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. 2021 Mar 30;11(1):7144.
doi: 10.1038/s41598-021-86436-3.

Computerized image understanding system for reliable estimation of spinal curvature in idiopathic scoliosis

Ananthakrishna Thalengala #  1 , Shyamasunder N Bhat #  2 , H Anitha #  1
Affiliations

Computerized image understanding system for reliable estimation of spinal curvature in idiopathic scoliosis

Ananthakrishna Thalengala et al. Sci Rep. .

Abstract

Analysis of scoliosis requires thorough radiographic evaluation by spinal curvature estimation to completely assess the spinal deformity. Spinal curvature estimation gives orthopaedic surgeons an idea of severity of spinal deformity for therapeutic purposes. Manual intervention has always been an issue to ensure accuracy and repeatability. Computer assisted systems are semi-automatic and is still influenced by surgeon's expertise. Spinal curvature estimation completely relies on accurate identification of required end vertebrae like superior end-vertebra, inferior end-vertebra and apical vertebra. In the present work, automatic extraction of spinal information central sacral line and medial axis by computerized image understanding system has been proposed. The inter-observer variability in the anatomical landmark identification is quantified using Kappa statistic. The resultant Kappa value computed between proposed algorithm and observer lies in the range 0.7 and 0.9, which shows good accuracy. Identification of the required end vertebra is automated by the extracted spinal information. Difference in inter and intra-observer variability for the state of the art computer assisted and proposed system are quantified in terms of mean absolute difference for the various types (Type-I, Type-II, Type-III, Type-IV, and Type-V) of scoliosis.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Scoliosis views: (a) normal versus scoliotic spine. (b) Definition of required anatomical landmarks. (c) Definition: medial axis (MA), central sacral line (CSL).
Figure 2
Figure 2
Spinal curvature evaluation (a) Ferguson, (b) Cobb, (c) Greenspan Index and (d) Diab method.
Figure 3
Figure 3
Spinal curvature evaluation.
Figure 4
Figure 4
Images of Type-I, Type-III, Type-IV and Type-V for (a) input radiograph, (b) segmented vertebral column, (c) extracted boundary and (d) automated definition of MA and CSL.
Figure 5
Figure 5
Type I (a) mean absolute difference (MAD) in inter observer variation.
Figure 6
Figure 6
Type II (a) mean absolute difference (MAD) in inter observer variation.
Figure 7
Figure 7
Type III (a) mean absolute difference (MAD) in inter observer variation.
Figure 8
Figure 8
Type IV (a) mean absolute difference (MAD) in inter observer variation.
Figure 9
Figure 9
Type V (a) mean absolute difference (MAD) in inter observer variation.
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