A study on whether deep learning models based on CT images for bone density classification and prediction can be used for opportunistic osteoporosis screening.

Journal: Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA
PMID: 37670164

Abstract

UNLABELLED: This study utilized deep learning to classify osteoporosis and predict bone density using opportunistic CT scans and independently tested the models on data from different hospitals and equipment. Results showed high accuracy and strong correlation with QCT results, showing promise for expanding osteoporosis screening and reducing unnecessary radiation and costs.

Authors

  • Tao Peng
    Department of Biology, Shantou University, Shantou, China.
  • Xiaohui Zeng
    Department of Radiology, Affiliated Hospital of Chengdu University, 82 2Nd N Section of Second Ring Rd, Chengdu, 610081, Sichuan Province, China.
  • Yang Li
    Occupation of Chinese Center for Disease Control and Prevention, Beijing, China.
  • Man Li
    Department of Psychogeriatrics, Kangci Hospital of Jiaxing, Tongxiang, Zhejiang, China.
  • Bingjie Pu
    Department of Radiology, Affiliated Hospital of Chengdu University, 82 2Nd N Section of Second Ring Rd, Chengdu, 610081, Sichuan Province, China.
  • Biao Zhi
    Department of Radiology, Affiliated Hospital of Chengdu University, 82 2Nd N Section of Second Ring Rd, Chengdu, 610081, Sichuan Province, China.
  • Yongqin Wang
    Department of Radiology, Affiliated Hospital of Chengdu University, 82 2Nd N Section of Second Ring Rd, Chengdu, 610081, Sichuan Province, China.
  • Haibo Qu
    Department of Radiology, West China Second Hospital of Sichuan University, Chengdu, Sichuan, China.

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