Characterizing Subjects Exposed to Humidifier Disinfectants Using Computed-Tomography-Based Latent Traits: A Deep Learning Approach

Frank Li, Jiwoong Choi, Xuan Zhang, Prathish K. Rajaraman, Chang-Hyun Lee, Hongseok Ko, Kum-Ju Chae, Eun-Kee Park, Alejandro P. Comellas, Eric A. Hoffman and Ching-Long Lin ()
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Frank Li: Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, IA 52242, USA
Jiwoong Choi: Department of Mechanical Engineering, University of Iowa, Iowa City, IA 52242, USA
Xuan Zhang: IIHR—Hydroscience & Engineering, University of Iowa, Iowa City, IA 52242, USA
Prathish K. Rajaraman: IIHR—Hydroscience & Engineering, University of Iowa, Iowa City, IA 52242, USA
Chang-Hyun Lee: Department of Radiology, University of Iowa, Iowa City, IA 52242, USA
Hongseok Ko: Department of Radiology, Kangwon National University Hospital, Chuncheon 200-010, Korea
Kum-Ju Chae: Department of Radiology, Jeonbuk National University Hospital, Jeonju 560-011, Korea
Eun-Kee Park: Department of Medical Humanities and Social Medicine, College of Medicine, Kosin University, Busan 600-011, Korea
Alejandro P. Comellas: Department of Internal Medicine, University of Iowa, Iowa City, IA 52242, USA
Eric A. Hoffman: Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, IA 52242, USA
Ching-Long Lin: Roy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, IA 52242, USA

IJERPH, 2022, vol. 19, issue 19, 1-19

Abstract: Around nine million people have been exposed to toxic humidifier disinfectants (HDs) in Korea. HD exposure may lead to HD-associated lung injuries (HDLI). However, many people who have claimed that they experienced HD exposure were not diagnosed with HDLI but still felt discomfort, possibly due to the unknown effects of HD. Therefore, this study examined HD-exposed subjects with normal-appearing lungs, as well as unexposed subjects, in clusters (subgroups) with distinct characteristics, classified by deep-learning-derived computed-tomography (CT)-based tissue pattern latent traits. Among the major clusters, cluster 0 (C0) and cluster 5 (C5) were dominated by HD-exposed and unexposed subjects, respectively. C0 was characterized by features attributable to lung inflammation or fibrosis in contrast with C5. The computational fluid and particle dynamics (CFPD) analysis suggested that the smaller airway sizes observed in the C0 subjects led to greater airway resistance and particle deposition in the airways. Accordingly, women appeared more vulnerable to HD-associated lung abnormalities than men.

Keywords: humidifier disinfectants; computed tomography; deep learning; cluster analysis; computational fluid and particle dynamics (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
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