Looking Ahead to 2022 for the Korean Journal of Radiology

Copyright © 2022 The Korean Society of Radiology In this editorial, I will briefly review some of the activities of the Korean Journal of Radiology (KJR) in 2021 and explain the changes planned in 2022. In 2021, the world continued to suffer from the coronavirus disease-2019 (COVID-19). However, the massive impact of COVID-19 on scientific publications witnessed by us in 2020 [1,2] seems to have largely disappeared by 2021 in the field of radiology. KJR received a much smaller number of manuscripts on COVID-19 in 2021 than in 2020. This abrupt change is different from that experienced by general medical journals. For example, the majority of the articles published in the Journal of the American Medical Association in 2021 were still related to COVID-19. The rapid shrinkage of research studies on COVID-19 in radiology was because although radiology is a discipline mainly focused on diagnosis, the approach in dealing with the pandemic has shifted from diagnosis to vaccination and treatment/patient management in 2021. The KJR published eight articles related to COVID-19 in 2021 [3-9]. This number was much lower than that in 2020 and only two of them concerned the diagnosis of lung disease (commentaries on articles published in 2020) [8,9]. Other articles involved vaccination-associated lymphadenopathy [3,4], a meta-analysis of related neuroimaging findings [5], and modeling for patient management [6,7]. These topics reflect the phase shift in dealing with the pandemic. Notably, with the population-based large-scale vaccination campaign, COVID-19 vaccine-related lymphadenopathy that mimics malignant lymphadenopathy has become an issue that radiologists should be aware of [3,4]. As the manuscript submission and publication returned to the usual flow, artificial intelligence (AI) was a dominant topic addressed by the KJR in 2021. External validation/testing is critical for research studies involving AI [10,11]. KJR pays close attention to external validation/testing while reviewing manuscripts, as demonstrated by some recent articles [7,12-14]. One particular issue that is garnering attention with respect to the introduction of AI in radiology is “opportunistic” automated body composition analyses using imaging performed for other targeted purposes such as quantitative measurements of bone mineral density, visceral and subcutaneous fat, skeletal muscle, liver fat, coronary vascular calcification, and organ size [12,15-19]. The labor-intensive nature of manual (or even semi-automated) body composition measurements has largely prevented their translation from the research realm to routine clinical practice or large-scale population healthcare [15]. However, the emergence of automated AI-based approaches has paved the way for both efficient prospective clinical reporting and large-scale studies [15]. The association between skeletal muscle mass and patient outcomes is currently an area of active research [20-22]. The KJR is interested in receiving and publishing research studies that broadly address how the use of various body composition measurements, which were previously neglected in image interpretation, may change the radiology practice in the future. There will be a few notable changes in the KJR in 2022. Several new article categories have been added, which include