Radiology During the COVID-19 Pandemic: Mapping Radiology Literature in 2020

OBJECTIVES

Our aim was to assess articles published in the field of radiology, nuclear medicine, and medical imaging in 2020 and analyze the linkage of radiology-related topics with coronavirus disease 2019 (COVID-19) through literature mapping along with a bibliometric analysis for publications.

METHODS

We performed a search on the Web of Science Core Collection database for articles in the field of radiology, nuclear medicine, and medical imaging published in 2020. We analyzed the included articles using VOS viewer software, where we analyzed the co-occurrence of keywords, representing major topics discussed. Of the resulting topics, a literature map was created and linkage analysis was done.

RESULTS

A total of 24,748 articles were published in the field of radiology, nuclear medicine, and medical imaging in 2020. We found a total of 61,267 keywords; only 78 keywords occurred more than 250 times. COVID-19 had 449 occurrences, 29 links, with a total link strength of 271. MRI was the topic most commonly appearing in 2020 radiology publications, while "computed tomography" had the highest linkage strength with COVID-19, with a linkage strength of 149, representing 54.98% of the total COVID-19 linkage strength, followed by "radiotherapy, and "deep and machine learning". The top cited paper had a total of 1,687 citations. Nine out of the 10 most cited articles discussed COVID-19 and included "COVID-19" or "coronavirus" in their title, including the top cited paper.

CONCLUSION

While MRI was the topic that dominated, CT had the highest linkage strength with COVID-19 and represented the topic of top cited articles in 2020 radiology publications.

Predictors of Citation Rates in High-Impact Glioblastoma Clinical Trials

Clinical trials are at the top of research study designs and tend to attract high citation numbers. Glioblastoma multiforme (GBM) is a multidisciplinary disease that continues to be the subject of peak research interest. In general, the literature relating to the predictors of citation rates in clinical trials remains limited. This review aims to identify the factors that influence citation numbers in high-impact GBM clinical trials. The 100 most cited GBM trials of any phase published from 1975 to 2019 were selected and reviewed. The primary analysis correlated citation numbers of articles with various trial and publication-related predictors using the Pearson correlation coefficient. The secondary analysis compared the mean citation numbers for different subgroups using the mean difference test. The median (range) citation number for the selected 100 trials was 349 (135-16,384). The primary analysis showed a significant correlation between citation numbers of articles and the study population (P = 0.024), trial phase (I-III) (P = 0.0427), and the impact factor (IF) of the journal (P < 0.0001). The secondary analysis demonstrated significantly higher mean citation numbers in all trials with the following features: study population ≥115 (P = 0.0208), phase III (P = 0.0372), treatment protocol including radiotherapy (P = 0.0189), temozolomide (TMZ) therapy (P = 0.0343), IF of the journal ≥14.9 (P = 0.02), and general medical journals (P = 0.28). We conclude that the most significant predictors of citation rates in high-impact GBM trials were the study population, trial phase, and journal's IF. The treatment protocol was a positive predictor when it included the currently widely accepted treatment modalities (radiotherapy and TZM). Randomization, age of publication, as well as the numbers of arms, authors, centers, countries, and references were not significant predictors. Increasing awareness of the factors that could affect citations may help researchers undertaking clinical trials to enhance the academic impact of their work.

Profile of Articles Published in AJR From 2014 to 2018 and Potential Association With Bibliometric Parameters

OBJECTIVE. The purpose of this study was to assess the profile of articles published in the American Journal of Roentgenology (AJR) and potential associations with bibliometric indexes over a 5-year period. MATERIALS AND METHODS. Citable documents published from 2014 to 2018 were retrieved from the Journal Citation Reports database. Six bibliometric indexes were assessed. The following article parameters were retrieved: type, subspecialty (17 topics covered by AJR), origin, and title. Differences between groups were assessed by t test, ANOVA, Kruskal-Wallis test, or chi-square test. Citability was assessed by regression analysis. RESULTS. After exclusions, 2210 articles were considered citable and included in the analyses. Most of the metrics improved slightly, except for the Eigenfactor score and article influence score, which decreased. Original articles were preponderant; AJR published significantly more review articles than did three other general radiology journals. The mean number of citations per year of original articles (2.03 ± 2.18) was significantly larger than that of review articles (2.06 ± 2.47) (p = .02). The mean number of citations per year was significantly higher for articles with mixed-origin authorship (3.12 ± 3.19) than for articles with American (2.02 ± 2.17) or non-American (1.93 ± 2.26) authors only (p < .001). The distributions of mean number of citations per year among subspecialties differed significantly (p = .001). Articles on abdominal, musculoskeletal, pediatric, and women's imaging were more frequently cited. Multivariate regression analysis showed that subspecialty and presence of acronyms or initialisms in the title were the only independent predictors of citability (both, p = .001). CONCLUSION. The main AJR bibliometric indexes increased slightly from 2014 to 2018, except for those from the Eigenfactor Project. The presence of acronyms or initialisms in the title and subspecialty were the only independent predictors of citability.

Quoted speech in linguistics research article titles: patterns of use and effects on citations

This paper investigates the uses and scholarly impact of quoted/direct speech in research article titles (e.g., "I Know I'm Generalizing but…": How Teachers' Perceptions Influence ESL Learner Placement) across the 50 highest-listed linguistics journals according to Clarivate Analytics’ inCites Journal Citation Reports. The aims of the study were to: (1) uncover the prevalence of titles featuring quoted speech between 1980 and 2019, (2) describe how directly reported speech is utilised structurally in article titles, and (3) investigate the effects of various patterns of use of quotations on articles’ age-weighted citation rates. 640 linguistics articles with speech act titles were uncovered, occurring with an incidence of 1.8% in the dataset (n = 36,438), although their prevalence has risen significantly since 2004. Structural analysis revealed 90.9% of quotations were contained in the first segment of a compound title, serving to create an information gap (often for the purposes of provoking interest or intrigue), which is resolved in the second segment; the research article’s topic. Regression analysis showed that speech act titles were significant negative determinants of articles’ age-weighted citations, particularly the prevalent pattern of compound structures featuring a quotation phrased as a declarative. The length of the quotation was found to exert no significant effect, although quotations that were not marked by single or double quotation marks were found to have an especially suppressed scholarly impact.

Global Tissue Engineering Trends: A Scientometric and Evolutive Study

Tissue engineering (TE) is defined as a multidisciplinary scientific discipline with the main objective to develop artificial bioengineered living tissues to regenerate damaged or lost tissues. Since its appearance in 1988, TE has globally spread to improve current therapeutic approaches, entailing a revolution in clinical practice. The aim of this study is to analyze global research trends on TE publications to realize the scenario of TE research from 1991 to 2016 by using document retrieval from Web of Science database and bibliometric analysis. Document type, language, source title, authorship, countries and filiation centers, and citation count were evaluated in 31,859 documents. Obtained results suggest a great multidisciplinary role of TE due to a wide spectrum-up to 51-of scientific research areas identified in the corpus of literature, being predominant technological disciplines as Material Sciences or Engineering, followed by biological and biomedical areas, as Cell Biology, Biotechnology, or Biochemistry. Distribution of authorship, journals, and countries revealed a clear imbalance, in which a minority is responsible for a majority of documents. Such imbalance is notorious in authorship, where a 0.3% of authors are involved in half of the whole production.