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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...

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Detalles Bibliográficos
Autores principales: Zhang, Xiaohan, Zhu, Xueping, Jiang, Yuchen, Wang, Huan, Guo, Zezhen, Du, Bai, Hu, Yuanhui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2023
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.
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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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