Deep brain stimulation (DBS) is a highly efficacious treatment option for movement disorders and a growing number of other indications are investigated in clinical trials. To ensure optimal treatment outcome, exact electrode placement is required. Moreover, to analyze the relationship between electrode location and clinical results, a precise reconstruction of electrode placement is required, posing specific challenges to the field of neuroimaging. Since 2014 the open source toolbox Lead-DBS is available, which aims at facilitating this process. The tool has since become a popular platform for DBS imaging. With support of a broad community of researchers worldwide, methods have been continuously updated and complemented by new tools for tasks such as multispectral nonlinear registration, structural / functional connectivity analyses, brain shift correction, reconstruction of microelectrode recordings and orientation detection of segmented DBS leads. The rapid development and emergence of these methods in DBS data analysis require us to revisit and revise the pipelines introduced in the original methods publication. Here we demonstrate the updated DBS and connectome pipelines of Lead-DBS using a single patient example with state-of-the-art high-field imaging as well as a retrospective cohort of patients scanned in a typical clinical setting at 1.5T. Imaging data of the 3T example patient is co-registered using five algorithms and nonlinearly warped into template space using ten approaches for comparative purposes. After reconstruction of DBS electrodes (which is possible using three methods and a specific refinement tool), the volume of tissue activated is calculated for two DBS settings using four distinct models and various parameters. Finally, four whole-brain tractography algorithms are applied to the patient’s preoperative diffusion MRI data and structural as well as functional connectivity between the stimulation volume and other brain areas are estimated using a total of eight approaches and datasets. In addition, we demonstrate impact of selected preprocessing strategies on the retrospective sample of 51 PD patients. We compare the amount of variance in clinical improvement that can be explained by the computer model depending on the method of choice. This work represents a multi-institutional collaborative effort to develop a comprehensive, open source pipeline for DBS imaging and connectomics, which has already empowered several studies, and may facilitate a variety of future studies in the field.

Oncolytic virotherapy is a rapidly progressing field that uses oncolytic viruses (OVs) to selectively infect malignant cells and cause an antitumor response through direct oncolysis and stimulation of the immune system. Despite demonstrated pre-clinical efficacy of OVs in many cancer types and some favorable clinical results in glioblastoma (GBM) trials, durable increases in overall survival have remained elusive. Recent evidence has emerged that tumor-associated macrophage/microglia (TAM) involvement is likely an important factor contributing to OV treatment failure. It is prudent to note that the relationship between TAMs and OV therapy failures is complex. Canonically activated TAMs (i.e., M1) drive an antitumor response while also inhibiting OV replication and spread. Meanwhile, M2 activated TAMs facilitate an immunosuppressive microenvironment thereby indirectly promoting tumor growth. In this focused review, we discuss the complicated interplay between TAMs and OV therapies in GBM. We review past studies that aimed to maximize effectiveness through immune system modulation—both immunostimulatory and immunosuppressant—and suggest future directions to maximize OV efficacy.

Background and purpose Data differentiating flow diversion properties of commercially available low- and high-porosity stents are limited. This in vitro study applies angiographic analysis of intra-aneurysmal flow to compare the flow-diversion performance of five neurovascular devices in idealized sidewall and bifurcation aneurysm models. Methods Five commercial devices (Enterprise, Neuroform, LVIS, FRED, and Pipeline) were implanted in silicone sidewall and bifurcation aneurysm models under physiological average flow of blood analog fluid. High-speed angiographic images were acquired pre- and post-device implantation and contrast concentration-time curves within the aneurysm were recorded. The curves were quantified with five parameters to assess changes in contrast transport, and thus aneurysm hemodynamics, due to each device. Results Inter-device flow-diversion performance was more easily distinguished in the sidewall model than the bifurcation model. There were no obvious overall statistical trends in the bifurcation parameters but the Pipeline performed marginally better than the other devices. In the sidewall geometry, overall evidence suggests that the LVIS performed better than the Neuroform and Enterprise. The Pipeline and FRED devices were statistically superior to the three stents and Pipeline was superior to FRED in all sidewall parameters evaluated. Conclusions Based on this specific set of experiments, lower-porosity flow diverters perform significantly better in reducing intra-aneurysmal flow activity than higher-porosity stents in sidewall-type geometries. The LVIS device is potentially a better flow diverter than the Neuroform and Enterprise devices, while the Pipeline is potentially better than the FRED.