Department of Biomedical Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR, China.
SH Ho Scoliosis Research Lab, Joint Scoliosis Research Center of the Chinese University of Hong Kong and Nanjing University, Department of Orthopaedics and Traumatology, The Chinese University of Hong Kong, Shatin, Hong Kong.
Int J Comput Assist Radiol Surg. 2022 Dec;17(12):2239-2251. doi: 10.1007/s11548-022-02740-x. Epub 2022 Sep 9.
Bending Asymmetry Index (BAI) has been proposed to characterize the types of scoliotic curve in three-dimensional ultrasound imaging. Scolioscan has demonstrated its validity and reliability in scoliosis assessment with manual assessment-based X-ray imaging. The objective of this study is to investigate the ultrasound-derived BAI method to X-ray imaging of scoliosis, with supplementary information provided for the pre-surgery planning.
About 30 pre-surgery scoliosis subjects (9 males and 21 females; Cobb: 50.9 ± 19.7°, range 18°-115°) were investigated retrospectively. Each subject underwent three-posture X-ray scanning supine on a plain mattress on the same day. BAI is an indicator to distinguish structural or non-structural curves through the spine flexibility information obtained from lateral bending spinal profiles. BAI was calculated semi-automatically with manual annotation of vertebral centroids and pelvis level inclination adjustment. BAI classification was validated with the scoliotic curve type and traditional Lenke classification using side-bending Cobb angle measurement (S-Cobb).
82 curves from 30 pre-surgery scoliosis patients were included. The correlation coefficient was R = 0.730 (p < 0.05) between BAI and S-Cobb. In terms of scoliotic curve type classification, all curves were correctly classified; out of 30 subjects, 1 case was confirmed as misclassified when applying to Lenke classification earlier, thus has been adjusted.
BAI method has demonstrated its inter-modality versatility in X-ray imaging application. The curve type classification and the pre-surgery Lenke classification both indicated promising performances upon the exploratory dataset. A fully-automated of BAI measurement is surely an interesting direction to continue our endeavor. Deep learning on the vertebral-level segmentation should be involved in further study.
弯曲不对称指数（BAI）已被提出用于在三维超声成像中描述脊柱侧弯的类型。Scolioscan 已在基于手动评估的 X 射线成像的脊柱侧弯评估中证明了其有效性和可靠性。本研究的目的是研究超声衍生的 BAI 方法与 X 射线成像的脊柱侧弯，为术前计划提供补充信息。
回顾性调查了约 30 例术前脊柱侧弯患者（男性 9 例，女性 21 例；Cobb 角：50.9±19.7°，范围 18°-115°）。每位患者在同一天仰卧于普通床垫上进行三种体位 X 射线扫描。BAI 是一种通过从侧屈脊柱轮廓获得的脊柱灵活性信息来区分结构性或非结构性曲线的指标。BAI 通过手动注释椎骨中心点和骨盆水平倾斜度调整半自动计算。使用侧屈 Cobb 角测量（S-Cobb），通过 BAI 分类与脊柱侧弯曲线类型和传统 Lenke 分类进行验证。
30 例术前脊柱侧弯患者的 82 条曲线被纳入研究。BAI 和 S-Cobb 之间的相关系数为 R=0.730（p<0.05）。在脊柱侧弯曲线类型分类方面，所有曲线均被正确分类；在 30 例患者中，1 例在应用 Lenke 分类时被确认为分类错误，因此进行了调整。
BAI 方法已证明其在 X 射线成像应用中的跨模态通用性。曲线类型分类和术前 Lenke 分类都在探索性数据集上表现出了有前景的性能。BAI 测量的完全自动化无疑是一个有趣的研究方向。在进一步的研究中应涉及基于椎体级别的分割的深度学习。
