2.5D deep learning based on multi-parameter MRI to differentiate primary lung cancer pathological subtypes in patients with brain metastases.

Journal: European journal of radiology
Published Date: Aug 28, 2024

Abstract

BACKGROUND: Brain metastases (BMs) represents a severe neurological complication stemming from cancers originating from various sources. It is a highly challenging clinical task to accurately distinguish the pathological subtypes of brain metastatic tumors from lung cancer (LC).The utility of 2.5-dimensional (2.5D) deep learning (DL) in distinguishing pathological subtypes of LC with BMs is yet to be determined.

Authors

  • Jinling Zhu
    Guangdong Provincial Hospital of Chinese Medicine, Guangzhou, Guangdong, 510000, China.
  • Li Zou
    State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, Yunnan, China.
  • Xin Xie
    School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, 200093, PR China.
  • Ruizhe Xu
    Department of Radiotherapy & Oncology, The Second Affiliated Hospital of Soochow University, Suzhou, 215004, China.
  • Ye Tian
    State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics and Center for Molecular Imaging and Translational Medicine, School of Public Health, Xiamen University, Xiamen, 361102, China.
  • Bo Zhang
    Department of Clinical Pharmacology, Key Laboratory of Clinical Cancer Pharmacology and Toxicology Research of Zhejiang Province, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310006, PR China.

Keywords

External Resources

Popular Topics
Recent Journals