Bibliometric analysis of CT-based atherosclerosis plaque imaging in coronary artery disease: from “gatekeeper” of invasive angiography to “whistleblower” of high-risk patients

Introduction

Coronary artery disease (CAD) is the major cause of morbidity and mortality worldwide (1-4). Previously, coronary computed tomography angiography (CCTA), as the “gatekeeper” of coronary angiography, played an important role in the clinical pathway of CAD patients, through the non-invasive assessment of coronary stenosis and ischemia (5-7). With the further understanding of the pathophysiology of atherosclerosis, we have recognized that the mechanism of stenosis and ischemia being associated with coronary adverse events is actually due to the fact that they are indirect substitutes for plaque burden (2,8,9), which has a more direct correlation with coronary adverse events (2,9). This contributes to the deepening and development of coronary atherosclerotic plaque studies (2,10).

Computed tomography (CT)-based coronary atherosclerotic plaque studies are booming, and there have been a number of large cohort studies confirming the significant value of coronary atherosclerotic plaque imaging in CAD (11,12). However, to date, few studies have meaningfully investigated the current state of coronary atherosclerotic plaque studies, including research trends, subsequent focus, and future directions. Therefore, evaluating the current state of research on coronary atherosclerotic plaque will help to clarify the current research landscape, identify research trends, explore keywords flows, and further analyze its underlying causes and deep significance.

Bibliometric analysis is a rigorous and objective methodology for exploring large-scale scientific data (13), which allows for an objective and quantitative evaluation of academic output and the identification of research trends and hot spots. By sourcing data from databases such as Web of Science, and using easily accessible tools such as Bibliometrix and VOSviewer, this method can present objective and visualizable results in a reader-friendly manner (14).

The purpose of this study was to conduct a bibliometric analysis of coronary atherosclerotic plaque studies in CAD based on CT, and to further present the research landscape, identify research trends, and their keyword flows, assess the challenges and potentials, and to explore possible solutions and future directions of research.

Methods

Data source and search criteria

Our data was sourced from the Web of Science Core Collection (WoSCC). The search was conducted on 16 July 2024, with the WosCC database having been updated on 12 July 2024. To accurately retrieve the relevant publications, we used the following search formula: (plaque or atherosclerosis) AND (CT or CCTA or CTCA or “computed tomography” or “coronary angiography” or “coronary computed tomography angiography”) AND (“coronary artery disease” or “coronary heart disease” or CAD or CHD or “myocardial infarction” or “coronary syndrome” or ACS or MI or “ischemic heart disease” or IHD or angina). Based on the publication types categorized in WosCC, we only included articles and reviews written in English.

Data processing

To ensure the data accuracy, the documents were manually screened by title, abstract, keywords, and full text content when needed. The inclusion criteria were as follows: (I) study on CADs; (II) study involved coronary atherosclerotic plaque evaluation by CT; and (III) study explored the association between coronary atherosclerotic plaque and CAD. All the retrieved results and their cited references included in this study from WoSCC were exported as plain text form and then imported into the bibliometric analysis software, Bibliometrix (https://www.bibliometrix.org/home/) and VOSviewer (https://www.vosviewer.com/).

Data analysis and visualization

Based on the WoSCC database, using R (version 4.2.0; https://cran.r-project.org/) with Bibliometrix package and VOSviewer, we obtained fundamental information about annual publication counts, keywords, authors, institutions, countries, publication sources, cited references, and their citations. Data aggregation was performed in Microsoft Excel (Microsoft Corp., Redmond, WA, USA). Trend analyses of annual publications and information on authors and institutions were displayed by using Origin (version 2023b; https://www.originlab.com/2023b). The h-index is an indicator of a researcher’s scholarly work impact and productivity, meaning that a researcher has published at least h articles, with each having been cited at least h times. Scimago Graphica (https://www.graphica.app/) was applied to show the global distributions of publications and citations. The top 10 most cited articles were analyzed.

To explore the hotspots and focuses of the research field in different periods, keyword temporal analysis was conducted by constructing a co-occurrence network map and temporal overlay visualization map of keywords. Then, the keywords were further categorized, and temporal analysis was performed by category.

In the co-citation analysis, co-citation network maps of the cited references and their journals were constructed. Co-citation analysis is often used to study the structure and dynamic development of a field, which enables identification of influential articles and exploration of the interconnections among them (15). Briefly, if two (or more) papers had been cited by one or more later papers, these 2 papers constitute a co-citation relationship.

