Combined Effects of Masking and Distance on Aerosol Exposure Potential.

OBJECTIVE: To quantify the efficacy of masking and "social distancing" on the transmission of airborne particles from a phantom aerosol source (simulating an infected individual) to a nearby target (simulating a healthy bystander) in a well-controlled setting. METHODS: An aerosol was created using monodisperse polystyrene latex beads in place of infectious respiratory secretions. Detection was by aerodynamic particle spectrometry. Both reusable cloth masks and disposable paper masks were studied. Transmission was simulated indoors during a 3-minute interval to eliminate the effect of variable ventilation rate on aerosol exposure. The study commenced on September 16, 2020, and concluded on December 15, 2020. RESULTS: Compared with a baseline of 1-foot separation with no masks employed, particle count was reduced by 84% at 3 feet of separation and 97% at 6 feet. A modest decrease in particle count was observed when only the receiver was masked. The most substantial exposure reduction occurred when the aerosol source was masked (or both parties were masked). When both the source and target were masked, particle count was reduced by more than 99.5% of baseline, regardless of separation distance or which type of mask was employed. CONCLUSION: These results support the principle of layered protection to mitigate transmission of SARS-CoV-2, the virus causing COVID-19, and other respiratory viruses and emphasize the importance of controlling the spread of aerosol at its source. The combination of masking and distancing reduced the exposure to exhaled particulates more than any individual measure. Combined measures remain the most effective way to combat the spread of respiratory infection.

Morphological and Hemodynamic Changes during Cerebral Aneurysm Growth.

Computational fluid dynamics (CFD) has grown as a tool to help understand the hemodynamic properties related to the rupture of cerebral aneurysms. Few of these studies deal specifically with aneurysm growth and most only use a single time instance within the aneurysm growth history. The present retrospective study investigated four patient-specific aneurysms, once at initial diagnosis and then at follow-up, to analyze hemodynamic and morphological changes. Aneurysm geometries were segmented via the medical image processing software Mimics. The geometries were meshed and a computational fluid dynamics (CFD) analysis was performed using ANSYS. Results showed that major geometry bulk growth occurred in areas of low wall shear stress (WSS). Wall shape remodeling near neck impingement regions occurred in areas with large gradients of WSS and oscillatory shear index. This study found that growth occurred in areas where low WSS was accompanied by high velocity gradients between the aneurysm wall and large swirling flow structures. A new finding was that all cases showed an increase in kinetic energy from the first time point to the second, and this change in kinetic energy seems correlated to the change in aneurysm volume.

A novel re-attachable stereotactic frame for MRI-guided neuronavigation and its validation in a large animal and human cadaver model.

OBJECTIVE: Stereotactic frame systems are the gold-standard for stereotactic surgeries, such as implantation of deep brain stimulation (DBS) devices for treatment of medically resistant neurologic and psychiatric disorders. However, frame-based systems require that the patient is awake with a stereotactic frame affixed to their head for the duration of the surgical planning and implantation of the DBS electrodes. While frameless systems are increasingly available, a reusable re-attachable frame system provides unique benefits. As such, we created a novel reusable MRI-compatible stereotactic frame system that maintains clinical accuracy through the detachment and reattachment of its stereotactic devices used for MRI-guided neuronavigation. APPROACH: We designed a reusable arc-centered frame system that includes MRI-compatible anchoring skull screws for detachment and re-attachment of its stereotactic devices. We validated the stability and accuracy of our system through phantom, in vivo mock-human porcine DBS-model and human cadaver testing. MAIN RESULTS: Phantom testing achieved a root mean square error (RMSE) of 0.94 ± 0.23 mm between the ground truth and the frame-targeted coordinates; and achieved an RMSE of 1.11 ± 0.40 mm and 1.33 ± 0.38 mm between the ground truth and the CT- and MRI-targeted coordinates, respectively. In vivo and cadaver testing achieved a combined 3D Euclidean localization error of 1.85 ± 0.36 mm (p < 0.03) between the pre-operative MRI-guided placement and the post-operative CT-guided confirmation of the DBS electrode. SIGNIFICANCE: Our system demonstrated consistent clinical accuracy that is comparable to conventional frame and frameless stereotactic systems. Our frame system is the first to demonstrate accurate relocation of stereotactic frame devices during in vivo MRI-guided DBS surgical procedures. As such, this reusable and re-attachable MRI-compatible system is expected to enable more complex, chronic neuromodulation experiments, and lead to a clinically available re-attachable frame that is expected to decrease patient discomfort and costs of DBS surgery.

