Multi-functionality of computer-aided quantitative vertebral fracture morphometry analyses

Quantitative Imaging in Medicine and Surgery

Fernando Rivadeneira³  Frank J. A. van Rooij⁶  Albert Hofman²  M. Carola Zillikens⁷  Salih El Saddy¹  Edwin H. G. Oei⁴  André G. Uitterlinden³  Felisia Ly⁵  Ater A. Makurthou¹  Ling Oei³ 

[1]Department of Internal Medicine, Erasmus MC, Rotterdam, the Netherlands

[2]Department of Epidemiology, Erasmus MC, Rotterdam, the Netherlands

[3]Department of Radiology, Erasmus MCDepartment of Epidemiology, Erasmus MC, Rotterdam, the Netherlands

[4]Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging (NCHA), the Netherlands

[5]Department of Internal Medicine, Erasmus MC, Rotterdam, the Netherlands

[6]Department of Epidemiology, Erasmus MC, Rotterdam, the Netherlands

[7]Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging (NCHA), the Netherlands

[8]

[9]Department of Radiology, Erasmus MC, Rotterdam, the NetherlandsDepartment of Internal Medicine, Erasmus MC, Rotterdam, the Netherlands

[10]Department of Epidemiology, Erasmus MC, Rotterdam, the Netherlands

[11]Department of Epidemiology, Erasmus MC, Rotterdam, the Netherlands

[12]Department of Internal Medicine, Erasmus MC, Rotterdam, the Netherlands

[13]Netherlands Genomics Initiative (NGI)-sponsored Netherlands Consortium for Healthy Aging (NCHA), the Netherlands

关键词: Vertebral fracture;    quantitative;    morphometry;    osteoporosis;    degenerative disease;    spine;    software;    post-processing;   

DOI  :  10.3978/j.issn.2223-4292.2013.09.03

学科分类：外科医学

来源: AME Publications

【 摘 要 】

Osteoporotic vertebral fractures are an increasingly active area of research. Oftentimes assessments are performed by software-assisted quantitative morphometry. Here, we will discuss multi-functionality of these data for research purposes. A team of trained research assistants processed lateral spine radiographs from the population-based Rotterdam Study with SpineAnalyzer^® software (Optasia Medical Ltd, Cheadle, UK). Next, the raw coordinate data of the two upper corners of Th5 and the two lower corners of Th12 were extracted to calculate the Cobb’s kyphosis angle. In addition, two readers performed independent manual measurements of the Cobb’s kyphosis angle between Th5 and Th12 for a sample (n=99). The mean kyphosis angle and its standard deviation were 53° and 10° for the SpineAnalyzer^® software measurements and 54° and 12° by manual measurements, respectively. The Pearson’s correlation coefficient was 0.65 [95% confidence interval (CI): 0.53-0.75; P=2×10^�?13]. There was a substantial intraclass correlation with a coefficient of 0.64 (95% CI: 0.51-0.74). The mean difference between methods was 1° (95% CI: �?2°-4°), with 95% limits of agreement of �?20°-17° and there were no systematic biases. In conclusion, vertebral fracture morphometry data can be used to derive the Cobb’s kyphosis angle. Even more quantitative measures could be derived from the raw data, such as vertebral wedging, intervertebral disc space, spondylolisthesis and the lordosis angle. These measures may be of interest for research into musculoskeletal disorders such as osteoporosis, degenerative disease or Scheuermann’s disease. Large-scale studies may benefit from efficient capture of multiple quantitative measures in the spine.

【 授权许可】

Unknown