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Springer, Pediatric Radiology, 2(51), p. 282-288, 2020

DOI: 10.1007/s00247-020-04827-6

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Chronic nonbacterial osteomyelitis — clinical and magnetic resonance imaging features

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Abstract

Abstract Background Chronic nonbacterial osteomyelitis (CNO) is a rare autoinflammatory bone disorder. Little information exists on the use of imaging techniques in CNO. Materials and methods We retrospectively reviewed clinical and MRI findings in children diagnosed with CNO between 2012 and 2018. Criteria for CNO included unifocal or multifocal inflammatory bone lesions, symptom duration >6 weeks and exclusion of infections and malignancy. All children had an MRI (1.5 tesla) performed at the time of diagnosis; 68 of these examinations were whole-body MRIs including coronal short tau inversion recovery sequences, with additional sequences in equivocal cases. Results We included 75 children (26 boys, or 34.7%), with mean age 10.5 years (range 0–17 years) at diagnosis. Median time from disease onset to diagnosis was 4 months (range 1.5–72.0 months). Fifty-nine of the 75 (78.7%) children presented with pain, with or without swelling or fever, and 17 (22.7%) presented with back pain alone. Inflammatory markers were raised in 46/75 (61.3%) children. Fifty-four of 75 (72%) had a bone biopsy. Whole-body MRI revealed a median number of 6 involved sites (range 1–27). Five children (6.7%) had unifocal disease. The most commonly affected bones were femur in 46 (61.3%) children, tibia in 48 (64.0%), pelvis in 29 (38.7%) and spine in 20 (26.7%). Except for involvement of the fibula and spine, no statistically significant differences were seen according to gender. Conclusion Nearly one-fourth of the children presented with isolated back pain, particularly girls. The most common sites of disease were the femur, tibia and pelvic bones. Increased inflammatory markers seem to predict the number of MRI sites involved.