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Spine (Phila Pa 1976). 2005 Dec 15;30(24):2824-9.

Prediction of thoracic dimensions and spine length based on individual pelvic dimensions in children and adolescents: an age-independent, individualized standard for evaluation of outcome in early onset spinal deformity.

Author information

1
Department of Orthopaedic Surgery, Children's Hospital and Harvard Medical School, Boston, MA 02115, USA. john.emans@childrens.harvard.edu

Abstract

STUDY DESIGN:

A retrospective review of spine, chest, and pelvic dimensions of normal CT scans from 1999 to 2004 was performed.

OBJECTIVE:

To determine age-independent predictors of spine and chest dimensions.

SUMMARY OF BACKGROUND DATA:

Progressive thoracic deformity is associated with early-onset spinal deformities. Patients with severe early-onset scoliosis are commonly smaller and slower to grow than normal. Newer treatment approaches emphasize spine length and chest growth. Assessing treatment outcomes is hampered by the lack of normal values appropriate for diseased children. This study establishes normal range standards of chest and spine dimensions to aid in assessment of treatment outcomes.

METHODS:

A total of 198 CT scans of previously healthy patients 0 to 21 years of age were measured. Measurements taken from CT scans include maximum inner chest width, anteroposterior chest depth, thoracic spine height, lumbar spine height, total spine height, and pelvic inlet width. Linear regression was applied to establish gender-specific reference ranges for spine and chest dimensions based on pelvic width.

RESULTS:

Chest and spine dimensions were significantly correlated with pelvic inlet width and gender (P < 0.001). Multiple linear regression indicated that pelvic inlet width provided excellent fit in establishing gender-specific normal ranges independent of age.

CONCLUSION:

Pelvic inlet width is an age-independent predictor of pediatric chest width and thoracic dimensions that may be used to assess thoracic and spine growth in early onset spine deformity patients.

PMID:
16371912
[Indexed for MEDLINE]

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