Telemedicine for Outpatient Neurosurgical Oncology Care: Lessons Learned for the Future During the COVID-19 Pandemic.

The coronavirus 2019 (COVD-19) pandemic has drastically disrupted the delivery of neurosurgical care, especially for the already at-risk neuro-oncology population. The sudden change to clinic visits has rapidly spurned the implementation of telemedicine. A recommendation care paradigm of neuro-oncologic patients limited by telemedicine has not been reported. A summary of a multi-institution experience detailing the potential benefits, pitfalls, and the necessary considerations to outpatient care of neurosurgical oncology patients. There are limitations and advantages to incorporating telemedicine into the outpatient care of neuro-oncology patients. Telemedicine-specific considerations for each step and stakeholder of the appointment (physician, patient, scheduling, previsit, imaging, and physical examination) are examined. Telemedicine, pushed to prominence during this COVID-19 pandemic, is a powerful and possibly preferential tool for the future of outpatient neuro-oncologic care

Current Update on the Randomized Controlled Trials of Intracranial Aneurysms

Endovascular coiling has become the primary treatment modality for the treatment of intracranial ruptured aneurysms in many centers. A multicenter randomized controlled trial (RCT), ISAT study, has demonstrated that endovascular coiling of ruptured intracranial aneurysms has benefits over surgical clipping in those patients suitable for either treatment. Because RCT comparing conservative management with surgical clipping and with endovascular coiling have not been performed to date for unruptured intracranial aneurysms, the best management for unruptured aneurysm remains unclear. A RCT is ongoing to answer the question whether active treatment can improve the outcome of patients with unruptured intracranial aneurysms as compared with observation

Toward Objective Quantification of Perfusion-weighted Computed Tomography in Subarachnoid Hemorrhage: Quantification of Symmetry and Automated Delineation of Vascular Territories

Rationale and Objectives: Perfusion-weighted computed tomography (CTP) is a relatively recent innovation that estimates a value for cerebral blood flow (CBF) using a series of axial head CT images tracking the time course of a signal from an intravenous contrast bolus. Materials and Methods: CTP images were obtained using a standard imaging protocol and were analyzed using commercially available software. A novel computer-based method was used for objective quantification of side-to-side asymmetries of CBF values calculated from CTP images. Results: Our method corrects for the inherent variability of the CTP methodology seen in the subarachnoid hemorrhage (SAH) patient population to potentially aid in the diagnosis of cerebral vasospasm (CVS). This method analyzes and quantifies side-to-side asymmetry of CBF and presents relative differences in a construct termed a Relative Difference Map (RDM). To further automate this process, we have developed a unique methodology that enables a computer to delineate vascular territories within a brain image, regardless of the size and shape of the brain. Conclusions: While both the quantification of image symmetry using RDMs and the automated assignment of vascular territories were initially designed for the analysis of CTP images, it is likely that they will be useful in a variety of applications

Post-carotid endarterectomy neurocognitive decline is associated with cerebral blood flow asymmetry on post-operative magnetic resonance perfusion brain scans

Objective: Up to 25% of patients experience subtle declines in post-operative neurocognitive function following, otherwise uncomplicated, carotid endarterectomy (CEA). We sought to determine if post-CEA neurocognitive deficits are associated with cerebral blood flow (CBF) abnormalities on post-operative MR perfusion brain scans. Methods: We enrolled 22 CEA patients to undergo a battery of neuropsychometric tests pre-operatively and on post-operative day 1 (POD 1). Neurocognitive dysfunction was defined as a two standard deviation decline in performance in comparison to a similarly aged control group of lumbar laminectomy patients. All patients received MR perfusion brain scans on POD 1 that were analysed for asymmetries in CBF distribution. One patient experienced a transient ischemic attack within 24 hours before the procedure and was excluded from our analysis. Results: Twenty-nine percent of CEA patients demonstrated neurocognitive dysfunction on POD 1. One hundred percent of those patients with cognitive deficits demonstrated CBF asymmetry, in contrast to only 27% of those patients without cognitive impairment. Post-CEA cognitive dysfunction was significantly associated with CBF abnormalities (RR=3.75, 95% CI: 1.62-8.67, p=0.004). Conclusion: Post-CEA neurocognitive dysfunction is significantly associated with post-operative CBF asymmetry. These results support the hypothesis that post-CEA cognitive impairment is caused by cerebral hemodynamic changes. Further work exploring the relationship between CBF and post-CEA cognitive dysfunction is needed

Zynq SoC based acceleration of the lattice Boltzmann method

Cerebral aneurysm is a life‐threatening condition. It is a weakness in a blood vessel that may enlarge and bleed into the surrounding area. In order to understand the surrounding environmental conditions during the interventions or surgical procedures, a simulation of blood flow in cerebral arteries is needed. One of the effective simulation approaches is to use the lattice Boltzmann (LB) method. Due to the computational complexity of the algorithm, the simulation is usually performed on high performance computers. In this paper, efficient hardware architectures of the LB method on a Zynq system‐on‐chip (SoC) are designed and implemented. The proposed architectures have first been simulated in Vivado HLS environment and later implemented on a ZedBoard using the software‐defined SoC (SDSoC) development environment. In addition, a set of evaluations of different hardware architectures of the LB implementation is discussed in this paper. The experimental results show that the proposed implementation is able to accelerate the processing speed by a factor of 52 compared to a dual‐core ARM processor‐based software implementation