 61 unilateral TLE patients with HS and 53 healthy controls (HCs) from the Department of Neurosurgery at Xiangya Hospital were included in the study. All subjects underwent DTI using the same 3 T MR Scanner, and the DTI-ALPS index was calculated. Differences in the DTI-ALPS index between TLE patients and HCs were evaluated, along with the correlation between the DTI-ALPS index of TLE and clinical features of epilepsy. These features included age, age of onset, seizure duration, and neuropsychological scores. RESULTS: Compared to the bilateral means of the HCs, both the ipsilateral and contralateral DTI-ALPS index of the TLE patients were significantly decreased (TLE ipsilateral 1.41 ± 0.172 vs. HC bilateral mean: 1.49 ± 0.116, p = 0.006; TLE contralateral: 1.42 ± 0.158 vs. HC bilateral mean: 1.49 ± 0.116, p = 0.015). The ipsilateral DTI-ALPS index in TLE patients showed a significant negative correlation with disease duration (r = -0.352, p = 0.005). CONCLUSIONS: The present study suggests the presence of bilateral dysfunctions in the glymphatic system and also highlight a laterality feature in these dysfunctions. Additionally, the study found a significant negative correlation between the ipsilateral DTI-ALPS index and disease duration, underscoring the significance of early effective interventions and indicating potential for the development of innovative treatments targeting the glymphatic system.

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.

Development and validation of a novel survival prediction model for newly diagnosed lower-grade gliomas.

OBJECTIVE: Diffuse gliomas are the most common primary gliomas with a poor prognosis. This study aimed to develop and validate prognostic models for predicting the survival probability in newly diagnosed lower-grade glioma (LGG) patients. METHODS: Detailed data were obtained for newly diagnosed LGG from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) cohorts. Survival was assessed using Cox proportional hazards regression with adjustment for known prognostic factors. The model was established using the TCGA cohort, and independently validated using the CGGA cohort, to predict the 3-, 5-, and 10-year survival probabilities of patients. RESULTS: Data from 293 patients with newly diagnosed LGG from the TCGA cohort were used to establish a prognostic model, and from 232 patients with primary LGG in the CGGA cohort to validate the model. Age, tumor grade, molecular subtype, tumor resection, and preoperative neurological deficits were included in the prediction model. The Cox regression model had a satisfactory corrected concordance index of 0.8508, 0.8510, and 0.8516 in the internal bootstrap validation at 3, 5, and 10 years, respectively. The calibration plots demonstrated high consistency of the predicted and observed outcomes. The CGGA cohort was used for external validation and showed satisfactory discrimination of 0.7776, 0.7682, and 0.7051 at 3, 5, and 10 years, respectively. The calibration plots demonstrated an acceptable calibration capability in the external validation. CONCLUSIONS: This study established and validated a prognostic model to predict the survival probability of patients with newly diagnosed LGG. The model performed well in discrimination and calibration with ease of use, speed, accessibility, interpretability, and generalizability. An easily used nomogram based on the Cox model was established for clinical application. Moreover, a free, easy-to-use software interface based on the nomogram is provided online.

Fortification of set yogurt with passion fruit juice: Effects on fermentation kinetics, physicochemical properties, and functionality.

With the purpose of developing an alternative set yogurt with high consumer acceptability, passion fruit juice, at levels that varied from 0 to 10%, was incorporated into set yogurt, and the effects on the fermentation kinetics, physicochemical properties, and functionality of set yogurt were evaluated. The results showed that the addition of passion fruit juice was simultaneously propitious for milk acidification in earlier fermentation stages and reduced the fermentation rate at later stages of fermentation. The phenolic compounds and pectin in passion fruit juice interacted with caseins to form soluble complexes, enhancing the gel strength of set yogurts by 7.5%. The aroma and flavor of the set yogurt was improved as well. However, with the addition of 10% passion fruit juice, the gel structure was destroyed, and the quality of the set yogurt was very degraded. More importantly, the addition of passion fruit juice increased the polyphenol content and significantly enhanced the antioxidant activity of the set yogurt. This investigation demonstrated the feasibility of fabricating passion fruit juice-enriched set yogurt and its superior quality compared with the corresponding normal product.

Molecular profiles for insular low-grade gliomas with putamen involvement.

