Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/92925
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Title: Analysis of sagittal profile of spine using 3D ultrasound imaging : a phantom study and preliminary subject test
Authors: Lee, TTY 
Cheung, JCW 
Law, SY 
To, MKT
Cheung, JPY
Zheng, YP 
Issue Date: 2020
Source: Computer methods in biomechanics and biomedical engineering: imaging & visualization, 2020, v. 8, no. 3, p. 232-244
Abstract: Radiographic Cobb’s angle is the gold standard for evaluation of spinal curvature, however, X-ray is ionising. In contrast, ultrasound is non-ionising and inexpensive. However, no study has reported the reliability and accuracy of ultrasound on sagittal curvature analysis. Ultrasound and X-ray scanning were conducted on 16 sets of spine phantoms with different deformities. Intra-rater and inter-rater reliability, correlations, mean absolute differences (MAD) and linear regression of ultrasound spinous process angles (USSPA), X-ray spinous process angles (XSPA) and X-ray Cobb’s angles (XCA) together with the intra-operator reliability of USSPA were investigated. In addition, USSPA and XCA of five AIS subjects were obtained using the ultrasound system. In the phantom study, excellent intra-rater and inter-rater reproducibility for the three angles and excellent intra-operator reproducibility for USSPA were demonstrated. Good to moderate or better correlations were obtained among the angles. All three angles indicated positive linear relationships with MAD ≤ 6.0°. The results of the preliminary study demonstrated a high intra-reliability for the ultrasound measurements. The measured difference between the USSPA and XCA methods was 6.3° ± 5.4°. The results showed that ultrasound is feasible for measuring sagittal curvature and has the potential for monitoring the curve progression and evaluating sagittal spinal profiles.
Keywords: 3D ultrasound imaging
Cobb’s angle
Sagittal balance
Spine
Spinous process
Publisher: Taylor & Francis
Journal: Computer methods in biomechanics and biomedical engineering: imaging & visualization 
ISSN: 2168-1163
EISSN: 2168-1171
DOI: 10.1080/21681163.2019.1566025
Rights: © 2019 Informa UK Limited, trading as Taylor & Francis Group
This is an Accepted Manuscript of an article published by Taylor & Francis in Computer methods in biomechanics and biomedical engineering: imaging & visualization on 30 Apr 2019 (published online), available at: http://www.tandfonline.com/10.1080/21681163.2019.1566025
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