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Assessment of Computed Tomography Perfusion Research Landscape: A Topic Modeling Study.

Burak B Ozkara1, Mert Karabacak2, Konstantinos Margetis2

  • 1Department of Neuroradiology, MD Anderson Cancer Center, 1400 Pressler Street, Houston, TX 77030, USA.

Tomography (Ann Arbor, Mich.)
|November 21, 2023
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Summary

Topic modeling of computed tomography perfusion (CTP) research reveals key trends. "Postprocessing" and "Artificial Intelligence" are emerging as the most significant topics in recent CTP studies.

Keywords:
CT perfusionnatural language processingtopic modeling

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Area of Science:

  • Medical Imaging
  • Radiology
  • Data Science in Medicine

Background:

  • The exponential growth in scholarly articles presents challenges for researchers in synthesizing information.
  • Computed tomography perfusion (CTP) has seen rapid advancements, necessitating a structured overview of its research landscape.
  • Topic modeling offers a novel approach to analyze and understand large volumes of scientific literature.

Purpose of the Study:

  • To apply topic modeling to the scientific literature of computed tomography perfusion (CTP).
  • To identify and analyze the prevalent and trending research topics within CTP.
  • To provide insights into the evolving focus of CTP research over time.

Main Methods:

  • A comprehensive literature search was performed on the Scopus database (2000-2023).
  • The BERTopic model was employed to derive and group research topics from identified CTP articles.
  • Linear regression models were used to analyze topic trends, particularly for the 2020s.

Main Results:

  • A total of 12 distinct topics were identified, including 'Tumor Vascularity', 'Stroke Assessment', 'Myocardial Perfusion', and 'Artificial Intelligence'.
  • The most prevalent topics were 'Tumor Vascularity' and 'Stroke Assessment'.
  • Emerging trends in the 2020s highlight 'Postprocessing' and 'Artificial Intelligence' as the most significant trending topics.

Conclusions:

  • Topic modeling is an effective method for navigating and understanding the expanding CTP research field.
  • The identified topics provide a structured overview of CTP applications and research focus areas.
  • The increasing prominence of 'Postprocessing' and 'Artificial Intelligence' signals key future directions in CTP research.