Validating Surface Topography for the Measurement of the Thoracic Kyphosis Angle in Patients With Scoliosis: A Prospective Study of Accuracy.

OBJECTIVE: The purpose of this study was to test the validity and determine the accuracy of surface topography in relation to photogrammetry for measuring the thoracic kyphosis angle in patients with scoliosis. METHODS: This was a prospective, cross-sectional study of diagnostic accuracy that followed the guidelines recommended by the Standards for Reporting Diagnostic Accuracy. We consecutively included 51 participants aged 7 to 18 years. Exclusion criteria were surgical treatment of the spine, neurological disease, lower limb discrepancy greater than 1.5 cm, and body mass index above 29 kg/m². Each participant was evaluated using both a surface topography scan and photogrammetry in random order. The measurement obtained through photogrammetry was used as a reference in this study. For statistical purposes, Pearson's correlation test, Bland-Altman graphical analysis, and the receiver operating characteristic curve (P < .05) were performed. RESULTS: The correlation between the measurements was strong and significant (r = 0.76, P < .001) with an average difference of 0.4° in the Bland-Altman analysis. The receiver operating characteristic curve area was excellent for hypokyphosis (93.4%) and good for hyperkyphosis (86.4%), both being significant (P < .005). CONCLUSION: The agreement and strong correlation between the 2 methods indicate the validity of surface topography to measure the thoracic kyphosis angle. The surface topography provides accurate measures for the thoracic kyphosis angle with cutoff points for hypo- (33.3°) and hyperkyphosis (40.8°) for individuals with scoliosis.

Validation of the Measurement of the Angle of Trunk Rotation in Photogrammetry.

OBJECTIVE: The purpose of this study was to validate the photogrammetric measurement of the angle of trunk rotation in relation to the scoliometer instrument. METHODS: Fifty-eight prominences from individuals with ages between 7 and 18 and with suspicion of spinal asymmetry (SA) were evaluated through the scoliometer and photogrammetry. The photographs were analyzed in the Digital Image-based Postural Assessment software. For statistical purposes, we used Pearson's correlation test (r), root mean square error, Bland-Altman graphical analysis, and receiver operating characteristic curve. The level of significance was P ≤ .05. RESULTS: Excellent correlation for the angle of trunk rotation was obtained between the scoliometer and photogrammetry, with a root mean square error of 3°. The Bland-Altman graphical analysis showed equally dispersed data with no participants outside the limits of agreement. The receiver operating characteristic curve evidenced that (1) the cutoff point for the identification of the presence of spinal asymmetry is 4°; (2) mild to moderate SA is between 4° and 7°; (3) moderate to severe SA is above 8°; and (4) sensitivity and specificity were above 83% and 78%, respectively, with an area under the curve ≥ 90%. CONCLUSION: Photogrammetry is validated for measuring the angle of trunk rotation, being an accurate and accessible tool for the evaluation of patients with spinal asymmetries.

Development and Validation of Prediction Equations for Spinal Curve Angles Based on Skin Surface Measurements.

OBJECTIVE: The purpose of this study was to develop, assess the reliability of, and validate prediction equations that estimate the sagittal curves of the spine from the skin surface. METHODS: Forty digital panoramic radiographs were used to develop the prediction equation, and 59 radiographs were used to assess reliability and validate the equations. For evaluation of the thoracic and lumbar curves, anatomical reference points were marked on the vertebral body, spinous process, and skin surface at the C6, C7, T2, T4, T6, T8, T10, T12, L2, L4, and S2 vertebrae. Three third-degree polynomials were obtained, estimated with the least squares method: inner curves from the centroid of the vertebral bodies and from the apex of the spinous processes and external curve from the skin surface. The magnitude of the curves of each region was estimated based on the angle between tangent lines at several vertebral levels. Prediction equations were obtained (simple linear regression) for the vertebral levels that had the best correlation between the inner and surface curves. The validation of the prediction equations was confirmed using Pearson's correlation (r), Student t test, and root mean square error. The reliability of the method was confirmed using the intraclass correlation coefficient, standard error of measurement, and minimal detectable change (α = 0.05). RESULTS: The best correlations were obtained between the T4-T12 (thoracic) and T10-S2 (lumbar) levels (r > 0.85). For the intrarater and interrater reliability, the correlation was higher than 0.965 and higher than 0.896, respectively. There was a significant and strong correlation between estimated and actual values for the thoracic and lumbar curves, which was confirmed by the t-test results and by the root mean square error inferior to 1°. CONCLUSION: Prediction equations can precisely and accurately estimate the angles of the internal sagittal curves of the spine from the skin surface.