A comparison of 18 F-FDG PET-based radiomics and deep learning in predicting regional lymph node metastasis in patients with resectable lung adenocarcinoma: a cross-scanner and temporal validation study.

Journal: Nuclear medicine communications
Published Date: Sep 21, 2023

Abstract

OBJECTIVE: The performance of 18 F-FDG PET-based radiomics and deep learning in detecting pathological regional nodal metastasis (pN+) in resectable lung adenocarcinoma varies, and their use across different generations of PET machines has not been thoroughly investigated. We compared handcrafted radiomics and deep learning using different PET scanners to predict pN+ in resectable lung adenocarcinoma.

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.
  • Bee-Song Chang
    Department of Cardiothoracic Surgery, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, .
  • Chih-Bin Lin
    Department of Internal Medicine, Hualien Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, .
  • Yen-Chang Chen
    School of Medicine, College of Medicine, Tzu Chi University, .
  • Hsin-Hon Lin
    Department of Medical Imaging and Radiological Sciences, College of Medicine, Chang Gung University, Taoyuan and .
  • Shu-Hsin Liu
    Department of Medical Imaging and Radiological Sciences, Tzu Chi University of Science and Technology, .

Keywords

External Resources

Popular Topics
Recent Journals