Journal of neurosurgery
-
Journal of neurosurgery · Jan 2024
ReviewComputational modeling of whole-brain dynamics: a review of neurosurgical applications.
A major goal of modern neurosurgery is the personalization of treatment to optimize or predict individual outcomes. One strategy in this regard has been to create whole-brain models of individual patients. Whole-brain modeling is a subfield of computational neuroscience that focuses on simulations of large-scale neural activity patterns across distributed brain networks. ⋯ The resulting personalized whole-brain models have translational potential in neurosurgery, allowing investigators to simulate the effects of virtual therapies (such as resections or brain stimulations), assess the effect of brain pathology on network dynamics, or discern epileptic networks and predict seizure propagation in silico. The information gained from these simulations can be used as clinical decision support, guiding patient-specific treatment plans. Here the authors provide an overview of the rapidly advancing field of whole-brain modeling and review the literature on neurosurgical applications of this technology.
-
Journal of neurosurgery · Jan 2024
High signal intensity of the intraaneurysmal sac on T1 CUBE imaging as a predictor of aneurysm stability after coil embolization.
Histopathological studies of aneurysms after coil embolization showed that thrombus formation during the first month after endovascular treatment (EVT) played an important role in the healing process. The authors hypothesized that dedicated T1-weighted imaging may be used to predict stable aneurysms by visualizing the thrombus status within coil-treated aneurysms. Therefore, this study investigated the relationship between the signal intensity (SI) of the intraaneurysmal sac after coil embolization and aneurysm stability. ⋯ RSIcoiled was associated with postcoiling aneurysm stability. High RSIcoiled might imply intraaneurysmal thrombus formation associated with the healing process of coil-treated aneurysms.
-
Journal of neurosurgery · Jan 2024
Does waiting for surgery matter? How time from diagnostic MRI to resection affects outcomes in newly diagnosed glioblastoma.
Maximal safe resection is the standard of care for patients presenting with lesions concerning for glioblastoma (GBM) on magnetic resonance imaging (MRI). Currently, there is no consensus on surgical urgency for patients with an excellent performance status, which complicates patient counseling and may increase patient anxiety. This study aims to assess the impact of time to surgery (TTS) on clinical and survival outcomes in patients with GBM. ⋯ An increased TTS for patients with imaging concerning for GBM did not impact clinical outcomes, and while there was a significant association with ΔCETV, SPGR remained unaffected. However, SPGR was associated with a worse preoperative KPS, which highlights the importance of tumor growth speed over TTS. Therefore, while it is ill advised to wait an unnecessarily long time after initial imaging studies, these patients do not require urgent/emergency surgery and can seek tertiary care opinions and/or arrange for additional preoperative support/resources. Future studies are needed to explore subgroups for whom TTS may impact clinical outcomes.
-
Journal of neurosurgery · Jan 2024
Observational StudyHigh-volume facilities are not always low risk: comparing risk-standardized mortality rates versus facility volume as quality measures in surgical neuro-oncology.
Risk-standardized mortality rates (RSMRs) have recently been shown to outperform facility case volume as a proxy for surgical quality in lung and gastrointestinal cancer. The aim of this study was to investigate RSMR as a surgical quality metric in primary CNS cancer. ⋯ RSMR is more effective and efficient than a traditional volume-based approach for preventing early postoperative death in glioblastoma surgery. These data have important implications for future quality-related studies in neurosurgical oncology and may be relevant for healthcare/insurance payments, hospital evaluation assessments, healthcare disparities, and the standardization of care across hospitals.