Results

Publications and citations analysis

A total of 2,195 publications from 1990 to 2024 were identified in this study, including 1,970 articles and 225 reviews. As shown in Figure 1, the annual number of publications in the field of CT-based atherosclerosis plaque imaging in CAD experienced a strong upward trend. The top 10 most cited articles are listed in Table 1, of which there was 1 review and 9 articles. An article written by Neeland et al. in 2002 stands out with 2,823 citations.

Figure 1 Trend analysis of annual publications in the field of CT-based atherosclerosis plaque imaging in coronary artery disease. CT, computed tomography.

Keywords analysis

We constructed a co-occurrence network of high-frequency keywords (those that appeared more than 20 times), with a total of 44. Highly correlated keywords were more likely to be clustered together and assigned the same color label. These keywords were automatically grouped into four color clusters, with CAD as the central theme (Figure 2). The red clusters were in the majority, focused on stenosis, ischemia, disease course, and regression; yellow focused on plaque and metabolic; blue focused on calcification and chronic course; and green focused on inflammation, risk, and prevention. In the keyword analysis, “coronary artery disease” (n=773), “atherosclerosis” (n=543), “coronary calcification” (n=474), “coronary computed tomography angiography” (n=410), “computed tomography” (n=288), and “plaque” (n=223) were most frequently used as keywords in the study of CT-based atherosclerosis plaque imaging in CAD. The temporal analysis of keywords is shown in Figure 3.

Figure 2 Co-occurrence network map of keywords with at least 20 occurrences.

Figure 3 Keywords temporal analysis. The circles size represented the frequency of keyword occurrence, the circles position represented the median time of keyword occurrence, and the lines represented the interquartile range of the time of keyword occurrence. CCTA, coronary computed tomography angiography; CT, computed tomography; CTA, computed tomography angiography; EBCT, electron-beam computed tomography; MDCT, multi-detector computed tomography.

In order to better understand the research status and research trend of coronary atherosclerotic plaque, the keywords were manually categorized into 4 categories (disease, atherosclerotic plaque type, imaging technique, and study orientation), and further in-depth temporal analysis of keywords was performed. The results of the temporal analysis of these categorized keywords are shown in Figure 4A-4D, and the detailed descriptions of the results can be found in the Appendix 1. Notably, although machine learning (ML) and artificial intelligence (AI) techniques appeared late in the evolution until the fourth stage, they still appeared as high-frequency words in the category analysis.

Figure 4 Keywords temporal analysis in 4 categories: disease (A), atherosclerotic plaque type (B), imaging technique (C), and study orientation (D). The circle size represents the frequency of keyword occurrence, the circle position represents the median time of keyword occurrence, and the lines represent the interquartile range of the time of keyword occurrence. CAD-RADS, Coronary Artery Disease Reporting and Data System; CCTA, coronary computed tomography angiography; CT, computed tomography; CTA, computed tomography angiography; EAT, epicardial adipose tissue; EBCT, electron-beam computed tomography; HIV, human immunodeficiency virus; MACE, major adverse cardiovascular events; MDCT, multi-detector computed tomography; MRI, magnetic resonance imaging; Non-obstructive CAD, non-obstructive coronary artery disease; OCT, optical coherence tomography; PET, positron emission tomography; PCAT, pericoronary adipose tissue; PCI, percutaneous coronary intervention; SLE, systemic lupus erythematosus.

Through these temporal analyses, we found that the study of coronary atherosclerotic plaques can be generally divided into the following four stages: (I) initial stage (1990–1999, 42 publications): studies in this stage focused on the assessment of coronary artery calcification and analyzed the relationship between coronary artery calcification burden and CAD risk and patient prognosis (16); (II) slow rise stage (2000–2006, 195 publications): studies in this stage focused on the assessment of plaque and its resultant coronary stenosis, and CCTA began to play an important role as a diagnostic tool for coronary stenosis in both clinical and research practice (17); (III) Wavelike rise stage (2007–2016, 888 publications): researchers began to focus on high-risk plaques associated with acute coronary events, and qualitatively assessed high-risk plaques through some imaging features (18); (IV) Blooming stage (2017–2024, 1,070 publications): researchers began to study the quantitative assessment of different components of plaques and focused on the high-risk indicative role of larger low-density component burden of plaques (2,19). Especially after the 2020s, researchers started to explore the risk prediction efficacy difference of “high-risk plaques” at the lesion level and the individual level, and began to pay more attention to the risk prediction at the “individual level”.

