Patient- and Ventilator-Specific Modeling to Drive the Use and Development of 3D Printed Devices for Rapid Ventilator Splitting During the COVID-19 Pandemic

Muath Bishawi, Michael Kaplan, Simbarashe Chidyagwai, Jhaymie Cappiello, Anne Cherry, David MacLeod, Ken Gall, Nathan Evans, Michael Kim, Rajib Shaha, John Whittle, Melanie Hollidge, George Truskey, Amanda Randles

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In the early days of the COVID-19 pandemic, there was a pressing need for an expansion of the ventilator capacity in response to the COVID19 pandemic. Reserved for dire situations, ventilator splitting is complex, and has previously been limited to patients with similar pulmonary compliances and tidal volume requirements. To address this need, we developed a system to enable rapid and efficacious splitting between two or more patients with varying lung compliances and tidal volume requirements. We present here a computational framework to both drive device design and inform patient-specific device tuning. By creating a patient- and ventilator-specific airflow model, we were able to identify pressure-controlled splitting as preferable to volume-controlled as well create a simulation-guided framework to identify the optimal airflow resistor for a given patient pairing. In this work, we present the computational model, validation of the model against benchtop test lungs and standard-of-care ventilators, and the methods that enabled simulation of over 200 million patient scenarios using 800,000 compute hours in a 72 h period.

Original languageEnglish
Title of host publicationComputational Science - ICCS 2022, 22nd International Conference, Proceedings
EditorsDerek Groen, Clélia de Mulatier, Valeria V. Krzhizhanovskaya, Peter M.A. Sloot, Maciej Paszynski, Jack J. Dongarra
PublisherSpringer Science and Business Media Deutschland GmbH
Pages137-149
Number of pages13
ISBN (Print)9783031087561
DOIs
StatePublished - 2022
Event22nd Annual International Conference on Computational Science, ICCS 2022 - London, United Kingdom
Duration: 21 Jun 202223 Jun 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13352 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference22nd Annual International Conference on Computational Science, ICCS 2022
Country/TerritoryUnited Kingdom
CityLondon
Period21/06/2223/06/22

Keywords

  • Airflow
  • Cloud computing
  • Ventilator modeling

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