Cerebral aneurysm blood flow simulations are sensitive to basic solver settings.

Computational modeling of peri-aneurysmal hemodynamics is typically carried out with commercial software without knowledge of the sensitivity of the model to variation in input values. For three aneurysm models, we carried out a formal sensitivity analysis and optimization strategy focused on variation in timestep duration and model residual error values and their impact on hemodynamic outputs. We examined the solution sensitivity to timestep sizes of 10-3s, 10-4s, and 10-5s while using model residual error values of 10-4, 10-5, and 10-6 using ANSYS Fluent to observe compounding errors and to optimize solver settings for computational efficiency while preserving solution accuracy. Simulations were compared qualitatively and quantitatively against the most rigorous combination of timestep and residual parameters, 10-5s and 10-6, respectively. A case using 10-4s timesteps, with 10-5 residual errors proved to be a converged solution for all three models with mean velocity and WSS difference RMS errors less than <1% compared with baseline, and was computationally efficient with a simulation time of 62h per cardiac cycle compared to 392h for baseline for the model with the most complex flow simulation. The worst case of our analysis, using 10-3s timesteps and 10-4 residual errors, was still able to predict the dominant vortex in the aneurysm, but its velocity and WSS RMS errors reached 20%. Even with an appealing simulation time of 11h per cycle for the model with the most complex flow, the worst case analysis solution exhibited compounding errors from large timesteps and residual errors. To resolve time-dependent flow characteristics, CFD simulations of cerebral aneurysms require sufficiently small timestep size and residual error. Simulations with both insufficient timestep and residual resolution are vulnerable to compounding errors.

Intra-aneurysmal flow rates are reduced by two flow diverters: an experiment using tomographic particle image velocimetry in an aneurysm model.

BACKGROUND: Limitations on treating large, giant, and wide-necked aneurysms with coiling have made flow diverters a promising alternative to current practice by supporting reconstruction of the parent artery. OBJECTIVE: To assess the changes to fluid dynamics within an aneurysm by studying two different endoluminal flow diverters on a simple aneurysm model, using tomographic particle image velocimetry to determine which device would better minimize fluid flow into an aneurysm and observe any significant changes in aneurysm fluid structures. METHODS: Steady velocity fields of the model's aneurysm dome and neck were measured at three inlet velocities (18, 39, and 59 cm/s) for two flow diverter diameters with different porosities and compared against a baseline case with no flow diverter. RESULTS: In the baseline case a large vortex was present inside the dome for all flow rates. However, both devices eliminated this main vortex at all flow rates and reduced the peak aneurysmal velocities by about 90%. A strong correlation between flow diverter porosity and flow reduction was found. In each case the inflow to the aneurysm shifted from the distal neck to the mid- or proximal neck after flow diverter placement. CONCLUSIONS: Even with this relatively simple experimental setup, we were able to observe the major flow field changes, which occurred immediately after the deployment of each flow diverter. Limitations of the study included a simplified geometry and steady-state flow. Constraints included model making and limited availability of flow diverters.

Grid convergence errors in hemodynamic solution of patient-specific cerebral aneurysms.

Computational fluid dynamics (CFD) has become a cutting-edge tool for investigating hemodynamic dysfunctions in the body. It has the potential to help physicians quantify in more detail the phenomena difficult to capture with in vivo imaging techniques. CFD simulations in anatomically realistic geometries pose challenges in generating accurate solutions due to the grid distortion that may occur when the grid is aligned with complex geometries. In addition, results obtained with computational methods should be trusted only after the solution has been verified on multiple high-quality grids. The objective of this study was to present a comprehensive solution verification of the intra-aneurysmal flow results obtained on different morphologies of patient-specific cerebral aneurysms. We chose five patient-specific brain aneurysm models with different dome morphologies and estimated the grid convergence errors for each model. The grid convergence errors were estimated with respect to an extrapolated solution based on the Richardson extrapolation method, which accounts for the degree of grid refinement. For four of the five models, calculated velocity, pressure, and wall shear stress values at six different spatial locations converged monotonically, with maximum uncertainty magnitudes ranging from 12% to 16% on the finest grids. Due to the geometric complexity of the fifth model, the grid convergence errors showed oscillatory behavior; therefore, each patient-specific model required its own grid convergence study to establish the accuracy of the analysis.