Telovelar vs. Transvermian approach for the fourth ventricle tumors: A systematic review and meta-analysis.

BACKGROUND: Tumors in the fourth ventricle can be critical due to the small size of the fourth ventricle, which causes symptoms to be detected even in the presence of lesser mass effects. A proper surgical approach to the fourth ventricle poses challenges due to its deep location and proximity to vital compartments within the brainstem. The two commonly used approaches to these tumors are the transvermian and telovelar approaches. METHODS: A comprehensive systematic study was conducted based on a literature search of the databases. All case controls, cohorts, and case series including patients with fourth ventricle tumors, who were operated on with either telovelar or transvermian approaches were considered eligible. The evaluated outcomes were comparative postoperative complications of the telovelar vs. transvermian approach. After screening and data extraction, a meta-analysis was performed whenever adequate quantitative data were available. RESULTS: Seven studies with a total number of 848 patients, discussed both telovelar and transvermian approaches, with comparative reporting of outcomes in each group. Postoperative outcomes including cranial nerve deficit, mutism, diplopia, CSF leak, need for CSF diversion, and postoperative gait disturbance were not significantly different between telovelar and transvermian approaches. CONCLUSION: Postoperative complications were not significantly different between telovelar and transvermian approaches. Moreover, it could be proposed that such complications would be more likely to be a multifactorial matter concerning the patient's clinical condition, tumor characteristics, and surgeon's experience, rather than the surgical approach alone.

Glioma Tumor Grading Using Radiomics on Conventional MRI: A Comparative Study of WHO 2021 and WHO 2016 Classification of Central Nervous Tumors.

BACKGROUND: Glioma grading transformed in World Health Organization (WHO) 2021 CNS tumor classification, integrating molecular markers. However, the impact of this change on radiomics-based machine learning (ML) classifiers remains unexplored. PURPOSE: To assess the performance of ML in classifying glioma tumor grades based on various WHO criteria. STUDY TYPE: Retrospective. SUBJECTS: A neuropathologist regraded gliomas of 237 patients into WHO 2016 and 2021 from 2007 criteria. FIELD STRENGTH/SEQUENCE: Multicentric 0.5 to 3 Tesla; pre- and post-contrast T1-weighted, T2-weighted, and fluid-attenuated inversion recovery. ASSESSMENT: Radiomic features were selected using random forest-recursive feature elimination. The synthetic minority over-sampling technique (SMOTE) was implemented for data augmentation. Stratified 10-fold cross-validation with and without SMOTE was used to evaluate 11 classifiers for 3-grade (2, 3, and 4; WHO 2016 and 2021) and 2-grade (low and high grade; WHO 2007 and 2021) classification. Additionally, we developed the models on data randomly divided into training and test sets (mixed-data analysis), or data divided based on the centers (independent-data analysis). STATISTICAL TESTS: We assessed ML classifiers using sensitivity, specificity, accuracy, and the area under the receiver operating characteristic curve (AUC). Top performances were compared with a t-test and categorical data with the chi-square test using a significance level of P < 0.05. RESULTS: In the mixed-data analysis, Stacking Classifier without SMOTE achieved the highest accuracy (0.86) and AUC (0.92) in 3-grade WHO 2021 grouping. The results of WHO 2021 were significantly better than WHO 2016 (P-value<0.0001). In the 2-grade analysis, ML achieved 1.00 in all metrics. In the independent-data analysis, ML classifiers showed strong discrimination between grade 2 and 4, despite lower performance metrics than the mixed analysis. DATA CONCLUSION: ML algorithms performed better in glioma tumor grading based on WHO 2021 criteria. Nonetheless, the clinical use of ML classifiers needs further investigation. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

Graph theoretical approach to brain remodeling in multiple sclerosis.

Multiple sclerosis (MS) is a neuroinflammatory disorder damaging structural connectivity. Natural remodeling processes of the nervous system can, to some extent, restore the damage caused. However, there is a lack of biomarkers to evaluate remodeling in MS. Our objective is to evaluate graph theory metrics (especially modularity) as a biomarker of remodeling and cognition in MS. We recruited 60 relapsing-remitting MS and 26 healthy controls. Structural and diffusion MRI, plus cognitive and disability evaluations, were done. We calculated modularity and global efficiency from the tractography-derived connectivity matrices. Association of graph metrics with T2 lesion load, cognition, and disability was evaluated using general linear models adjusting for age, gender, and disease duration wherever applicable. We showed that MS subjects had higher modularity and lower global efficiency compared with controls. In the MS group, modularity was inversely associated with cognitive performance but positively associated with T2 lesion load. Our results indicate that modularity increase is due to the disruption of intermodular connections in MS because of the lesions, with no improvement or preserving of cognitive functions.

Stereotactic radiosurgery outcome for deep-seated cerebral arteriovenous malformations in the brainstem and thalamus/basal ganglia: systematic review and meta-analysis.