BACKGROUND: The newly proposed putamen classification system shows good prognostic value in patients with insular LGGs, yet no study towards the molecular profiles of putamen involved LGGs has been proposed. METHODS: Clinical information and imaging data of patients diagnosed with insular low-grade gliomas were collected retrospectively. Genetic information of the 34 tumors was assessed using RNA-sequencing. Gene set enrichment analysis was further performed to identify the genes showing differential expression between putamen-involved tumors and putamen non-involved tumors. The level of Ki-67 expression was also evaluated. RESULTS: There were 843 genes identified to be differentially expressed between putamen-involved and non-involved gliomas. Specifically, Gene set enrichment analysis discovered 13 Kyoto Encyclopedia of Genes and Genomes pathways and 37 Gene Ontology Biological Process term were upregulated in putamen-involved low-grade glioma cells. The enriched GO sets with the highest gene counts included cell cycle (42 genes), mitotic cell cycle (24 genes), and cell division (19 genes). Furthermore, high expression of Ki-67 was associated with putamen involvement in insular gliomas. CONCLUSIONS: There is clear genetic variation between putamen-involved and non-involved insular low-grade gliomas. The differential expression of genes related to the processes of cell proliferation, cell migration, or DNA repair may lead to putamen involvement. The findings suggest that among the two subtypes, putamen-involved insular low-grade gliomas have higher malignancy, and the clinical treatment towards the putamen-involved insular low-grade gliomas should be more active.

Structural-functional coupling abnormalities in temporal lobe epilepsy.

Background: Nowadays, researchers are using advanced multimodal neuroimaging techniques to construct the brain network connectome to elucidate the complex relationship among the networks of brain functions and structure. The objective of this study was to evaluate the coupling of structural connectivity (SC) and functional connectivity (FC) in the entire brain of healthy controls (HCs), and to investigate modifications in SC-FC coupling in individuals suffering from temporal lobe epilepsy (TLE). Methods: We evaluated 65 patients with TLE matched for age and gender with 48 healthy controls. The SC-FC coupling between regions was determined, based on which whole-brain nodes were clustered. Differences in the coupling among the three groups of nodes were compared. To further validate the results obtained, the within-cluster coupling indices of the three groups were compared to determine the inter-group differences. Results: Nodes were divided into five clusters. Cluster 1 was primarily located in the limbic system (n = 9/27), whereas cluster 5 was mainly within the visual network (n = 12/29). By comparing average cluster SC-FC coupling in each cluster of the three groups, we identified marked discrepancies within the three cohorts in Cluster 3 (p = 0.001), Cluster 4 (p < 0.001), and Cluster 5 (p < 0.001). Post-hoc analysis revealed that the SC-FC coupling strengths in LTLE and RTLE were significantly lower than that in HCs in Cluster 3 (PL = 0.001/PR = 0.003), Cluster 4 (PL = 0.001/PR < 0.001), and Cluster 5 (PL < 0.001/PR < 0.001). We also observed that the within-cluster SC-FC coupling in cluster 5 of left- and right TLE was significantly lower than in HCs (PL = 0.0001, PR = 0.0005). Conclusion: The SC and FC are inconsistently coupled across the brain with spatial heterogeneity. In the fifth cluster with the highest degree of coupling in HCs, the average SC-FC coupling index of individuals with TLE was notably less than that of HCs, manifesting that brain regions with high coupling may be more delicate and prone to pathological disruption.

Microstructural changes of white matter fiber tracts induced by insular glioma revealed by tract-based spatial statistics and automatic fiber quantification.

Gliomas typically grow along white matter fiber tracts, yet their invasion patterns remain unclear. This study assessed the effect of insular glioma on large white matter fiber tracts and the microstructural subcortical changes associated with clinical outcomes in patients with insular glioma. Twenty-five patients with insular glioma were enrolled and divided into left and right groups according to tumor lateralization. The control group comprised 14 healthy volunteers. Subjects in both the glioma and control groups underwent diffusion tensor magnetic resonance imaging at 3.0 T. The characteristics of white matter fiber bundles were analyzed using tract-based spatial statistics and automatic fiber quantification. Both Automatic Fiber Quantification and Tract-Based Spatial Statistics revealed that patients with insular glioma had significantly lower fractional anisotropy (FA) values in the inferior frontal-occipital fasciculus and uncinate fasciculus ipsilateral to the tumor, than the controls. Fractional anisotropy associated with mean diffusivity values several large fiber tracts showed potential on tumor-grade distinguishing. Diffusion metrics can sensitively detect microstructural changes in tumor progression. Insular glioma significantly affects the microstructure of white matter fibers proximal to the tumor. The range of white matter fiber bundles affected differs according to the grade of the glioma. These changes are mainly associated with early-stage tumor invasion.

