Importance and Evidence of Extent of Resection in Glioblastoma.

Maximal safe resection is an essential part of the multidisciplinary care of patients with glioblastoma. A growing body of data shows that gross total resection is an independent prognostic factor associated with improved clinical outcome. The relationship between extent of glioblastoma (GB) resection and clinical benefit depends critically on the balance between cytoreduction and avoiding neurologic morbidity. The definition of the extent of tumor resection, how this is best measured pre- and postoperatively, and its relation to volume of residual tumor is still discussed. We review the literature supporting extent of resection in GB, highlighting the importance of a standardized definition and measurement of extent of resection to allow greater collaboration in research projects and trials. Recent developments in neurosurgical techniques and technologies focused on maximizing extent of resection and safety are discussed

Epilepsia partialis continua responsive to neocortical electrical stimulation

Epilepsia partialis continua (EPC), defined as a syndrome of continuous focal jerking, is a rare form of focal status epilepticus that usually affects a distal limb, and when prolonged, can produce long-lasting deficits in limb function. Substantial electrophysiologic evidence links the origin of EPC to the motor cortex; thus surgical resection carries the risk of significant handicap. We present two patients with focal, drug-resistant EPC, who were admitted for intracranial video-electroencephalography monitoring to elucidate the location of the epileptogenic focus and identification of eloquent motor cortex with functional mapping. In both cases, the focus resided at or near eloquent motor cortex and therefore precluded resective surgery. Chronic cortical stimulation delivered through subdural strips at the seizure focus (continuous stimulation at 60–130 Hz, 2–3 mA) resulted in \u3e90% reduction in seizures and abolition of the EPC after a follow-up of 22 months in both patients. Following permanent implantation of cortical stimulators, no adverse effects were noted. EPC restarted when intensity was reduced or batteries depleted. Battery replacement restored previous improvement. This two-case report opens up avenues for the treatment of this debilitating condition

Battery Longevity Comparison of Two Commonly Available Dual Channel Implantable Pulse Generators Used for Subthalamic Nucleus Stimulation in Parkinson's Disease.

OBJECTIVES Deep brain stimulation for Parkinson's disease (PD) utilises an implantable pulse generator (IPG) whose finite lifespan in non-rechargeable systems necessitates their periodic replacement. We wish to determine if there is any significant difference in longevity of 2 commonly used IPG systems; the Medtronic Kinetra, and the Medtronic Activa Primary Cell (PC), which has come to replace it. METHODS All patients with bilateral Subthalamic Nucleus stimulators for PD performed in our centre were included. Battery life was then assessed using a Kaplan-Meier approach and comparisons between the Kinetra and Activa PC batteries were performed using log-rank tests. RESULTS Complete data was available for 183 patients. There was a significant difference in the average battery duration with an estimated median battery life in the Kinetra cohort of 6.6 years (95% CI 6.4-6.7), compared to 4.5 years (95% CI 4.4-4.5) in the Activa PC cohort (p < 0.001). CONCLUSION The Activa PC IPG demonstrates a significantly reduced battery life of 2.1 years, with a median battery life of 4.5 years in comparison to 6.6 years in the Kinetra IPG. Future technology developments should therefore be focused on improving the battery life of the newer IPG systems

Machine learning-based radiomic, clinical and semantic feature analysis for predicting overall survival and MGMT promoter methylation status in patients with glioblastoma.

INTRODUCTION Survival varies in patients with glioblastoma due to intratumoral heterogeneity and radiomics/imaging biomarkers have potential to demonstrate heterogeneity. The objective was to combine radiomic, semantic and clinical features to improve prediction of overall survival (OS) and O-methylguanine-DNA methyltransferase (MGMT) promoter methylation status from pre-operative MRI in patients with glioblastoma. METHODS A retrospective study of 181 MRI studies (mean age 58 ± 13 years, mean OS 497 ± 354 days) performed in patients with histopathology-proven glioblastoma. Tumour mass, contrast-enhancement and necrosis were segmented from volumetric contrast-enhanced T1-weighted imaging (CE-T1WI). 333 radiomic features were extracted and 16 Visually Accessible Rembrandt Images (VASARI) features were evaluated by two experienced neuroradiologists. Top radiomic, VASARI and clinical features were used to build machine learning models to predict MGMT status, and all features including MGMT status were used to build Cox proportional hazards regression (Cox) and random survival forest (RSF) models for OS prediction. RESULTS The optimal cut-off value for MGMT promoter methylation index was 12.75%; 42 radiomic features exhibited significant differences between high and low-methylation groups. However, model performance accuracy combining radiomic, VASARI and clinical features for MGMT status prediction varied between 45 and 67%. For OS predication, the RSF model based on clinical, VASARI and CE radiomic features achieved the best performance with an average iAUC of 96.2 ± 1.7 and C-index of 90.0 ± 0.3. CONCLUSIONS VASARI features in combination with clinical and radiomic features from the enhancing tumour show promise for predicting OS with a high accuracy in patients with glioblastoma from pre-operative volumetric CE-T1WI