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Science mapping analysis of computed tomography-derived fractional flow reverse: a bibliometric review from 2012 to 2022
BACKGROUND: Computed tomography-derived fractional flow reserve (CT-FFR) is a non-invasive imagological examination used for diagnosing suspected coronary atherosclerotic heart disease, providing the morphological and functional value on a three-dimensional (3D) coronary artery model. This article a...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10498214/ https://www.ncbi.nlm.nih.gov/pubmed/37711816 http://dx.doi.org/10.21037/qims-22-1094 |
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author | Zhang, Xiaohan Zhu, Xueping Jiang, Yuchen Wang, Huan Guo, Zezhen Du, Bai Hu, Yuanhui |
author_facet | Zhang, Xiaohan Zhu, Xueping Jiang, Yuchen Wang, Huan Guo, Zezhen Du, Bai Hu, Yuanhui |
author_sort | Zhang, Xiaohan |
collection | PubMed |
description | BACKGROUND: Computed tomography-derived fractional flow reserve (CT-FFR) is a non-invasive imagological examination used for diagnosing suspected coronary atherosclerotic heart disease, providing the morphological and functional value on a three-dimensional (3D) coronary artery model. This article aimed to collate the existing knowledge and predict this novel technology’s future research hotspots. METHODS: To collect data, 1,712 articles were retrieved from the Web of Science Core Collection (WoSCC) database from 2012–2022. CiteSpace5.8.R3 was used to visually analyze the research status and predict future research hotspots. RESULTS: Firstly, the United States, China, and the Netherlands were identified as the countries having published the most articles about CT-FFR. Jonathan Leipsic’s group ranked first for the highest number of published articles. Secondly, the visualized analysis indicated that the exploration of CT-FFR is multi-disciplinary and involves cardiology, radiology, engineering, and computer science. Thirdly, the hotspots in this field, which were inferred from the keyword distribution and clustering, included the following: “diagnostic performance”, “accuracy”, and the “prognostic value” of CT-FFR, and comparison of CT-FFR and other imaging methods sharing similarities. The research frontiers included technologies utilized to obtain more accurate CT-FFR values, such as artificial intelligence (AI) and deep learning. CONCLUSIONS: As the first visualized bibliometric analysis on CT-FFR, this study captured the current accumulated information in this field and offer more insight and guidance for future research. |
format | Online Article Text |
id | pubmed-10498214 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-104982142023-09-14 Science mapping analysis of computed tomography-derived fractional flow reverse: a bibliometric review from 2012 to 2022 Zhang, Xiaohan Zhu, Xueping Jiang, Yuchen Wang, Huan Guo, Zezhen Du, Bai Hu, Yuanhui Quant Imaging Med Surg Original Article BACKGROUND: Computed tomography-derived fractional flow reserve (CT-FFR) is a non-invasive imagological examination used for diagnosing suspected coronary atherosclerotic heart disease, providing the morphological and functional value on a three-dimensional (3D) coronary artery model. This article aimed to collate the existing knowledge and predict this novel technology’s future research hotspots. METHODS: To collect data, 1,712 articles were retrieved from the Web of Science Core Collection (WoSCC) database from 2012–2022. CiteSpace5.8.R3 was used to visually analyze the research status and predict future research hotspots. RESULTS: Firstly, the United States, China, and the Netherlands were identified as the countries having published the most articles about CT-FFR. Jonathan Leipsic’s group ranked first for the highest number of published articles. Secondly, the visualized analysis indicated that the exploration of CT-FFR is multi-disciplinary and involves cardiology, radiology, engineering, and computer science. Thirdly, the hotspots in this field, which were inferred from the keyword distribution and clustering, included the following: “diagnostic performance”, “accuracy”, and the “prognostic value” of CT-FFR, and comparison of CT-FFR and other imaging methods sharing similarities. The research frontiers included technologies utilized to obtain more accurate CT-FFR values, such as artificial intelligence (AI) and deep learning. CONCLUSIONS: As the first visualized bibliometric analysis on CT-FFR, this study captured the current accumulated information in this field and offer more insight and guidance for future research. AME Publishing Company 2023-07-19 2023-09-01 /pmc/articles/PMC10498214/ /pubmed/37711816 http://dx.doi.org/10.21037/qims-22-1094 Text en 2023 Quantitative Imaging in Medicine and Surgery. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/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 (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Original Article Zhang, Xiaohan Zhu, Xueping Jiang, Yuchen Wang, Huan Guo, Zezhen Du, Bai Hu, Yuanhui Science mapping analysis of computed tomography-derived fractional flow reverse: a bibliometric review from 2012 to 2022 |
title | Science mapping analysis of computed tomography-derived fractional flow reverse: a bibliometric review from 2012 to 2022 |
title_full | Science mapping analysis of computed tomography-derived fractional flow reverse: a bibliometric review from 2012 to 2022 |
title_fullStr | Science mapping analysis of computed tomography-derived fractional flow reverse: a bibliometric review from 2012 to 2022 |
title_full_unstemmed | Science mapping analysis of computed tomography-derived fractional flow reverse: a bibliometric review from 2012 to 2022 |
title_short | Science mapping analysis of computed tomography-derived fractional flow reverse: a bibliometric review from 2012 to 2022 |
title_sort | science mapping analysis of computed tomography-derived fractional flow reverse: a bibliometric review from 2012 to 2022 |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10498214/ https://www.ncbi.nlm.nih.gov/pubmed/37711816 http://dx.doi.org/10.21037/qims-22-1094 |
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