Global evolution of research on pulmonary nodules: a bibliometric analysis

Knowledge mapping analysis of ground glass nodules: a bibliometric analysis from 2013 to 2023

Background

In recent years, the widespread use of computed tomography (CT) in early lung cancer screening has led to an increase in the detection rate of lung ground glass nodules (GGNs). The persistence of GGNs, which may indicate early lung adenocarcinoma, has been a focus of attention for scholars in the field of lung cancer prevention and treatment in recent years. Despite the rapid development of research into GGNs, there is a lack of intuitive content and trend analyses in this field, as well as a lack of detailed elaboration on possible research hotspots. The objective of this study was to conduct a comprehensive analysis of the knowledge structure and research hotspots of lung ground glass nodules over the past decade, employing bibliometric methods.

Method

The Web of Science Core Collection (WoSCC) database was searched for relevant ground-glass lung nodule literature published from 2013-2023. Bibliometric analyses were performed using VOSviewer, CiteSpace, and the R package "bibliometrix".

Results

A total of 2,218 articles from 75 countries and 2,274 institutions were included in this study. The number of publications related to GGNs has been high in recent years. The United States has led in GGNs-related research. Radiology has one of the highest visibilities as a selected journal and co-cited journal. Jin Mo Goo has published the most articles. Travis WD has been cited the most frequently. The main topics of research in this field are Lung Cancer, CT, and Deep Learning, which have been identified as long-term research hotspots. The GGNs-related marker is a major research trend in this field.

Conclusion

This study represents the inaugural bibliometric analysis of applied research on ground-glass lung nodules utilizing three established bibliometric software. The bibliometric analysis of this study elucidates the prevailing research themes and trends in the field of GGNs over the past decade. It also furnishes pertinent recommendations for researchers to provide objective descriptions and comprehensive guidance for future related research.

Worldwide research landscape of artificial intelligence in lung disease: A scientometric study

Purpose

To perform a comprehensive bibliometric analysis of the application of artificial intelligence (AI) in lung disease to understand the current status and emerging trends of this field.

Materials and methods

AI-based lung disease research publications were selected from the Web of Science Core Collection. Citespace, VOS viewer and Excel were used to analyze and visualize co-authorship, co-citation, and co-occurrence analysis of authors, keywords, countries/regions, references and institutions in this field.

Results

Our study included a total of 5210 papers. The number of publications on AI in lung disease showed explosive growth since 2017. China and the United States lead in publication numbers. The most productive author were Li, Weimin and Qian Wei, with Shanghai Jiaotong University as the most productive institution. Radiology was the most co-cited journal. Lung cancer and COVID-19 emerged as the most studied diseases. Deep learning, convolutional neural network, lung cancer, radiomics will be the focus of future research.

Conclusions

AI-based diagnosis and treatment of lung disease has become a research hotspot in recent years, yielding significant results. Future work should focus on establishing multimodal AI models that incorporate clinical, imaging and laboratory information. Enhanced visualization of deep learning, AI-driven differential diagnosis model for lung disease and the creation of international large-scale lung disease databases should also be considered.

Global Trends in Research of Perioperative Analgesia Over Past 10 Years: A Bibliometric Analysis

Background

The postoperative acute pain caused by surgery has been a major problem plaguing anesthesiologists, and even some acute pain progresses to chronic pain syndrome, terribly reducing the quality of life of patients. To this end, increasing attention has been paid to the management of perioperative analgesia. At present, with the increase of research on perioperative analgesia, the understanding and solution of this clinical problem have been further developed. Bibliometrics can estimate research hot-spots and trends of related fields in a certain period of time. However, a systematic bibliometric analysis has not been conducted to explore current research hotspots and future development trends, which is thus the purpose of this study.

Methods

Articles and reviews published from 2012 to 2021 were retrieved from the Web of Science Core Collection (WoSCC) database, and the bibliometric analysis of the keywords and references of articles was performed using VOSviewer1.6.18. Besides, the number of articles related to perioperative analgesia in term of countries, affiliations, authors, and journals were analyzed.

Results

Finally, 3157 articles meeting the screening requirements were retrieved, and it was hereby found that the research on perioperative analgesia had received more attention and interest in the past 10 years, with the United States making more contributions, where there were eight of the top ten affiliations by the number of publications. Kaye AD was the most active researcher in this field. Most related articles were published in Anesthesia and Analgesia, accounting for 2.76% of all literature. Enhanced recovery after surgery, different types of anesthesia and multi-mode analgesic drug intervention were the main trends and hotspots.

Conclusion

Perioperative analgesia has attracted considerable academic interest. In the past decade, the effects of enhanced recovery after surgery, different types of anesthesia and multi-mode analgesic drug intervention on perioperative analgesia have become the research hotspots, which are also likely to be the focus of future study.

Knowledge mapping visualization of the pulmonary ground-glass opacity published in the web of science

Objectives

With low-dose computed tomography(CT) lung cancer screening, many studies with an increasing number of patients with ground-glass opacity (GGO) are published. Hence, the present study aimed to analyze the published studies on GGO using bibliometric analysis. The findings could provide a basis for future research in GGO and for understanding past advances and trends in the field.

