A review on surgical treatment options in gliomas

Chordoid glioma of right lateral ventricle in young male: a case report

Introduction and importance

Chordoid glioma is an extremely rare, slow-growing brain tumor. This report discusses the clinical presentation, imaging characteristics, surgical approach, histopathology, and prognosis. The review of literature provides an overview focusing on diagnostic challenges and treatment strategies.

Case presentation

A 21-year-old male presented with progressive blurring of vision, headache and intermittent convulsive seizures over a period of 2 months. Computerized tomography and magnetic resonance imaging revealed a mass in the right lateral ventricle, possibilities of central neurocytoma or ganglioglioma. Surgical resection was performed, and histopathological examination confirmed the diagnosis of chordoid glioma through a combination of histological and immunohistochemical analyses.

Clinical discussion

Chordoid glioma is a distinct clinicopathologic entity, recognized for its unique histological and immunohistochemical features. It is crucial to differentiate chordoid gliomas from other neoplasms due to differences in treatment approaches and prognosis.

Conclusion

Chordoid glioma, although rare, should be considered in the differential diagnosis of lateral ventricular tumors, especially in young adults presenting with visual and neurological symptoms. Early diagnosis and surgical intervention are crucial for improving outcomes.

Identification of the high-risk population facing early death in older patients with primary intracranial glioma: a retrospective cohort study

Background

This study aimed to establish a diagnostic nomogram to predict the early death risk in older patients with primary intracranial glioma and to identify the high-risk population in those patients to provide them with specialized care to increase their benefit from survival.

Methods

Patients aged 60 years and older with histologically confirmed intracranial glioma were identified in the Surveillance, Epidemiology and End Results (SEER) database. Initially, they were divided into a training set and a validation set in a 7:3 ratio. Next, univariate and multivariate logistic regression were employed to identify independent risk variables, which were used to develop a diagnostic nomogram further. Additional analyses were performed on the diagnostic nomogram's performance, including calibration curves, receiver operating characteristic (ROC) curves, and decision curve analysis (DCA). A mortality risk classification system was ultimately developed using the diagnostic nomogram.

Results

This study included 8,859 individuals diagnosed with primary intracranial glioma. The participants were randomly split into two groups: a training set consisting of 6203 individuals and a validation set consisting of 2,656 individuals, with a ratio of 7 to 3. Univariate and multivariate logistic regression analyses on early death showed 7 independent risk variables (age, median household income, histological type, tumor grade, surgery, radiation therapy, and systemic therapy sequence with surgery) in the training set. A diagnostic nomogram for predicting the early death risk was created based on these variables. Calibration curves showed a high agreement between the expected and actual probabilities. The area under the curves (AUC) for the training and validation sets were 0.798 and 0.811, respectively. Meanwhile, the novel-created diagnostic nomogram had the highest AUC value compared to each independent risk variables, which showed that the nomogram had the best discriminatory ability. The DCA indicated that the nomogram has the potential to provide greater clinical advantages across a broad spectrum of threshold probabilities. Furthermore, a nomogram-based risk classification system was constructed to help us identify the high-risk population facing early death.

Conclusions

This study created a novel diagnostic nomogram to predict the probability of early death in older patients with intracranial glioma. In the meantime, a nomogram-based risk classification system was also constructed to help us identify the high-risk population facing early death in older patients with intracranial glioma and provide them with specialized care to increase their benefit from survival.

Mass spectrometry for neurosurgery: Intraoperative support in decision-making

Ambient ionization mass spectrometry was proved to be a powerful tool for oncological surgery. Still, it remains a translational technique on the way from laboratory to clinic. Brain surgery is the most sensitive to resection accuracy field since the balance between completeness of resection and minimization of nerve fiber damage determines patient outcome and quality of life. In this review, we summarize efforts made to develop various intraoperative support techniques for oncological neurosurgery and discuss difficulties arising on the way to clinical implementation of mass spectrometry-guided brain surgery.

Preliminary investigation of nitric oxide release from upconverted nanoparticles excited at 808 nm near-infrared for brain tumors

Upconverted UCNPs@mSiO2-NH2 nanoparticles were synthesized via thermal decomposition while employing the energy resonance transfer principle and the excellent near-infrared (NIR) light conversion property of up-conversion. The 808 nm NIR-excited photocontrolled nitric oxide (NO) release platform was successfully developed by electrostatically loading photosensitive NO donor Roussin's black salt (RBS) onto UCNPs@mSiO2-NH2, enabling the temporal, spatial, and dosimetric regulation of NO release for biological applications of NO. The release of NO ranged from 0.015⁓0.099 mM under the conditions of 2.0 W NIR excitation power, 20 min of irradiation time, and UCNPs@mSiO2-NH2&RBS concentration of 0.25⁓1.25 mg/mL. Therefore, this NO release platform has an anti-tumor effect. In vitro experiments showed that under the NIR light, at concentrations of 0.3 mg/mL and 0.8 mg/mL of UCNPs@mSiO2-NH2&RBS, the activity of glioma (U87) and chordoma (U-CH1) cells, as measured by CCK8 assay, was reduced to 50 %. Cell flow cytometry and Western Blot experiments showed that NO released from UCNPs@mSiO2-NH2&RBS under NIR light induced apoptosis in brain tumor cells. In vivo experiments employing glioma and chordoma xenograft mouse models revealed significant inhibition of tumor growth in the NIR and UCNPs@mSiO2-NH2&RBS group, with no observed significant side effects in the mice. Therefore, NO released by UCNPs@mSiO2-NH2&RBS under NIR irradiation can be used as a highly effective and safe strategy for brain tumor therapy.

Risk factors for surgical compliance and impact on the survival of patients with glioma: a population-based propensity score-matched study

PURPOSE

To comprehensively analyze the impact of surgical compliance on the survival of patients with glioma and to explore the factors that influence surgical compliance.

METHODS

Clinical data of patients with glioma between 2004 and 2018 were collected from the Surveillance, Epidemiology, and End Results (SEER) database. Kaplan-Meier curves and Cox regression were used to analyze the effect of surgical compliance on overall survival (OS) and disease-specific survival (DSS). Multivariate Cox regression was used to select the prediction variables and construct the nomograms. The predictive power of these models was assessed using Harell's consistency index (C-index), decision curve analysis (DCA), receiver operating characteristic (ROC) curves, and calibration curves. Multivariate logistic regression was performed to analyze the related variables of surgical compliance, and 1:1 propensity score matching (PSM) was applied to evaluate the validity of the results of patients with favorable and poor surgical compliance.

RESULTS

Among the 47,573 eligible glioma patients recommended for surgery, 46,380 (97.5%) were in the surgical compliance group, while 1193 (2.5%) were in the noncompliance group. Surgical compliance was an independent prognostic factor for glioma patients, as indicated by multivariate Cox regression analysis that patients with surgical compliance had worse OS (hazard ratio [HR] 1.924; 95% confidence interval [CI] 1.800-2.056, p < 0.001) and DSS (HR 1.718; 95% CI 1.592-1.853, p < 0.001) in comparison to those without surgical compliance. A nomogram was developed and internally validated to be able to predict glioma prognosis. The nomogram can well predict patients' OS (C-index: 0.745) and DSS (C-index: 0.744). ROC curve, DCA curve, and calibration curve were applied to further assess the accuracy of the nomogram. Poor surgical compliance was found to be related to older age, female gender, tumor diameter, grade II or higher, poor grading, tumor location in the cerebellum and brainstem, and low household income.

CONCLUSION

Surgical compliance is an independent prognostic factor for predicting the OS and DSS of patients with glioma, and good surgical compliance was significantly related to good survival.