Yoon SH, et al. Korean J Radiol. 2020 Feb;21:e24. https://doi.org/10.3348/kjr.2020.0132

Purpose To study the extent of pulmonary involvement in COVID-19 with quantitative CT (QCT) and to assess the impact of disease burden on opacity visibility on chest radiographs. Materials and Meth...

Jeong WG, et al. Korean J Radiol. 2025 Sep;26:e75. https://doi.org/10.3348/kjr.2025.0457

양미현, et al. J Korean Soc Radiol. 2023 Sep;84:e101. https://doi.org/10.3348/jksr.2023.0006

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.

Successful human–large language model collaboration is associated with model confidence and reader expertise in chest imaging, with rationale quality facilitating uptake of correct advice but increasing overreliance on incorrect suggestions.