The maintenance of adequate blood flow to the brain is critical for normal brain function; cerebral blood flow, its regulation and the effect of alteration in this flow with disease have been studied extensively and are very well understood. This flow is not steady, however; the systolic increase in blood pressure over the cardiac cycle causes regular variations in blood flow into and throughout the brain that are synchronous with the heart beat. Because the brain is contained within the fixed skull, these pulsations in flow and pressure are in turn transferred into brain tissue and all of the fluids contained therein including cerebrospinal fluid. While intracranial pulsatility has not been a primary focus of the clinical community, considerable data have accrued over the last sixty years and new applications are emerging to this day. Investigators have found it a useful marker in certain diseases, particularly in hydrocephalus and traumatic brain injury where large changes in intracranial pressure and in the biomechanical properties of the brain can lead to significant changes in pressure and flow pulsatility. In this work, we review the history of intracranial pulsatility beginning with its discovery and early characterization, consider the specific technologies such as transcranial Doppler and phase contrast MRI used to assess various aspects of brain pulsations, and examine the experimental and clinical studies which have used pulsatility to better understand brain function in health and with disease.

Vascular endothelial growth factor (VEGF) is a potent growth factor playing diverse roles in vasculogenesis and angiogenesis. In the brain, VEGF mediates angiogenesis, neural migration and neuroprotection. As a permeability factor, excessive VEGF disrupts intracellular barriers, increases leakage of the choroid plexus endothelia, evokes edema, and activates the inflammatory pathway. Recently, we discovered that a heparin binding epidermal growth factor like growth factor (HB-EGF)—a class of EGF receptor (EGFR) family ligands—contributes to the development of hydrocephalus with subarachnoid hemorrhage through activation of VEGF signaling. The objective of this review is to entail a recent update on causes of death due to neurological disorders involving cerebrovascular and age-related neurological conditions and to understand the mechanism by which angiogenesis-dependent pathological events can be treated with VEGF antagonisms. The Global Burden of Disease study indicates that cancer and cardiovascular disease including ischemic and hemorrhagic stroke are two leading causes of death worldwide. The literature suggests that VEGF signaling in ischemic brains highlights the importance of concentration, timing, and alternate route of modulating VEGF signaling pathway. Molecular targets distinguishing two distinct pathways of VEGF signaling may provide novel therapies for the treatment of neurological disorders and for maintaining lower mortality due to these conditions.

We propose a novel systematic approach to optimizing the design of concentric tube robots for neurosurgical procedures. These procedures require that the robot approach specified target sites while navigating and operating within an anatomically constrained work space. The availability of preoperative imaging makes our approach particularly suited for neurosurgery, and we illustrate the method with the example of endoscopic choroid plexus ablation. A novel parameterization of the robot characteristics is used in conjunction with a global pattern search optimization method. The formulation returns the design of the least-complex robot capable of reaching single or multiple target points in a confined space with constrained optimization metrics. A particular advantage of this approach is that it identifies the need for either fixed-curvature versus variable-curvature sections. We demonstrate the performance of the method in four clinically relevant examples.

Surgical robots are gaining favor in part due to their capacity to reach remote locations within the body. Continuum robots are especially well suited for accessing deep spaces such as cerebral ventricles within the brain. Due to the entry point constraints and complicated structure, current techniques do not allow surgeons to access the full volume of the ventricles. The ability to access the ventricles with a dexterous robot would have significant clinical implications. This paper presents a concentric tube manipulator mated to a robotically controlled flexible endoscope. The device adds three degrees of freedom to the standard neuroendoscope and roboticizes the entire package allowing the operator to conveniently manipulate the device. To demonstrate the improved functionality, we use an in-silica virtual model as well as an ex-vivo anatomic model of a patient with a treatable form of hydrocephalus. In these experiments we demonstrate that the augmented and roboticized endoscope can efficiently reach critical regions that a manual scope cannot.

BACKGROUND: A critical conceptual step in epilepsy surgery is to locate the causal region of seizures. In practice, the causal region may be inferred from the set of electrodes showing early ictal activity. There would be advantages in deriving information about causal regions from interictal data as well. We applied Granger's statistical approach to baseline interictal data to calculate causal interactions. We hypothesized that maps of the Granger causality network (or GC maps) from interictal data might inform about the seizure network, and set out to see if “causality” in the Granger sense correlated with surgical targets. OBJECTIVE: To determine whether interictal baseline data could produce GC maps, and whether the regions of high GC would statistically resemble the topography of the ictally active electrode (IAE) set and resection. METHODS: Twenty-minute interictal baselines obtained from 25 consecutive patients were analyzed. The “GC maps” were quantitatively compared to conventionally constructed surgical plans, by using rank order and Cartesian distance statistics. RESULTS: In 16 of 25 cases, the interictal GC rankings of the electrodes in the IAE set were lower than predicted by chance (P < .05). The aggregate probability of such a match by chance alone is very small (P < 10⁻²⁰) suggesting that interictal GC maps correlated with ictal networks. The distance of the highest GC electrode to the IAE set and to the resection averaged 4 and 6 mm (Wilcoxon P < .001). CONCLUSION: GC analysis has the potential to help localize ictal networks from interictal data.