The 100 most cited articles investigating the radiological staging of oesophageal and junctional cancer: a bibliometric analysis

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Abstract

Objectives: Accurate staging of oesophageal cancer (OC) is vital. Bibliometric analysis highlights key topics and publications that have shaped understanding of a subject. The 100 most cited articles investigating radiological staging of OC are identified. Methods: The Thomas Reuters Web of Science database with search terms including “CT, PET, EUS, oesophageal and gastro-oesophageal junction cancer” was used to identify all English language, full-script articles. The 100 most cited articles were further analysed by topic, journal, author, year and institution. Results: A total of 5,500 eligible papers were returned. The most cited paper was Flamen et al. (n = 306), investigating the utility of positron emission tomography (PET) for the staging of patients with potentially operable OC. The most common research topic was accuracy of staging investigations (n = 63). The article with the highest citation rate (38.00), defined as the number of citations divided by the number of complete years published, was Tixier et al. investigating PET texture analysis to predict treatment response to neo-adjuvant chemo-radiotherapy, cited 114 times since publication in 2011. Conclusion: This bibliometric analysis has identified key publications regarded as important in radiological OC staging. Articles with the highest citation rates all investigated PET imaging, suggesting this modality could be the focus of future research. Main Messages: • This study identifies key articles that investigate radiological staging of oesophageal cancer. • The most common topic was accuracy of staging investigations. • The article with the highest citation rate investigated the use of texture analysis in PET images.

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Foley, K. G., Powell, A., Lewis, W. G., & Roberts, S. A. (2016). The 100 most cited articles investigating the radiological staging of oesophageal and junctional cancer: a bibliometric analysis. Insights into Imaging, 7(4), 619–628. https://doi.org/10.1007/s13244-016-0505-6

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