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基于X线片的人体椎体骨赘形成与生长过程的定量分析及随机建模:一项随访研究

Quantitative analysis and stochastic modeling of osteophyte formation and growth process on human vertebrae based on radiographs: a follow-up study.

作者信息

Wu Tong, Wang Changxi, Li Kang

机构信息

West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, 610041, China.

Sichuan University - Pittsburgh Institute, Sichuan University, Chengdu, 610207, China.

出版信息

Sci Rep. 2024 Apr 24;14(1):9393. doi: 10.1038/s41598-024-60212-5.

Abstract

Osteophytes are frequently observed in elderly people and most commonly appear at the anterior edge of the cervical and lumbar vertebrae body. The anterior osteophytes keep developing and will lead to neck/back pain over time. In clinical practice, the accurate measurement of the anterior osteophyte length and the understanding of the temporal progression of anterior osteophyte growth are of vital importance to clinicians for effective treatment planning. This study proposes a new measuring method using the osteophyte ratio index to quantify anterior osteophyte length based on lateral radiographs. Moreover, we develop a continuous stochastic degradation model with time-related functions to characterize the anterior osteophyte formation and growth process on cervical and lumbar vertebrae over time. Follow-up data of anterior osteophytes up to 9 years are obtained for measurement and model validation. The agreement test indicates excellent reproducibility for our measuring method. The proposed model accurately fits the osteophyte growth paths. The model predicts the mean time to onset of pain and obtained survival function of the degenerative vertebrae. This research opens the door to future quantification and mathematical modeling of the anterior osteophyte growth on human cervical and lumbar vertebrae. The measured follow-up data is shared for future studies.

摘要

骨赘在老年人中很常见,最常出现在颈椎和腰椎椎体的前缘。椎体前缘骨赘不断发展,随着时间的推移会导致颈部/背部疼痛。在临床实践中,准确测量椎体前缘骨赘的长度以及了解其生长的时间进程,对于临床医生制定有效的治疗方案至关重要。本研究提出了一种基于侧位X线片,利用骨赘比率指数来量化椎体前缘骨赘长度的新测量方法。此外,我们开发了一个具有时间相关函数的连续随机退化模型,以描述颈椎和腰椎椎体前缘骨赘的形成和生长过程。获取了长达9年的椎体前缘骨赘随访数据用于测量和模型验证。一致性检验表明我们的测量方法具有出色的可重复性。所提出的模型准确地拟合了骨赘的生长路径。该模型预测了疼痛发作的平均时间,并得到了退变椎体的生存函数。本研究为未来对人类颈椎和腰椎椎体前缘骨赘生长的量化和数学建模打开了大门。所测量的随访数据已共享以供未来研究使用。

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