Characteristics of Microstructural Changes Associated with Glioma Related Epilepsy: A Diffusion Tensor Imaging (DTI) Study.

(1) Background: Glioma is the most common primary tumor in the central nervous system, and glioma-related epilepsy (GRE) is one of its common symptoms. The abnormalities of white matter fiber tracts are involved in attributing changes in patients with epilepsy (Rudà, R, 2012).This study aimed to assess frontal lobe gliomas' effects on the cerebral white matter fiber tracts. (2) Methods: Thirty patients with frontal lobe glioma were enrolled and divided into two groups (Ep and nEep). Among them, five patients were excluded due to apparent insular or temporal involvement. A set of 14 age and gender-matched healthy controls were also included. All the enrolled subjects underwent preoperative conventional magnetic resonance images (MRI) and diffusion tensor imaging (DTI). Furthermore, we used tract-based spatial statistics to analyze the characteristics of the white matter fiber tracts. (3) Results: The two patient groups showed similar patterns of mean diffusivity (MD) elevations in most regions; however, in the ipsilateral inferior fronto-occipital fasciculus (IFOF), superior longitudinal fasciculus (SLF), and superior corona radiata, the significant voxels of the EP group were more apparent than in the nEP group. No significant fractional anisotropy (FA) elevations or MD degenerations were found in the current study. (4) Conclusions: Gliomas grow and invade along white matter fiber tracts. This study assessed the effects of GRE on the white matter fiber bundle skeleton by TBSS, and we found that the changes in the white matter skeleton of the frontal lobe tumor-related epilepsy were mainly concentrated in the IFOF, SLF, and superior corona radiata. This reveals that GRE significantly affects the white matter fiber microstructure of the tumor.

Contralesional Cortical and Network Features Associated with Preoperative Language Deficit in Glioma Patients.

Lower-grade Gliomas anchored in eloquent areas cause varying degrees of language impairment. Except for a tumor's features, contralesional compensation may explain these differences. Therefore, studying changes in the contralateral hemisphere can provide insights into the underlying mechanisms of language function compensation in patients with gliomas. This study included 60 patients with eloquent-area or near-eloquent-area gliomas. The participants were grouped according to the degree of language defect. T1 and diffusion tensor imaging were obtained. The contralesional cortical volume and the subcortical network were compared between groups. Patients with unimpaired language function showed elevated cortical volume in the midline areas of the frontal and temporal lobes. In subcortical networks, the group also had the highest global efficiency and shortest global path length. Ten nodes had intergroup differences in nodal efficiency, among which four nodes were in the motor area and four nodes were in the language area. Linear correlation was observed between the efficiency of the two nodes and the patient's language function score. Functional compensation in the contralesional hemisphere may alleviate language deficits in patients with gliomas. Structural compensation mainly occurs in the contralesional midline area in the frontal and temporal lobes, and manifests as an increase in cortical volume and subcortical network efficiency.

Management of central nervous system Rosai-Dorfman disease: A single center treatment experience.

Rosai-Dorfman disease (RDD) is an idiopathic histiocytic proliferation disease with various clinical manifestations. A retrospective study of patients with pathological diagnosed RDD primarily involved in the central nervous system was conducted from January 2011 to December 2020 at a tertiary center. The clinical profile, imaging, and treatment data were collected. There were 16 male and 5 female patients with RDD-CNS. The patients were aged from 6 to 68 years with a median of 37 years. Of these 21 patients, 15 presented with intracranial RDD and 6 with spinal RDD. The main symptoms of RDD-CNS included headache, epilepsy, and neurological deficits. 76.19% (16/21) of the patients showed dura-based, homogeneous enhancement lesion on magnetic resonance imaging (MRI). Twenty patients received surgery as first treatment, and one patient received biopsy after steroid therapy. Total lesion resection was achieved in 42.9% (9/21) of the patients, subtotal resection in 47.6% (10/21), and biopsy in 0.9% (2/21). The symptoms were alleviated or stayed stable. Some RDDs (80%, 4/5) in the skull base had some complications. The patients were followed up for 11-108 months with a median duration of 47 months. Lesion progression or recurrence was found in two patients. The various clinical manifestations, as well as the dura-based and homogenous enhancement imaging profiles of RDD-CNS patients pose a great diagnostic challenge for clinicians. Surgery is effective for RDD-CNS requiring treatment. Medical therapy and radiotherapy would be feasible as noninvasive treatments, varying degrees of efficacy. The overall prognosis of RDD-CNS is acceptable. Periodic long-term follow-up is necessary.

