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Analysis of sagittal profile of spine using 3D ultrasound imaging: a phantom study and preliminary subject test.

Authors :
Lee, Timothy Tin-Yan
Cheung, James Chung-Wai
Law, Siu-Yu
To, Michael Kai Tsun
Cheung, Jason Pui Yin
Zheng, Yong-Ping
Source :
Computer Methods in Biomechanics & Biomedical Engineering: Imaging & Visualisation; May2020, Vol. 8 Issue 3, p232-244, 13p
Publication Year :
2020

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
21681163
Volume :
8
Issue :
3
Database :
Complementary Index
Journal :
Computer Methods in Biomechanics & Biomedical Engineering: Imaging & Visualisation
Publication Type :
Academic Journal
Accession number :
143139114
Full Text :
https://doi.org/10.1080/21681163.2019.1566025