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

Cited 8 time in Web of Science Cited 10 time in Scopus

Park, Noyeol; Lee, Jehee; Sung, Ki Hyuk; Park, Moon Seok; Koo, Seungbum

Issue Date
Springer Verlag
Journal of Digital Imaging, Vol.27 No.2, pp.262-269
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 2.52A degrees, 2.85A degrees, 0.92A degrees, 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).
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  • College of Medicine
  • Department of Medicine
Research Area Cerebral palsy, Medical image, Motion analysis, Pediatric orthopedic surgery, Statistics in orthopedic research


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