Computer-Aided Assessment of Spinal Inflammation on Magnetic Resonance Images in XXXX With @entity1691 .

@entity1 @entity66 @entity4 @entity1691 @entity1499
OBJECTIVE: To evaluate a computer-aided approach to the assessment of spinal inflammation on magnetic resonance imaging (MRI) in @entity1691 as compared to visual assessment. METHODS: Following institutional ethics approval, 32 @entity1 (mean        SD age 35.3        10.2 years) with active @entity1691 underwent treatment with @entity1499 and infliximab for 30 weeks. Spinal MRI examination (T1-weighted, T2-weighted fat-suppressed, and postcontrast T1-weighted fat-suppressed sagittal sequences using a 1.5T MRI system) was performed at baseline and at 30 weeks. Following manual identification of the vertebral corners, vertebral body segmentation was performed using a deformable model that automatically isolated the 4 vertebral corner areas, allowing automatic measurement of the relative mean corner intensity of each vertebral corner before and after treatment. Quantitative computer-aided assessment of spinal inflammation was compared with a semiquantitative visual assessment of spinal inflammation (the Berlin method). RESULTS: Computer-aided quantification was quick and highly reliable, and it identified increases in vertebral corner @entity4 or enhancement that were significantly decreased following treatment (P   <   0.5). For computer-aided analysis, there was excellent inter- and intrarater correlation of both corner @entity4 and enhancement (intraclass correlation coefficients [ICCs] >0.99), and the correlations were better than those for visual analysis (ICCs 0.83-0.96). For computer-aided analysis, the standardized response mean was 1.67 for corner @entity4 and 1.64 for enhancement, as compared to 1.20 and 1.18, respectively, for visual analysis. Computer-aided quantification of MRI data correlated better (r   =   0.50-0.53, P   <   0.01) with clinical features of @entity66 activity pre- and posttreatment than did visual analysis of spinal inflammation (r   =   0.37-0.43, P   >   0.02). CONCLUSION: Computer-aided assessment of spinal inflammation in @entity1691 is quick, reliable, and sensitive and correlates better with clinical disease activity than does visual assessment by the Berlin method.