Deep-seated unruptured AVMs located in the thalamus, basal ganglia, or brainstem have a higher risk of hemorrhage compared to superficial AVMs and surgical resection is more challenging. Our systematic review and meta-analysis provide a comprehensive summary of the stereotactic radiosurgery (SRS) outcomes for deep-seated AVMs. This study follows the guidelines set forth by the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) Statement. We conducted a systematic search in December 2022 for all reports of deep-seated arteriovenous malformations treated with SRS. Thirty-four studies (2508 patients) were included. The mean obliteration rate in brainstem AVM was 67% (95% CI: 0.60-0.73), with significant inter-study heterogeneity (tau2 = 0.0113, I2 = 67%, chi2 = 55.33, df = 16, p-value < 0.01). The mean obliteration rate in basal ganglia/thalamus AVM was 65% (95% CI: 0.58-0.72) with significant inter-study heterogeneity (tau2 = 0.0150, I2 = 78%, chi2 = 81.79, df = 15, p-value < 0.01). The presence of deep draining veins (p-value: 0.02) and marginal radiation dose (p-value: 0.04) were positively correlated with obliteration rate in brainstem AVMs. The mean incidence of hemorrhage after treatment was 7% for the brainstem and 9% for basal ganglia/thalamus AVMs (95% CI: 0.05-0.09 and 95% CI: 0.05-0.12, respectively). The meta-regression analysis demonstrated a significant positive correlation (p-value < 0.001) between post-operative hemorrhagic events and several factors, including ruptured lesion, previous surgery, and Ponce C classification in basal ganglia/thalamus AVMs. The present study found that radiosurgery appears to be a safe and effective modality in treating brainstem, thalamus, and basal ganglia AVMs, as evidenced by satisfactory rates of lesion obliteration and post-surgical hemorrhage.

Surgical anatomic findings of sphenoid sinus in 1009 Iranian patients with pituitary adenoma undergoing endoscopic transsphenoidal surgery.

OBJECTIVE: The most common surgical technique for the management of pituitary adenomas is the endoscopic endonasal transsphenoidal approach (EEA). preoperative neuroimaging along with detecting surgical landmarks of the sphenoid sinus during surgery is important for making a successful operation. METHOD: This study includes 1009 patients with pituitary adenomas who underwent EEA between 2013 and 2020. We evaluated the anatomical features of the sphenoid sinus through a panel of items obtained from imaging and intra-operative findings. RESULTS: Our result includes 57.38% nonfunctional, 8.42% cushing, 12.39% prolactinoma, and 21.8% acromegaly patients who had undergone endoscopic endonasal transsphenoidal surgery. The mean age of the patients was 45 with a male to female ratio of 1.2:1. Sellar sphenoid type was the most common (91.8%) with only 12% symmetrical inter sphenoid septa, Internal carotid artery dehiscence was found in 1.7% of the cases. Apoplexy was present in 6.3% of patients, which was found more prevalent in nonfunctional adenomas (9.67%, Odds ratio: 4.85, 95% CI 2.24-11.79) and further investigation revealed a significant association between apoplexy and sphenoid mucosal edema and hemorrhage (Odds ratio: 43.0, 95% CI 22.50-84.26), and between apoplexy and cystic lesions (OR = 4.14, 95% CI 1.87-8.45, P-value < 0.0001). Acromegaly is associated with the increased number of lateral recces (Odds ratio: 11.41, 95% CI 7.54-17.52), septation of the sphenoid sinus (Marginal mean: 3.92, 95% CI 3.69-4.14), edematous sinonasal mucosa (Odds ratio: 6.7; 95% CI 4.46-10.08), and higher bony (OR: 4.81, 95% CI 2.60-8.97, P-value < 0.001) and cavernous (OR: 1.7, 95% CI 1.13-2.46, P-value < 0.01) invasion. CONCLUSION: The present study provides anatomical data about the sphenoid sinus and its adjacent vital structures with adenomal specific changes that are necessary to prevent complications during endoscopic advanced transsphenoidal surgery.

COVID-19-related rhino-orbital-cerebral mucormycosis: Neurological manifestation and related risk factors in two cases.

Mucormycosis is an opportunistic infection that has become a serious concern as a result of the immunosuppressive drugs used during COVID-19. In this report, we describe two cases of rhino-orbital-cerebral mucormycosis with neurological presentation and ophthalmologic problems accompanied by a history of COVID-19 and diabetes.

White matter microstructural associates of apathy-avolition in schizophrenia.

Apathy is present at the onset in nearly half the patients with schizophrenia. Current therapies lack the efficiency to improve apathy in patients. The presence of apathy is also associated with poorer outcomes. Despite its clinical importance, the underlying mechanism of apathy in schizophrenia is unclear, but it seems frontostriatal connections play a role. In this study, we investigated whole-brain white matter microstructural properties associated with the severity of apathy-avolition in schizophrenia. We included 80 schizophrenia patients (60 Male, 20 Female) from the Mind Clinical Imaging Consortium database and associated Apathy-Avolition score of "Scale for Assessment of Negative Symptoms" with fiber integrity measures derived from diffusion-weighted imaging using Tract-Based Spatial Statistics (TBSS). We also did tractography on eight tracts, including bilateral superior longitudinal fasciculus, uncinate fasciculus, cingulum, genu and splenium of the corpus callosum. Age, gender, years of education, chlorpromazine equivalent cumulative dose, and acquisition site were inserted as covariates. We showed a widespread association between lower fiber integrity (by measures of increased mean diffusivity and decreased fractional anisotropy) and increased apathy-avolition in TBSS, which we also validated in tractography. Moreover, mean diffusivity, and not fractional anisotropy, was associated with apathy independent of disease severity. In conclusion, we propose diffuse white-matter pathology, within the corpus callosum, limbic system, and the frontostriatal circuit is involved in apathy-avolition in schizophrenia. Also, we suggest that diffuse neuroinflammatory processes may play a part in apathy-avolition, independent of disease severity.