Fully automatic measurements of axial vertebral rotation for assessment of spinal deformity in idiopathic scoliosis

Reliable measurements of spinal deformities in idiopathic scoliosis are vital, since they are used for assessing the degree of scoliosis, deciding upon treatment and monitoring the progression of the disease. However, commonly used two dimensional methods (e.g. the Cobb angle) do not fully capture t...

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Bibliographic Details
Published in:Physics in medicine & biology 2013-03, Vol.58 (6), p.1775-1787
Main Authors: Forsberg, Daniel, Lundström, Claes, Andersson, Mats, Vavruch, Ludvig, Tropp, Hans, Knutsson, Hans
Format: Article
Language:English
Subjects:
Adolescent
Automation
Humans
Imaging, Three-Dimensional
Lumbar Vertebrae - diagnostic imaging
Lumbar Vertebrae - pathology
Observer Variation
Rotation
Scoliosis - diagnostic imaging
Scoliosis - pathology
Tomography, X-Ray Computed - methods
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Summary:Reliable measurements of spinal deformities in idiopathic scoliosis are vital, since they are used for assessing the degree of scoliosis, deciding upon treatment and monitoring the progression of the disease. However, commonly used two dimensional methods (e.g. the Cobb angle) do not fully capture the three dimensional deformity at hand in scoliosis, of which axial vertebral rotation (AVR) is considered to be of great importance. There are manual methods for measuring the AVR, but they are often time-consuming and related with a high intra- and inter-observer variability. In this paper, we present a fully automatic method for estimating the AVR in images from computed tomography. The proposed method is evaluated on four scoliotic patients with 17 vertebrae each and compared with manual measurements performed by three observers using the standard method by Aaro-Dahlborn. The comparison shows that the difference in measured AVR between automatic and manual measurements are on the same level as the inter-observer difference. This is further supported by a high intraclass correlation coefficient (0.971-0.979), obtained when comparing the automatic measurements with the manual measurements of each observer. Hence, the provided results and the computational performance, only requiring approximately 10 to 15 s for processing an entire volume, demonstrate the potential clinical value of the proposed method.
ISSN:0031-9155
1361-6560
1361-6560
DOI:10.1088/0031-9155/58/6/1775