To better analyze the potential associations between the categorized keywords, a Sankey diagram was drawn to more clearly display the flow trends between the categories (Figure 5). The results showed that coronary calcification was more commonly associated with progression of chronic diseases, such as CAD, cardiovascular disease, and coronary heart disease, whereas infarction, myocardial ischemia, acute coronary syndrome, and inflammation, which represent the acute course of the disease, were more commonly associated with plaque-related keywords such as as plaque, plaque progression, vulnerable plaque, high-risk plaque, non-calcified plaque, and plaque burden. The keyword of electron-beam computed tomography (EBCT) was strongly associated with coronary calcification. In the category of study orientation, a series of CTA-related keywords, mainly CCTA, showed the full coverage of the flow, which mainly accounted for calcification score, prognosis, and risk related, such as risk factor, risk assessment, risk stratification or risk prediction.

Figure 5 Sankey diagram of keywords categorization analysis.

Co-citation analysis of cited references and sources

Among the 32,485 cited references, a total of 149 cited references were analyzed with a minimum citation count of 50 (Figure S1). The co-citation map showed four distinct clusters in different colors. The most cited article was on CT-based assessment of coronary calcification, written by Agatston and published in the Journal of the American College of Cardiology (JACC) in 1990 (20), which had been cited 871 times. This article opened a new era of assessing the CAD burden in patients based on coronary calcification, and the calcification score assessment, epitomized as the Agatston score, which currently remains an important tool for primary prevention of CAD.

To evaluate the distribution of cited references in the journal, we created a co-citation network map of journals cited references. Of the 4,002 journals, we analyzed 82 journals with at least 100 citations respectively (Figure S2). The green and red clusters, which make up the majority, focused on cardiovascular, circulatory, and metabolic, whereas the blue cluster focused on radiology. Notably, The Journal of the American College of Cardiology stood out as the most frequently cited journal.

Publication analysis of countries, institutions, and authors

A total of 72 countries and 2,339 institutions were found to have participated in research in this field. The top ten countries of all articles included are listed in Table 2. The top 10 institutions according to the publication counts are shown in Table 3. An overview of the authors who had notable influence in their respective fields of expertise is presented in Table 4.

Discussion

The main findings of our study are as follows: the major study subjects shifted from calcified plaques to non-calcified plaques; the major study methods shifted from non-contrast CT to CCTA; the study contents shifted from assessment of stenosis and ischemia caused by plaques to the high-risk features of plaques as well as assessment of high-risk component burden; and the major clinical problem to be solved shifted from the diagnosis-oriented assessment of chronic disease burden to the prediction and prevention of acute events. Therefore, the CT plaque imaging enabled the CCTA to change from the “gatekeeper” of invasive angiography to the “whistleblower” of high-risk patients, and to play a more important role in the primary and secondary prevention of CAD patients.

The keywords categorization of temporal analysis showed some interesting findings. The categorization of disease showed that earlier studies focused on CAD associated metabolic and systemic diseases, whereas later studies focused more on acute coronary events, inflammation, and non-obstructive lesions. Correspondingly, in the categorization of plaques, early attention was given to calcified plaques, whereas later, more attention was given to non-calcified plaques, which was due to the understanding that calcification occurred as a healing response to intense necrotic plaque inflammation (2). Calcified plaques are predominantly associated with chronic disease burden and chronic course of metabolic diseases, whereas non-calcified plaques demonstrate stronger correlations with acute events, inflammation, and non-obstructive high-risk lesions (2,9,21-24). For both calcified and non-calcified plaques, there was a trend from qualitative to quantitative assessment. The categorization of study orientation showed a shift from CAD disease diagnosis, later to risk stratification, and then focused on the prevention of adverse events, to improve the prognosis of patients through accurate assessment, early prevention, and individualized treatment.

