Design and Validation of Automated Femoral Bone Morphology Measurements in Cerebral Palsy.

Accurate quantification of bone morphology is important for monitoring the progress of bony deformation in patients with cerebral palsy. The purpose of the study was to develop an automatic bone morphology measurement method using one or two radiographs. The study focused on four morphologic measure...

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Publicado en:Journal of Digital Imaging Vol. 27; no. 2; pp. 262 - 270
Autores principales: Park, Noyeol, Lee, Jehee, Sung, Ki, Park, Moon, Koo, Seungbum
Formato: diagnostic images research tables/charts Journal Article
Publicado: Springer Nature Apr2014
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Apr2014
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      pub: Springer Nature
      place: New York, New York
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        atl: Design and Validation of Automated Femoral Bone Morphology Measurements in Cerebral Palsy.
      aug:
        au:
          Park, Noyeol
          Lee, Jehee
          Sung, Ki
          Park, Moon
          Koo, Seungbum
        affil: Department of Computer Science and Engineering, Seoul National University, Seoul Republic of Korea
      sug:
        subj:
          Cerebral Palsy Pathology
          Femur Radiography
          Femur Anatomy and Histology
          Tomography, X-Ray Computed
          Models, Statistical
          Radiographic Image Enhancement
          Radiographic Image Interpretation, Computer-Assisted
          Imaging, Three-Dimensional
          Evaluation Research
          Factor Analysis
          Intraclass Correlation Coefficient
          Confidence Intervals
          Descriptive Statistics
          Child
          Adolescence
          Female
          Male
          Human
          Funding Source
          Child: 6-12 years
          Adolescent: 13-18 years
          Female
          Male
      ab: Accurate quantification of bone morphology is important for monitoring the progress of bony deformation in patients with cerebral palsy. The purpose of the study was to develop an automatic bone morphology measurement method using one or two radiographs. The study focused on four morphologic measurements-neck-shaft angle, femoral anteversion, shaft bowing angle, and neck length. Fifty-four three-dimensional (3D) geometrical femur models were generated from the computed tomography (CT) of cerebral palsy patients. Principal component analysis was performed on the combined data of geometrical femur models and manual measurements of the four morphologic measurements to generate a statistical femur model. The 3D-2D registration of the statistical femur model for radiography computes four morphological measurements of the femur in the radiographs automatically. The prediction performance was tested here by means of leave-one-out cross-validation and was quantified by the intraclass correlation coefficient (ICC) and by measuring the absolute differences between automatic prediction from two radiographs and manual measurements using original CT images. For the neck-shaft angle, femoral anteversion, shaft bowing angle, and neck length, the ICCs were 0.812, 0.960, 0.834, and 0.750, respectively, and the mean absolute differences were 2.52°, 2.85°, 0.92°, and 1.88 mm, respectively. Four important dimensions of the femur could be predicted from two views with very good agreement with manual measurements from CT and hip radiographs. The proposed method can help young patients avoid instances of large radiation exposure from CT, and their femoral deformities can be quantified robustly and effectively from one or two radiograph(s).
      pubtype: Academic Journal
      doctype:
        diagnostic images
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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