Abstract
Introduction and objectiveAlthough being standard for scoliosis curve size estimation, COBB angle measurement is well known to be inaccurate, due to a high interobserver variance in end vertebra selection and end plate contour delineation. We propose a stepwise improvement by using a spline constructed from vertebra centroids to resemble spinal curve characteristics more closely. To enhance precision even further, a neural net was trained to detect the centroids automatically.Materials & MethodsVertebra centroids in AP spinal X-ray images of varying quality from 551 scoliosis patients were manually labeled by 4 investigators. With these inputs, splines were generated and the computed curve sizes were compared to the manually measured COBB angles and to the curve estimation obtained from the neural net.ResultsSplines achieved a higher interobserver correlation of 0.92–0.95 compared to manual COBB measurements (0.83–0.92) and showed 1.5–2 times less variance, depending on the anatomic region. This translates into an average of 1° of interobserver measurement deviation for spline-based curve estimation compared to 3°–8° for COBB measurements. The neural net was even more precise and achieved mean deviations below 0.5°.ConclusionIn conclusion, our data suggest an advantage of spline-based automated measuring systems, so further investigations are warranted to abandon manual COBB measurements.
Highlights
Introduction and objective being standard for scoliosis curve size estimation, COBB angle measurement is well known to be inaccurate, due to a high interobserver variance in end vertebra selection and end plate contour delineation
The method itself is flawed by high inter- and intraobserver errors, ranging from 3° to 10°, which can mainly be attributed to the manual nature of end vertebra selection and delineation [1]
We investigated more closely if fuzzy end vertebra determination has an impact on measurement variance for spline and neural network (NN) approaches that estimate the global curve characteristics
Summary
Introduction and objective being standard for scoliosis curve size estimation, COBB angle measurement is well known to be inaccurate, due to a high interobserver variance in end vertebra selection and end plate contour delineation. Materials & Methods Vertebra centroids in AP spinal X-ray images of varying quality from 551 scoliosis patients were manually labeled by 4 investigators. With these inputs, splines were generated and the computed curve sizes were compared to the manually measured COBB angles and to the curve estimation obtained from the neural net. The method itself is flawed by high inter- and intraobserver errors, ranging from 3° to 10° (95% CI), which can mainly be attributed to the manual nature of end vertebra selection and delineation [1] In addition to this inaccuracy, the COBB method neglects important parts of the curve characteristics, e.g., apical vertebra translation. It has been shown that the error originating from imaging modality ranges from none to below 2° [2, 3]
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