Methods

Published studies on GGO were obtained from the Web of Science Core Collection. A bibliometric analysis was conducted using the R package and VOSviewer for countries, institutions, journals, authors, keywords, and articles relevant to GGO. In addition, a bibliometric map was created to visualize the relationship.

Results

The number of publications on GGO has been increasing since 2011. China is ranked as the most prolific country; however, Japan has the highest number of citations for its published articles. Seoul National University and Professor Jin Mo Goo from Korea had the highest publications. Most top 10 journals specialized in the field of lung diseases. Radiology is a comprehensive journal with the greatest number of citations and highest H-index than other journals. Using bibliometric analysis, research topics on "prognosis and diagnosis," "artificial intelligence," "treatment," "preoperative positioning and minimally invasive surgery," and "pathology of GGO" were identified. Artificial intelligence diagnosis and minimally invasive treatment may be the future of GGO. In addition, most top 10 literatures in this field were guidelines for lung cancer and pulmonary nodules.

Conclusions

The publication volume of GGO has increased rapidly. The top three countries with the highest number of published articles were China, Japan, and the United States. Japan had the most significant number of citations for published articles. Most key journals specialized in the field of lung diseases. Artificial intelligence diagnosis and minimally invasive treatment may be the future of GGO.

Current global research landscape on COVID-19 and cancer: Bibliometric and visualization analysis

BACKGROUND

Cancer is a severe public health issue that seriously jeopardizes global health. In individuals with coronavirus disease 2019 (COVID-19), cancer is considered an independent risk factor for severe illness and increased mortality.

AIM

To identify research hotspots and prospects, we used bibliometrics to examine the global production of COVID-19 literature published in the field of oncology.

METHODS

Data on publication output were identified based on the Scopus database between January 1, 2020, and June 21, 2022. This study used VOSviewer to analyze collaboration networks among countries and assess the terms most often used in the titles and abstracts of retrieved publications to determine research hotspots linked to cancer and COVID-19. The Impact Index Per Article for the top 10 high-cited papers collected from Reference Citation Analysis (RCA) are presented.

RESULTS

A total of 7015 publications were retrieved from the database. The United States published the greatest number of articles (2025; 28.87%), followed by Italy (964; 13.74%), the United Kingdom (839; 11.96%), and China (538; 7.67%). The University of Texas MD Anderson Cancer Center (n = 205, 2.92%) ranked first, followed by the Memorial Sloan-Kettering Cancer Center (n = 176, 2.51%). The European Journal of Cancer (n = 106, 1.51%) ranked first, followed by the Frontiers in Oncology (n = 104, 1.48%), Cancers (n = 102, 1.45%), and Pediatric Blood and Cancer (n = 95; 1.35%). The hot topics were stratified into "cancer care management during the COVID-19 pandemic"; and "COVID-19 vaccines in cancer patients".

CONCLUSION

This is the first bibliometric analysis to determine the present state and upcoming hot themes related to cancer and COVID-19 and vice versa using VOSviewer during the early stages of the pandemic. The emergence of hot themes related to cancer and COVID-19 may aid researchers in identifying new research areas in this field.

Bibliometric analysis of global research trends on small-cell lung cancer (2012–2021)

Background

Small-cell lung cancer (SCLC) is a recalcitrant tumor with a poor prognosis. With the rise of SCLC research in the past decade, this study aims to analyze the foundation and frontiers of SCLC research through bibliometric analysis.

Methods

Relevant publications from the Web of Science Core Collection were retrieved on January 3, 2022. R package bibliometrix and EXCEL2019 were used to analyze quantitative variables. Bibliometric mapping was constructed by VOS viewer and CiteSpace software to visualize citation, co-authorship, co-occurrence, and co-citation analysis of countries/regions, organizations, authors, references, and keywords.

Results

A total of 2,361 publications related to SCLC were identified with the total amount of articles steadily increasing, where China is the most productive country with 859 papers. Scholars and organizations from the United States, China, and Europe are primary sources of this research, among which the University of Texas MD Anderson Cancer Center made the most contribution to the field with 122 papers. Lung Cancer published the highest number of SCLC-related articles with a total of 121, while the Journal of Thoracic Oncology received the most citations totaling 3,098. Rudin, Charles M., and Sage, Julien are the most creative author. Leora, Horn, 2018, New Engl J Med and Rudin, Charles M., Nat Genet, 2012 can be categorized as classic literature owing to their high citations or strong sigma value. “Heterogeneity & Subtypes” and “Immunotherapy” may be the new frontiers in the SCLC domain.

Conclusion

Research on SCLC showed an upward trend based on the current global situation. Moreover, the current scope of collaboration in SCLC research is chiefly regional, which should further focus on transnational cooperation in the future. More attention should be devoted to “Heterogeneity & Subtypes” and “Immunotherapy”, which will be the hotspots in future research.