Prognostic value of combining clinical factors, F-FDG PET-based intensity, volumetric features, and deep learning predictor in patients with EGFR-mutated lung adenocarcinoma undergoing targeted therapies: a cross-scanner and temporal validation study.

Journal: Annals of nuclear medicine
Published Date: May 5, 2024

Abstract

OBJECTIVE: To investigate the prognostic value of F-FDG PET-based intensity, volumetric features, and deep learning (DL) across different generations of PET scanners in patients with epidermal growth factor receptor (EGFR)-mutated lung adenocarcinoma receiving tyrosine kinase inhibitor (TKI) treatment.

Authors

  • Kun-Han Lue
    Department of Medical Imaging and Radiological Sciences, Tzu Chi University of Science and Technology, .
  • Yu-Hung Chen
    Department of Medical Imaging and Radiological Sciences, Tzu Chi University of Science and Technology, .
  • Sung-Chao Chu
    Department of Hematology and Oncology, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien, Taiwan.
  • Chih-Bin Lin
    Department of Internal Medicine, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, .
  • Tso-Fu Wang
    Department of Hematology and Oncology, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Hualien, Taiwan.
  • Shu-Hsin Liu
    Department of Medical Imaging and Radiological Sciences, Tzu Chi University of Science and Technology, .

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