Evaluation of a computer-aided method for measuring the Cobb angle on chest X-rays.

Objectives: To automatically measure the Cobb angle and diagnose scoliosis on chest X-rays, a computer-aided method was proposed and the reliability and accuracy were evaluated.Methods: Two Mask R-CNN models as the core of a computer-aided method were used to separately detect and segment the spine...

Descripción completa

Detalles Bibliográficos
Publicado en:European Spine Journal Vol. 28; no. 12; pp. 3035 - 3044
Autores principales: Pan, Yaling, Chen, Qiaoran, Chen, Tongtong, Wang, Hanqi, Zhu, Xiaolei, Fang, Zhihui, Lu, Yong
Formato: research Journal Article
Publicado: Springer Nature Dec2019
Acceso en línea:Ver este registro en EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=139827186&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 139827186
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        09406719
        NPI
      jtl: European Spine Journal
      issn: 09406719
      maglogo: N
    pubinfo:
      dt: Dec2019
      vid: 28
      iid: 12
      pid: 237
      pub: Springer Nature
      place: New York, New York
    artinfo:
      ui:
        139827186
        139827186
        NLM31446493
        139827186
        10.1007/s00586-019-06115-w
        NLM31446493
        139827186
      ppf: 3035
      ppct: 9
      formats:
      tig:
        atl: Evaluation of a computer-aided method for measuring the Cobb angle on chest X-rays.
      aug:
        au:
          Pan, Yaling
          Chen, Qiaoran
          Chen, Tongtong
          Wang, Hanqi
          Zhu, Xiaolei
          Fang, Zhihui
          Lu, Yong
        affil: Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, 200025, Shanghai, China
      sug:
        subj:
          Radiographic Image Interpretation, Computer-Assisted Methods
          Radiography, Thoracic Methods
          Scoliosis
          Spine Pathology
          Spine
          Scoliosis Pathology
          Reproducibility of Results
          Human
          Validation Studies
          Comparative Studies
          Evaluation Research
          Multicenter Studies
      ab: Objectives: To automatically measure the Cobb angle and diagnose scoliosis on chest X-rays, a computer-aided method was proposed and the reliability and accuracy were evaluated.Methods: Two Mask R-CNN models as the core of a computer-aided method were used to separately detect and segment the spine and all vertebral bodies on chest X-rays, and the Cobb angle of the spinal curve was measured from the output of the Mask R-CNN models. To evaluate the reliability and accuracy of the computer-aided method, the Cobb angles on 248 chest X-rays from lung cancer screening were measured automatically using a computer-aided method, and two experienced radiologists used a manual method to separately measure Cobb angles on the aforementioned chest X-rays.Results: For manual measurement of the Cobb angle on chest X-rays, the intraclass correlation coefficients (ICC) of intra- and inter-observer reliability analysis was 0.941 and 0.887, respectively, and the mean absolute differences were < 3.5°. The ICC between the computer-aided and manual methods for Cobb angle measurement was 0.854, and the mean absolute difference was 3.32°. These results indicated that the computer-aided method had good reliability for Cobb angle measurement on chest X-rays. Using the mean value of Cobb angles in manual measurements > 10° as a reference standard for scoliosis, the computer-aided method achieved a high level of sensitivity (89.59%) and a relatively low level of specificity (70.37%) for diagnosing scoliosis on chest X-rays.Conclusion: The computer-aided method has potential for automatic Cobb angle measurement and scoliosis diagnosis on chest X-rays. These slides can be retrieved under Electronic Supplementary Material.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N