Benchtop assessment of sealing efficacy and breathability of additively manufactured (AM) face masks.

The onset of the 2019 novel coronavirus disease (COVID-19) led to a shortage of personal protective equipment (PPE), medical devices, and other medical supplies causing many stakeholders and the general public alike to turn to additive manufacturing (AM) as a stopgap when normally accessible devices were not available. However, without a method to test these AM constructs, there continued to be a disconnect between AM suppliers and the community's needs. The objective of this study was to characterize the pressure drop and leakage of four different publicly available AM face mask models with two filter material combinations, as well as to investigate the impact of frame modification techniques including the use of foam strips and hot-water face forming to improve fit when the masks are donned on manikin head forms. AM face mask frame designs were downloaded from public repositories during the early stages of the COVID-19 pandemic. AM face masks were fabricated and tested on manikin head forms within a custom chamber containing dry aerosolized NaCl. Pressure drops, particle penetration, and leakage were evaluated for various flow rates and NaCl concentrations. Results indicated that filter material combination and frame modification played a major role in the overall performance of the AM face masks studied. Filter material combinations showed improved performance when high filtration fabric was used, and the cross-sectional area of the fabric was increased. AM frame modifications appeared to improve AM face mask leakage performance by as much as 69.6%.

Algorithms used in medical image segmentation for 3D printing and how to understand and quantify their performance.

BACKGROUND: 3D printing (3DP) has enabled medical professionals to create patient-specific medical devices to assist in surgical planning. Anatomical models can be generated from patient scans using a wide array of software, but there are limited studies on the geometric variance that is introduced during the digital conversion of images to models. The final accuracy of the 3D printed model is a function of manufacturing hardware quality control and the variability introduced during the multiple digital steps that convert patient scans to a printable format. This study provides a brief summary of common algorithms used for segmentation and refinement. Parameters for each that can introduce geometric variability are also identified. Several metrics for measuring variability between models and validating processes are explored and assessed. METHODS: Using a clinical maxillofacial CT scan of a patient with a tumor of the mandible, four segmentation and refinement workflows were processed using four software packages. Differences in segmentation were calculated using several techniques including volumetric, surface, linear, global, and local measurements. RESULTS: Visual inspection of print-ready models showed distinct differences in the thickness of the medial wall of the mandible adjacent to the tumor. Volumetric intersections and heatmaps provided useful local metrics of mismatch or variance between models made by different workflows. They also allowed calculations of aggregate percentage agreement and disagreement which provided a global benchmark metric. For the relevant regions of interest (ROIs), statistically significant differences were found in the volume and surface area comparisons for the final mandible and tumor models, as well as between measurements of the nerve central path. As with all clinical use cases, statistically significant results must be weighed against the clinical significance of any deviations found. CONCLUSIONS: Statistically significant geometric variations from differences in segmentation and refinement algorithms can be introduced into patient-specific models. No single metric was able to capture the true accuracy of the final models. However, a combination of global and local measurements provided an understanding of important geometric variations. The clinical implications of each geometric variation is different for each anatomical location and should be evaluated on a case-by-case basis by clinicians familiar with the process. Understanding the basic segmentation and refinement functions of software is essential for sites to create a baseline from which to evaluate their standard workflows, user training, and inter-user variability when using patient-specific models for clinical interventions or decisions.

Dimensional variability characterization of additively manufactured lattice coupons.

BACKGROUND: Additive manufacturing (AM), commonly called 3D Printing (3DP), for medical devices is growing in popularity due to the technology's ability to create complex geometries and patient-matched products. However, due to the process variabilities which can exist between 3DP systems, manufacturer workflows, and digital conversions, there may be variabilities among 3DP parts or between design files and final manufactured products. The overall goal of this project is to determine the dimensional variability of commercially obtained 3DP titanium lattice-containing test coupons and compare it to the original design files. METHODS: This manuscript outlines the procedure used to measure dimensional variability of 3D Printed lattice coupons and analyze the differences in external dimensions and pore area when using laser and electron beam fabricated samples. The key dimensions measured were the bulk length, width, and depth using calipers. Strut thickness and pore area were assessed for the lattice components using optical imaging and µCT. RESULTS: Results show a difference in dimensional measurement between printed parts and the computer-designed files for all groups analyzed including the internal lattice dimensions. Measurements of laser manufactured coupons varied from the nominal by less than 0.2 mm and results show averages greater than the nominal value for length, width, and depth dimensions. Measurements of Electron Beam Melting coupons varied between 0.4 mm-0.7 mm from the nominal value and showed average lengths below the nominal dimension while the width and depths were greater than the nominal values. The length dimensions of Laser Powder Bed Fusion samples appeared to be impacted by hot isostatic press more than the width and depth dimension. When lattice relative density was varied, there appeared to be little impact on the external dimensional variability for the as-printed state. CONCLUSIONS: Based on these results, we can conclude that there are relevant variations between designed files and printed parts. However, we cannot currently state if these results are clinically relevant and further testing needs to be conducted to apply these results to real-world situations.