ArticleChild's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery2021
Physiological defects of lumbosacral vertebral arches on computed tomography images in children.
Article in Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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- Surgery for spina bifida occulta: spinal lipoma and tethered spinal cord.Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery · 2023Review
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Abstract
objectivePhysiological midline defects of the lumbosacral vertebral arches on radiographs must be distinguished from pathological spina bifida. To date, however, this has not been examined, except for some reports based on plain radiography. The aim of this study is to accurately define the rate and distribution of physiological defects by computed tomography (CT) imaging.
methodsA total of 115 patients aged 0 months to 16 years (median age, 4 years) who underwent CT scans for abdominopelvic disorder not involving the lumbosacral spine were retrospectively analyzed. The lumbosacral spines were collaterally identified on these images.
resultsIn the lumbosacral spine excluding the sacral hiatus, the rate of physiological defects was 66.1% (95% confidence interval [CI]: 56.7-74.7%), and the mean number of defective vertebral arches was 1.6 per patient (95% CI: 1.3-1.9). The rate and mean number of defects were significantly higher in the group of patients less than 6 years old (84.3%, 2.2/patient) than that of patients 6 years old or older (37.8%, 0.5/patient) (p < 0.001 and p < 0.001, respectively). The defect rates by spinal level were S3 (57.4%), S1 (47.8%), S2 (34.8%), L5 (13.0%), L4 (2.6%), and L3 (0.9%) in descending order.
conclusionsPhysiological defects were found more commonly at an earlier age and predominantly existed adjacent to the sacral hiatus (S3) and around S1. Understanding the detection rate and distribution features of defects more precisely on CT images will contribute clinically supportive information to distinguish between physiological defects and pathological spina bifida.
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