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.

Modifying NIOSH's Manikin Fit Evaluation Method to Match Fit Testing with Human Subjects.

A manikin fit test method developed by the Center for Disease Control and Prevention's (CDC) National Institute of Occupational Safety and Health (NIOSH) has been proposed as an alternative to fit testing with human subjects. The advantages of a manikin fit test method over actual fit testing are that it does not require human subjects which can be resource intensive, and hence easier to implement. At the beginning of coronavirus 2019 (COVID-19) pandemic, although early studies showed that manikin fit can be maintained after several decontamination cycles, real world evidence obtained using human subjects revealed that the N95 respirators failed only after a few decontamination cycles.

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.

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.