Predicting Lymphovascular Invasion in Non-small Cell Lung Cancer Using Deep Convolutional Neural Networks on Preoperative Chest CT.

Journal: Academic radiology
Published Date: Jun 6, 2024

Abstract

RATIONALE AND OBJECTIVES: Lymphovascular invasion (LVI) plays a significant role in precise treatments of non-small cell lung cancer (NSCLC). This study aims to build a non-invasive LVI prediction diagnosis model by combining preoperative CT images with deep learning technology.

Authors

  • Jian Wang
    Veterinary Diagnostic Center, Shanghai Animal Disease Control Center, Shanghai, China.
  • Yang Yang
    Department of Gastrointestinal Surgery, The Third Hospital of Hebei Medical University, Shijiazhuang, China.
  • Zongyu Xie
    The First Affiliated Hospital of Bengbu Medical College, No. 287 Changhuai Road, Bengbu Anhui, 233004, China. zongyuxie@sina.com.
  • Guoqun Mao
    Department of Radiology, Tongde Hospital of Zhejiang Province, No. 234 Gucui Road, Zhejiang Province, 310012, Hangzhou, China.
  • Chen Gao
    Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China.
  • Zhongfeng Niu
    Department of Radiology, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Hongli Ji
    Jianpei Technology Co., Ltd., Hangzhou, 310000, China.
  • Linyang He
    Hangzhou Jianpei Technology Co., Ltd, Hangzhou, China.
  • Xiandi Zhu
    Department of Radiology, Tongde Hospital of Zhejiang Province, No. 234 Gucui Road, Zhejiang Province, 310012, Hangzhou, China.
  • Hengfeng Shi
    Department of Radiology, Anqing Municipal Hospital, Anqing, Anhui, China.
  • Maosheng Xu
    Department of Radiology, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Hangzhou, China.

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