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Measurement of acetabular inclination and anteversion via CT generated 3D pelvic model

Overview of attention for article published in BMC Musculoskeletal Disorders, August 2017
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Title
Measurement of acetabular inclination and anteversion via CT generated 3D pelvic model
Published in
BMC Musculoskeletal Disorders, August 2017
DOI 10.1186/s12891-017-1714-y
Pubmed ID
Authors

R. Y. Wang, W. H. Xu, X. C. Kong, L. Yang, S. H. Yang

Abstract

Inclination and anteversion were the main factors that determined the reliability of the acetabulum. Inclination and anteversion measurements included anatomical, operational and radiographic methods. The aim of our present study was to exhibit divergence of inclination and anteversion via the three measurements. Inclination and anteversion were defined according to the definitions put forward by Murray. Three-dimensional models of pelvis of CT data were brought forth. Acetabular axis was determined by the rim of acetabula. Reference planes were established by bone landmarks including anterior superior iliac spine, pubic tubercles and sacral crests. Inclinations and anteversions were calculated according to the definitions. Forty-nine cases were involved in the research. Data of inclination form anatomical, operational and radiographic showed 37.48 ± 11.07, 45.12 ± 14.76 and 48.76 ± 14.36, and anteversion were 18.12 ± 7.59, 24.97 ± 9.68, 14.30 ± 5.64. A substantial deviation was noted in the inclinations (P < 0.01) and anteversions (P < 0.01). Our findings suggested that the inclinations and anteversions of the three measurements varied, which might in turn interfere the decision of orthopedists.

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Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 37 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 6 16%
Student > Ph. D. Student 4 11%
Student > Master 4 11%
Researcher 3 8%
Other 2 5%
Other 5 14%
Unknown 13 35%
Readers by discipline Count As %
Medicine and Dentistry 15 41%
Engineering 5 14%
Nursing and Health Professions 1 3%
Computer Science 1 3%
Veterinary Science and Veterinary Medicine 1 3%
Other 0 0%
Unknown 14 38%