The utility of intraoperative ECoG in tumor-related epilepsy: Systematic review.

OBJECT: Epilepsy is one of the most common clinical manifestations of primary brain tumors. Intraoperative electrocorticography (ECoG) has been widely used in tumor resection. We aim to describe the indication and utility of ECoG during brain tumor surgery. METHODS: We performed a systematic review of the literature on the prognosis of tumor-related epilepsy surgery guided by intraoperative ECoG. The published studies were searched in PubMed, Embase, and Web of Science using the keyword 'seizure' or 'epilepsy' and 'electrocorticography' or 'ECoG'. Two reviewer authors screened studies and extracted data independently. RESULTS: Thirteen studies included 569 patients were finally selected, of which eight investigated medically intractable epilepsy. Three publications described temporal tumor-related epilepsy. All included studies were retrospective, and the age of all patients ranged from 1 to 71 years. The duration of epilepsy ranged from 1 month to 30 years. Patients with tumor-related epilepsy underwent surgical treatment with Engel I outcomes ranging from 56.5%-100%. CONCLUSION: Intraoperative ECoG is generally considered a useful technique in delineating epileptogenic areas and improving the prognosis of surgical treatment of tumor-related epilepsy. However, large-scale randomized control trials are still needed to verify these findings and formulate appropriate surgical strategies.

Image-Based Differentiation of Intracranial Metastasis From Glioblastoma Using Automated Machine Learning.

Purpose: The majority of solitary brain metastases appear similar to glioblastomas (GBMs) on magnetic resonance imaging (MRI). This study aimed to develop and validate an MRI-based model to differentiate intracranial metastases from GBMs using automated machine learning. Materials and Methods: Radiomics features from 354 patients with brain metastases and 354 with GBMs were used to build prediction algorithms based on T2-weighted images, contrast-enhanced (CE) T1-weighted images, or both. The data of these subjects were subjected to a nested 10-fold split in the training and testing groups to build the best algorithms using the tree-based pipeline optimization tool (TPOT). The algorithms were independently validated using data from 124 institutional patients with solitary brain metastases and 103 patients with GBMs from the cancer genome atlas. Results: Three groups of models were developed. The average areas under the receiver operating characteristic curve (AUCs) were 0.856 for CE T1-weighted images, 0.976 for T2-weighted images, and 0.988 for a combination in the testing groups, and the AUCs of the groups of models in the independent validation were 0.687, 0.831, and 0.867, respectively. A total of 149 radiomics features were considered as the most valuable features for the differential diagnosis of GBMs and metastases. Conclusion: The models established by TPOT can distinguish glioblastoma from solitary brain metastases well, and its non-invasiveness, convenience, and robustness make it potentially useful for clinical applications.

Contralesional functional network reorganization of the insular cortex in diffuse low-grade glioma patients.

Diffuse low-grade gliomas (DLGGs) growing on the insular lobe induce contralesional hemispheric insular lobe compensation of damaged functioning by increasing cortical volumes. However, it remains unclear how functional networks are altered in patients with insular lobe DLGGs during functional compensation. Thirty-five patients with insular DLGGs were classified into the left (insL, n = 16) and right groups (insR, n = 19), and 33 healthy subjects were included in the control group. Resting state functional magnetic resonance imaging was used to generate functional connectivity (FC), and network topological properties were evaluated using graph theoretical analysis based on FC matrices. Network-based statistics were applied to compare differences in the FC matrices. A false discovery rate was applied to correct the topological properties. There was no difference in the FC of edges between the control and insL groups; however, the nodal shortest path length of the right insular lobe was significantly increased in the insL group compared to the control group. Additionally, FC was increased in the functional edges originating from the left insular lobe in the insR group compared to the control group. Moreover, there were no differences in topological properties between the insR and control groups. The contralesional insular lobe is crucial for network alterations. The detailed patterns of network alterations were different depending on the affected hemisphere. The observed network alterations might be associated with functional network reorganization and functional compensation.

