title: Image processing assessment of femoral osteopenia.
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 the structure 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 paired t-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.
authors.affiliation: CHIME, UCL Medical School, Whittington Hospital, London, UK.
authors.forename: R L
authors.initials: RL
authors.lastname: Lee
authors.forename: J E
authors.initials: JE
authors.lastname: Dacre
authors.forename: M F
authors.initials: MF
authors.lastname: James
mesh_terms: D015502:Absorptiometry, Photon; D000465:Algorithms; D015519:Bone Density; D016022:Case-Control Studies; D005260:Female; D005272:Femur Neck / Q000000981:diagnostic imaging*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008875:Middle Aged; D015663:Osteoporosis, Postmenopausal / Q000000981:diagnostic imaging* / Q000453:epidemiology; D012307:Risk Factors