CT-based radiomics and machine learning to predict spread through air space in lung adenocarcinoma.

Journal: European radiology
Published Date: Feb 28, 2020

Abstract

PURPOSE: Spread through air space (STAS) is a novel invasive pattern of lung adenocarcinoma and is also a risk factor for recurrence and worse prognosis of lung adenocarcinoma. The aims of this study are to develop and validate a computed tomography (CT)‑based radiomics model for preoperative prediction of STAS in lung adenocarcinoma.

Authors

  • Changsi Jiang
    Department of Radiology, Shenzhen People's Hospital, the Second Clinical Medical College of Jinan University, Shenzhen, 518020, China.
  • Yan Luo
    School of Public Health and Management, Research Center for Medicine and Social Development, Innovation Center for Social risk Governance in Health, Chongqing Medical University, Chongqing 400016, China.
  • Jialin Yuan
    Department of Radiology, Shenzhen People's Hospital, No.1017 Dongmen North Road, Luohu District, Shenzhen, Guangdong, 518020, PR China.
  • Shuyuan You
    Department of Pathology, Shenzhen People's Hospital, the Second Clinical Medical College of Jinan University, Shenzhen, 518020, China.
  • Zhiqiang Chen
    Department of Engineering Physics, Tsinghua University, Beijing, 100084, China.
  • Mingxiang Wu
    Department of Radiology, Shenzhen People's Hospital, No.1017 Dongmen North Road, Luohu District, Shenzhen, Guangdong, 518020, PR China.
  • Guangsuo Wang
    Department of Thoracic Surgery, Shenzhen People's Hospital, the Second Clinical Medical College of Jinan University, Shenzhen, 518020, China.
  • Jingshan Gong
    Department of Radiology, Shenzhen People's Hospital, the Second Clinical Medical College of Jinan University, Shenzhen, 518020, China. jshgong@sina.com.

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