Topological Characteristics Associated with Intraoperative Stimulation Related Epilepsy of Glioma Patients: A DTI Network Study.

Background: Awake craniotomy with intraoperative stimulation has been utilized in glioma surgical resection to preserve the quality of life. Epilepsy may occur in 5-20% of cases, leading to severe consequences. This study aimed to discuss the mechanism of intraoperative stimulation-related epilepsy (ISE) using DTI-based graph theoretical analysis. Methods: Twenty patients with motor-area glioma were enrolled and divided into two groups (Ep and nEp) according to the presence of ISE. Additionally, a group of 10 healthy participants matched by age, sex, and years of education was also included. All participants underwent T1, T2, and DTI examinations. Graph theoretical analysis was applied to reveal the topological characteristics of white matter networks. Results: Three connections were found to be significantly lower in at least one weighting in the Ep group. These connections were between A1/2/3truL and A4ulL, A1/2/3truR and A4tR, and A6mL and A6mR. Global efficiency was significantly decreased, while the shortest path length increased in the Ep group in at least one weighting. Ten nodes exhibited significant differences in nodal efficiency and degree centrality analyses. The nodes A6mL and A6mR showed a marked decrease in total four weightings in the Ep group. Conclusions: The hub nodes A6mL and A6mR are disconnected in patients with ISE, causing subsequent lower efficiency of global and regional networks. These findings provide a basis for presurgical assessment of ISE, for which caution should be taken when it involves hub nodes during intraoperative electrical stimulation.

Characteristic Alterations of Network in Patients With Intraoperative Stimulation-Induced Seizures During Awake Craniotomy.

Background: The use of electrocorticography (ECoG) to avoid intraoperative stimulation-induced seizure (ISS) during awake craniotomy is controversial. Although a standard direct cortical stimulating (DCS) protocol is used to identify the eloquent cortices and subcortical structures, ISS still occurs. Epilepsy is related to alterations in brain networks. In this study, we investigated specific alterations in brain networks in patients with ISS. Methods: Twenty-seven patients with glioma were enrolled and categorized into the ISS and non-ISS groups based on their history of ISS occurrence. A standard DCS protocol was used during awake craniotomy without ECoG supervision. Graph theoretical measurement was used to analyze resting-state functional magnetic resonance imaging data to quantitatively reveal alterations in the functional networks. Results: In the sensorimotor networks, the glioma significantly decreased the functional connectivity (FC) of four edges in the ISS group, which were conversely increased in the non-ISS group after multiple corrections (p < 0.001, threshold of p-value = 0.002). Regarding the topological properties, the sensorimotor network of all participants was classified as a small-world network. Glioma significantly increased global efficiency, nodal efficiency, and the sigma value, as well as decreased the shortest path length in the ISS group compared with the non-ISS group (p < 0.05). Conclusions: The specific alterations indicating patient susceptibility to ISS during DCS increased global and nodal efficiencies and decreased the shortest path length and FC induced by gliomas. If the patient has these specific alterations, ECoG is recommended to monitor after-discharge current during DCS to avoid ISS.

Ischemic Infarction of Pituitary Apoplexy: A Retrospective Study of 46 Cases From a Single Tertiary Center.

