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Role of physical exercise in improving pulmonary function: a radiomic perspective (PhD Academy Award)
  1. Xinyuan Ge
  1. Department of Epidemiology, Nanjing Medical University, Nanjing, Jiangsu, China
  1. Correspondence to Dr Xinyuan Ge; gexinyuan{at}stu.njmu.edu.cn

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What did I do?

The primary focus of my PhD research was to investigate the relationship between physical exercise and lung function, with a particular emphasis on imaging radiomic features derived from quantitative CT (qCT). My study aimed to uncover how different levels and intensities of physical exercise influence lung structural and functional parameters, as quantified by advanced radiomic analysis. Specifically, I evaluated the interplay between exercise-related parameters (eg, metabolic equivalent tasks, MET-min/week) and lung texture-based radiomic features, analysing their predictive value in chronic pulmonary disease progression and functional decline in lung capacity (figure 1).

Figure 1

Design of the study. FEV1, forced expiratory volume in 1 s; FVC, forced vital capacity; GLCM, grey-level co-occurrence matrix; GLDM, grey-level dependence matrix; GLRLM, grey-level run length matrix; GLSZM, grey-level size zone matrix; MET, metabolic equivalent value; NGTDM, neighbourhood grey tone difference matrix; VO2, volume of oxygen.

Why did I do it?

Radiomic features have been demonstrated to be powerful predictors of lung diseases and pulmonary function.1–3 At the same time, physical exercise is well established as a key factor …

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Footnotes

  • Correction notice This article has been corrected since it published Online First. The acknowledgements section has been updated.

  • Contributors The article is interpreted by the sole author.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; internally peer reviewed.