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Value of multidetector computed tomography for the radiologic grading of sacroiliitis in ankylosing spondylitis.
- Value of multidetector computed tomography for the radiologic grading of sacroiliitis in ankylosing spondylitis.
- Lee Y.H.; Hong Y.S.; Park W.; Kwon S.R.; Choi H.J.; Hong S.J.; Lee C.H.; Suh C.H.; Park S.W.; Hwang J.Y.; Lee J.
- Ewha Authors
- 이지수; 황지영
- SCOPUS Author ID
- 이지수; 황지영
- Issue Date
- Journal Title
- Rheumatology international
- vol. 33, no. 4, pp. 1005 - 1011
- SCI; SCIE; SCOPUS
- The objective of this study is to investigate the value of multidetector computed tomography (MDCT) in the assessment of sacroiliitis in patients with established ankylosing spondylitis (AS). Paired plain radiographs and MDCT images of the 330 sacroiliac (SI) joints in 165 patients with definite or probable ankylosing spondylitis were analyzed for sacroiliitis. Sacroiliitis on plain radiographs were graded on a scale of 0-4 according to the modified New York (NY) criteria. For grading of sacroiliitis by MDCT, modified NY criteria were revised for MDCT application introducing the concept of quantification. The relationship between sacroiliitis grades by plain radiography and MDCT was analyzed by two radiologists, blinded for all clinical data. Of the 330 SI joints assessed, there was agreement between the sacroiliitis grading by plain radiography and MDCT in 73 (22.1 %) SI joints. Sacroiliitis grade by MDCT was higher in 250 (75.8 %) SI joints and lower in 7 (2.1 %) SI joints than that by plain radiography. Using the MDCT, 83.6 % of patients met the modified NY radiologic criteria for the classification of AS, compared with 58.2 % of the patients by plain radiography. Twenty-six percent of the patients, who did not meet the modified NY criteria for the classification of AS by plain radiography, met the criteria by MDCT. Disease durations in patients with grade 2 and grade 3 sacroiliitis were significantly shorter in patients evaluated by MDCT compared with plain radiography. MDCT is a useful imaging method that can be applied to the initial diagnosis of the AS, and by better visualization of SI joint changes, it can be used to predict the progress of the disease.
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