OBJECTIVE: Ischemic infarction of pituitary apoplexy (PA) is a rare type of pituitary apoplexy. This study aims to characterize ischemic PA via clinical presentations, imaging data, histopathological manifestations, and focus on the management and prognosis of the disease. METHODS: This study retrospectively identified 46 patients with ischemic PA confirmed using histopathology at a single institution from January 2013 to December 2020. The clinical presentations, imaging data, laboratory examination, management, and outcomes were collected. We then summarized the clinical presentations, imaging features, intraoperative findings, and histopathological manifestations, and compared the outcomes based on the timing of surgical intervention. RESULTS: Headache was the most common initial symptom (95.65%, 44/46), followed by visual disturbance (89.13%, 41/46), and nausea and vomiting (58.70%, 27/46). 91.3% of the patients had at least one pituitary dysfunction, with hypogonadism being the most common endocrine dysfunction (84.78%, 39/46). Cortisol dysfunction occurred in 24 (52.17%) patients and thyroid dysfunction occurred in 17 (36.96%). Typical rim enhancement and thickening of the sphenoid sinus on MRI were seen in 35 (85.37%) and 26 (56.52%) patients, respectively. Except for one patient with asymptomatic apoplexy, the remaining patients underwent early (≤ 1 week, 12 patients) and delayed (> 1 week, 33 patients) transsphenoidal surgery. Total tumor resection was achieved in 27 patients and subtotal tumor resection in 19 patients. At surgery, cottage cheese-like necrosis was observed in 50% (23/46) of the patients. At the last follow-up of 5.5 ± 2.7 years, 92.68% (38/41) of the patients had gained a significant improvement in visual disturbance regardless of surgical timing, and 65% of the patients were still receiving long-term hormone replacement therapy. CONCLUSION: Patients with ischemic PA can be accurately diagnosed by typical imaging characteristics preoperatively. The timing of surgical intervention does not significantly affect the resolution of neurological and endocrinological dysfunctions. Preoperative endocrine dysfunctions are common and usually appear to be poor after surgical intervention.

Preoperative Radiomics Analysis of 1p/19q Status in WHO Grade II Gliomas.

PURPOSE: The present study aimed to preoperatively predict the status of 1p/19q based on radiomics analysis in patients with World Health Organization (WHO) grade II gliomas. METHODS: This retrospective study enrolled 157 patients with WHO grade II gliomas (76 patients with astrocytomas with mutant IDH, 16 patients with astrocytomas with wild-type IDH, and 65 patients with oligodendrogliomas with mutant IDH and 1p/19q codeletion). Radiomic features were extracted from magnetic resonance images, including T1-weighted, T2-weighted, and contrast T1-weighted images. Elastic net and support vector machines with radial basis function kernel were applied in nested 10-fold cross-validation loops to predict the 1p/19q status. Receiver operating characteristic analysis and precision-recall analysis were used to evaluate the model performance. Student's t-tests were then used to compare the posterior probabilities of 1p/19q co-deletion prediction in the group with different 1p/19q status. RESULTS: Six valuable radiomic features, along with age, were selected with the nested 10-fold cross-validation loops. Five features showed significant difference in patients with different 1p/19q status. The area under curve and accuracy of the predictive model were 0.8079 (95% confidence interval, 0.733-0.8755) and 0.758 (0.6879-0.8217), respectively, and the F1-score of the precision-recall curve achieved 0.6667 (0.5201-0.7705). The posterior probabilities in the 1p/19q co-deletion group were significantly different from the non-deletion group. CONCLUSION: Combined radiomics analysis and machine learning showed potential clinical utility in the preoperative prediction of 1p/19q status, which can aid in making customized neurosurgery plans and glioma management strategies before postoperative pathology.

Epilepsy-Related Brain Network Alterations in Patients With Temporal Lobe Glioma in the Left Hemisphere.

Background: Seizures are a common symptom in patients with temporal lobe gliomas and may result in brain network alterations. However, brain network changes caused by glioma-related epilepsy (GRE) remain poorly understood. Objective: In this study, we applied graph theory analysis to delineate topological networks with resting-state functional magnetic resonance images (rs-fMRI) and investigated characteristics of functional networks in patients with GRE. Methods: Thirty patients with low-grade gliomas in the left temporal lobe were enrolled and classified into GRE (n = 15) and non-GRE groups. Twenty healthy participants matched for age, sex, and education level were enrolled. All participants had rs-fMRI data. Sensorimotor, visual, default mode, auditory, and right executive control networks were used to construct connection matrices. Topological properties of those sub-networks were investigated. Results: Compared to that in the GRE group, four edges with higher functional connectivity were noted in the non-GRE group. Moreover, 21 edges with higher functional connectivity were identified in the non-GRE group compared to the healthy group. All significant alterations in functional edges belong to the visual network. Increased global efficiency and decreased shortest path lengths were noted in the non-GRE group compared to the GRE and healthy groups. Compared with that in the healthy group, nodal efficiency of three nodes was higher in the GRE and non-GRE groups and the degree centrality of six nodes was altered in the non-GRE group. Conclusion: Temporal lobe gliomas in the left hemisphere and GRE altered visual networks in an opposing manner. These findings provide a novel insight into brain network alterations induced by GRE.