Moreover, we found that the four stages in coronary atherosclerotic plaque studies are closely related to the development of CT technology. (I) Initial stage [1990–1999]: in this stage, most of the studies were based on EBCT for assessment of coronary artery calcification to evaluate its presence and burden, due to the limitation of CT technology. The most representative study was that published in JACC by Agatston in 1990, which unveiled the quantitative assessment of coronary artery calcification and laid the foundation for subsequent calcification scores (20). (II) Slow rise stage [2000–2006]: with the advent of multi-detector computed tomography (MDCT), the focus of CCTA shifted to the assessment of coronary ischemia based on coronary stenosis, such as the relationship between calcification score and coronary stenosis and patient prognosis. (III) Wavelike rise stage [2007–2016]: at this stage, CT technology developed rapidly, a series of high-end CT scanners were integrated into clinical practice gradually, such as dual-source CT, wide-detector CT, and high-resolution detector CT. Meanwhile, intravascular imaging also developed rapidly during this period. Through observation of plaque characteristics of criminal lesions by intravascular imaging in patients with acute coronary events, researchers began to investigate the specific signs of these plaques on high-quality CCTA images, and to explore the qualitative identification of high-risk plaques by CCTA. (IV) Blooming stage [2017–2024]: in this stage, high-end CT were popularized globally, and photon-counting computed tomography (PCCT) made a shining debut in the later period of this stage. With the advent of several new CCTA assessment tools, plaque studies began to be combined with several functional imaging tools such as pericoronary adipose tissue (PCAT) and CT-fractional flow reserve (CT-FFR) to improve the prediction of subsequent adverse events in patients. Moreover, ML and AI technologies began to flourish at this stage. With the development of these technologies, we were able to better understand these high-risk plaque features and their pathophysiological basis, and to realize the quantitative assessment of plaque components.

Therefore, the main directions that can be explored for future studies are as follows: (I) identifying high-risk patients: as the “blooming stage” studies begins to focus on the “individual level” risk, the subsequent studies may need to shift from the lesion level to the individual level to better identify high-risk patients (2,11). (II) Accurate qualitative assessment: previously, due to the limitations of spatial and density resolution, as well as the understanding of the characteristic signs of napkin-ring sign (NRS), the identification of NRS was difficult. With technological improvements in high-end CT detectors, the spatial resolution of images has been improved. Moreover, ML and AI technologies have been developing rapidly. Tools for identifying high-risk plaque features, which were trained and modeled with the help of experienced radiologists, are expected to better identify NRS, thus improving the accuracy of qualitative assessment of high-risk plaques. (III) Accurate quantitative assessment: as the results of keyword temporal analysis indicate, quantitative assessment is an important trend in plaque studies. However, quantitative plaque assessment still has several limitations, such as long post-processing time, especially in patients with diffuse lesions (25). In the future, ML and AI technologies may help us to quantitatively assess plaque more easily and accurately, which may contribute to promoting their clinical application (26-29). Besides, previous CT techniques have been found to over-assess the severity of calcified lesions; due to the partial volume effect of severe calcification, heavily calcified lesions tend to appear larger on CT than they actually are (30-32). The advent of PCCT foreshadows the expectation that severely calcified lesion burden will be able to be assessed more accurately (30,33). (IV) Dynamic changes in plaque: Previous studies have shown that the volume, composition, and specific phenotype of coronary atherosclerotic plaques are dynamically changed (34,35). Lesions that rapidly progress in a short time were more likely to incur adverse coronary events (36-39). Therefore, observation of changes in qualitative and quantitative characteristics of coronary atherosclerotic plaques assessed by serial CCTA may allow better identification of high-risk patients as well as assessment of treatment efficacy. (V) Some emerging areas: with the development of radiomics, analysis may be conducted in conjunction with other genetic or histological data, combining imaging features of plaque with tissue biological features and gene expression status, such as radiogenomics, radiotranscriptomics, and radiopathmics, which may provide new insights into the mechanisms of CAD occurrence and development (29,40,41).

This study has several limitations. First, this study used WoSCC a solitary core data source, and only studies reported in English were included, which might have led to potential selection bias. Second, there may be a “positive bias” in the included studies, as studies with positive or statistically significant results were more likely to be published, whereas studies with invalid or negative results might have been less likely to be reported. Third, earlier studies are more likely to receive high citations, whereas newer ones have relatively lower citations, which may have introduced some bias in the analysis. In addition, this study presented an overview of the current state of CT-based atherosclerotic plaque imaging in CAD and explored its trends through bibliometric analyses, whereas there was limited analysis of individual studies, which is similar to other bibliometric analyses.

Conclusions

Through bibliometric analysis, we found that coronary atherosclerotic plaque studies have been evolving and are now blooming, in tandem with the development of technology and our understanding of the lesions and the disease over the past 30 years. There are obvious trends and certain flow directions in these studies, which help us to identify the current research challenges and potentials, as well as future research directions. We believe that the CT plaque imaging enabled CCTA to transition from the “gatekeeper” of invasive angiography to the “whistleblower” of high-risk patients, and to play a more important role in the primary and secondary prevention of CAD patients.

Acknowledgments

None.

Footnote

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-239/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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(English Language Editor: J. Jones)