Translational design for limited resource settings as demonstrated by Vent-Lock, a 3D-printed ventilator multiplexer.

BACKGROUND: Mechanical ventilators are essential to patients who become critically ill with acute respiratory distress syndrome (ARDS), and shortages have been reported due to the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). METHODS: We utilized 3D printing (3DP) technology to rapidly prototype and test critical components for a novel ventilator multiplexer system, Vent-Lock, to split one ventilator or anesthesia gas machine between two patients. FloRest, a novel 3DP flow restrictor, provides clinicians control of tidal volumes and positive end expiratory pressure (PEEP), using the 3DP manometer adaptor to monitor pressures. We tested the ventilator splitter circuit in simulation centers between artificial lungs and used an anesthesia gas machine to successfully ventilate two swine. RESULTS: As one of the first studies to demonstrate splitting one anesthesia gas machine between two swine, we present proof-of-concept of a de novo, closed, multiplexing system, with flow restriction for potential individualized patient therapy. CONCLUSIONS: While possible, due to the complexity, need for experienced operators, and associated risks, ventilator multiplexing should only be reserved for urgent situations with no other alternatives. Our report underscores the initial design and engineering considerations required for rapid medical device prototyping via 3D printing in limited resource environments, including considerations for design, material selection, production, and distribution. We note that optimization of engineering may minimize 3D printing production risks but may not address the inherent risks of the device or change its indications. Thus, our case report provides insights to inform future rapid prototyping of medical devices.

Sensitivity of the stress field of the proximal femur predicted by CT-based FE analysis to modeling uncertainties.

Proximal femur anatomy and bone mineral density vary widely among individuals, precluding the use of one predefined finite element (FE) model to determine the stress field for all proximal femurs. This variability poses a challenge in current prosthetic hip design approach. Given the numerous options for generating computed tomography (CT)-based FE models, selecting the best methods for defining the mechanical behavior of the proximal femur is difficult. In this study, a combination of computational and experimental approaches was used to explore the susceptibility of the predicted stress field of the proximal femur to different combinations of density-elasticity relationships, element type, element size, and calibration error. Our results suggest that FE models with first-order voxelized elements generated by the Keyak and Falkinstein density-elasticity relationship or quadratic tetrahedral elements generated by the Morgan density-elasticity relationship lead to accurate estimations of the mechanical behavior of human femurs. Other combinations of element size, element type, and mathematical relationships produce less accurate results, especially in the cortical bone of the femoral neck and calcar region. The voxelized model was more susceptible to variation of element size and density-elasticity relationships than FE models with quadratic tetrahedral elements. Regardless of element type, the stress fields predicted by the Keyak and Falkinstein and the Morgan relationships were the most robust to calibration error when deriving material density from CT-generated Hounsfield data. These results provide insight into the implementation of a robust platform for designing patient-specific implants capable of maintaining or modifying the stress in bones.

FEMOSSA: Patient-specific finite element simulation of the prostate-rectum spacer placement, a predictive model for prostate cancer radiotherapy.

PURPOSE: Major advances in delivery systems in recent years have turned radiotherapy (RT) into a more effective way to manage prostate cancer. Still, adjacency of organs at risk (OARs) can severely limit RT benefits. Rectal spacer implant in recto-prostatic space provides sufficient separation between prostate and rectum, and therefore, the opportunity for potential dose escalation to the target and reduction of OAR dose. Pretreatment simulation of spacer placement can potentially provide decision support to reduce the risks and increase the efficacy of the spacer placement procedure. METHODS: A novel finite element method-oriented spacer simulation algorithm, FEMOSSA, was developed in this study. We used the finite element (FE) method to model and predict the deformation of rectum and prostate wall, stemming from hydrogel injection. Ten cases of prostate cancer, which undergone hydrogel placement before the RT treatment, were included in this study. We used the pre-injection organ contours to create the FE model and post-injection spacer location to estimate the distribution of the virtual spacer. Material properties and boundary conditions specific to each patient's anatomy were assigned. The FE analysis was then performed to determine the displacement vectors of regions of interest (ROIs), and the results were validated by comparing the virtually simulated contours with the real post-injection contours. To evaluate the different aspects of our method's performance, we used three different figures of merit: dice similarity coefficient (DSC), nearest neighbor distance (NND), and overlapped volume histogram (OVH). Finally, to demonstrate a potential dosimetric application of FEMOSSA, the predicted rectal dose after virtual spacer placement was compared against the predicted post-injection rectal dose. RESULTS: Our simulation showed a realistic deformation of ROIs. The post-simulation (virtual spacer) created the same separation between prostate and rectal wall, as post-injection spacer. The average DSCs for prostate and rectum were 0.87 and 0.74, respectively. Moreover, there was a statistically significant increase in rectal contour similarity coefficient (P < 0.01). Histogram of NNDs showed the same overall shape and a noticeable shift from lower to higher values for both post-simulation and post-injection, indicative of the increase in distance between prostate and rectum. There was less than 2.2- and 2.1-mm averaged difference between the mean and fifth percentile NNDs. The difference between the OVH distances and the corresponding predicted rectal dose was, on average, less than 1 mm and 1.5 Gy, respectively. CONCLUSIONS: FEMOSSA provides a realistic simulation of the hydrogel injection process that can facilitate spacer placement planning and reduce the associated uncertainties. Consequently, it increases the robustness and success rate of spacer placement procedure that in turn improves prostate cancer RT quality.

Damping of selectively bonded 3D woven lattice materials.

The objective of this paper is to unveil a novel damping mechanism exhibited by 3D woven lattice materials (3DW), with emphasis on response to high-frequency excitations. Conventional bulk damping materials, such as rubber, exhibit relatively low stiffness, while stiff metals and ceramics typically have negligible damping. Here we demonstrate that high damping and structural stiffness can be simultaneously achieved in 3D woven lattice materials by brazing only select lattice joints, resulting in a load-bearing lattice frame intertwined with free, 'floating' lattice members to generate damping. The produced material samples are comparable to polymers in terms of damping coefficient, but are porous and have much higher maximum use temperature. We shed light on a novel damping mechanism enabled by an interplay between the forcing frequency imposed onto a load-bearing lattice frame and the motion of the embedded, free-moving lattice members. This novel class of damping metamaterials has potential use in a broad range of weight sensitive applications that require vibration attenuation at high frequencies.

3-D phononic crystals with ultra-wide band gaps.

In this paper gradient based topology optimization (TO) is used to discover 3-D phononic structures that exhibit ultra-wide normalized all-angle all-mode band gaps. The challenging computational task of repeated 3-D phononic band-structure evaluations is accomplished by a combination of a fast mixed variational eigenvalue solver and distributed Graphic Processing Unit (GPU) parallel computations. The TO algorithm utilizes the material distribution-based approach and a gradient-based optimizer. The design sensitivity for the mixed variational eigenvalue problem is derived using the adjoint method and is implemented through highly efficient vectorization techniques. We present optimized results for two-material simple cubic (SC), body centered cubic (BCC), and face centered cubic (FCC) crystal structures and show that in each of these cases different initial designs converge to single inclusion network topologies within their corresponding primitive cells. The optimized results show that large phononic stop bands for bulk wave propagation can be achieved at lower than close packed spherical configurations leading to lighter unit cells. For tungsten carbide - epoxy crystals we identify all angle all mode normalized stop bands exceeding 100%, which is larger than what is possible with only spherical inclusions.