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Image processing assessment of femoral osteopenia

  • Plenary Sessions
  • Session 10 Image Processing
  • Published:
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Abstract

Visual assessment of femoral osteopenia (the radiographic presentation of osteoporosis) is unreliable. Many of the short-comings of observer grading can be overcome by digital image analysis. Our group has developed algorithms to make automatic assessment of osteopenia from clinical radiographs. Texture Analysis Models (TA) commonly used in image analysis were investigated as measures of osteopenia. Unlike densitometric methods, TA characterizes properties of thestructure of the image (ie, trabecular patterns). A group of women were analyzed whose subjects ranged from those at risk of osteoporosis (n=24) to normal (n=40). Using an IBM PC, frame-grabber, camera, and light-box, we appraised five statistical TA algorithms for assessment of the femoral neck in standard pelvic radiographs: (1)Fractal Signature (FS) describes the image’s fractal nature. (2)Auto-Correlation of unaltered and Sobel Edge Transformed images (ACSE) measures image spatial self-similarity. (3)Co-occurrence Matrices (CM) gives the joint probability of greylevels with distance/direction and describes statistical relationships of image variation. (4)Textural Spectrum (TS) neighborhood pixel relationships measure regional directional and pixel-inversion properties. (5)Eular Numbers (EN) describe texture by properties (such as connectivity) of binary images. Good reproducibility from repeated analysis of radiographs was shown using both pairedt-tests and Altman-Bland’s methods. We have shown a correlation between femoral neck bone mineral density (BMD—the “gold standard” of osteoporosis assessment) and textural measures for all five algorithms. Significant measures of osteopenia were: ACSE (r=0.6,P < .001), CM (r=−0.69,P < .001), FS (r=0.35,P < .01), TS (r=0.52,P < .001) and EN (r=−0.39,P < .01). Relationships were also found between textural characteristics and age/weight. TA techniques characterize the radiographic changes of bone in osteoporosis. Technology based on these ideas may have a place alongside BMD measurements in the assessment of this condition.

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Authors and Affiliations

  1. SmithKline Beecham Pharmaceuticals, Essex, UK

    M. F. James

  2. Centre for Health Informatics & Multiprofessional Education, UCL Medical School, Whittington Hospital, 4th Floor, Archway Wing, N19 5NE, London, UK

    R. L. Lee & J. E. Dacre

Authors
  1. R. L. Lee
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  2. J. E. Dacre
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  3. M. F. James
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Supported by SmithKline Beecham Pharmaceuticals, New Frontiers Science Park, Harlow, Essex, UK, PhD Studentship.

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Lee, R.L., Dacre, J.E. & James, M.F. Image processing assessment of femoral osteopenia. J Digit Imaging 10 (Suppl 1), 218–221 (1997). https://doi.org/10.1007/BF03168705

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  • DOI: https://doi.org/10.1007/BF03168705

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