Deep Learning Model to Classify and Monitor Idiopathic Scoliosis in Adolescents Using a Single Smartphone Photograph.

Journal: JAMA network open
Published Date: Aug 1, 2023

Abstract

IMPORTANCE: Adolescent idiopathic scoliosis (AIS) is the most common pediatric spinal disorder. Routine physical examinations by trained personnel are critical to diagnose severity and monitor curve progression in AIS. In the presence of concerning malformation, radiographs are necessary for diagnosis or follow-up, guiding further management, such as bracing correction for moderate malformation and spine surgery for severe malformation. If left unattended, progressive deterioration occurs in two-thirds of patients, leading to significant health concerns for growing children.

Authors

  • Teng Zhang
    College of Veterinary Medicine, Hebei Agricultural University, Baoding, Hebei 071000, China.
  • Chuang Zhu
    The Center for Data Science, the Beijing Key Laboratory of Network System Architecture and Convergence, the School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Xitucheng Road, Beijing, China. czhu@bupt.edu.cn.
  • Yongkang Zhao
    School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China.
  • Moxin Zhao
    Digital Health Laboratory, School of Clinical Medicine, Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.
  • Zhihao Wang
    School of Information Science and Engineering, Shandong Normal University, Jinan, Shandong, China; Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology, Jinan, Shandong, China.
  • Ruoning Song
    School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China.
  • Nan Meng
  • Alisha Sial
    SpineLabs, St George and Sutherland Clinical School, University of New South Wales, Sydney, Australia.
  • Ashish Diwan
    SpineLabs, St George and Sutherland Clinical School, University of New South Wales, Sydney, Australia.
  • Jun Liu
    Department of Radiology, Second Xiangya Hospital, Changsha, Hunan, China.
  • Jason P Y Cheung
    Digital Health Laboratory, School of Clinical Medicine, Faculty of Medicine, The University of Hong Kong, Hong Kong Special Administrative Region, China.

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