Department of Biomedical Engineering, Lund University, Box 118, 221 00, Lund, Sweden.
Department of Applied Physics, University of Eastern Finland, Kuopio, Finland.
Curr Osteoporos Rep. 2021 Dec;19(6):676-687. doi: 10.1007/s11914-021-00711-w. Epub 2021 Nov 13.
Statistical models of shape and appearance have increased their popularity since the 1990s and are today highly prevalent in the field of medical image analysis. In this article, we review the recent literature about how statistical models have been applied in the context of osteoporosis and fracture risk estimation.
Recent developments have increased their ability to accurately segment bones, as well as to perform 3D reconstruction and classify bone anatomies, all features of high interest in the field of osteoporosis and fragility fractures diagnosis, prevention, and treatment. An increasing number of studies used statistical models to estimate fracture risk in retrospective case-control cohorts, which is a promising step towards future clinical application. All the reviewed application areas made considerable steps forward in the past 5-6 years. Heterogeneities in validation hinder a thorough comparison between the different methods and represent one of the future challenges to be addressed to reach clinical implementation.
自 20 世纪 90 年代以来,形状和外观的统计模型越来越受欢迎,并且在医学图像分析领域得到了广泛应用。本文回顾了统计模型在骨质疏松症和骨折风险评估方面的应用的最新文献。
最近的发展提高了它们准确分割骨骼的能力,以及进行 3D 重建和分类骨骼解剖结构的能力,这些都是骨质疏松症和脆性骨折诊断、预防和治疗领域非常感兴趣的特征。越来越多的研究使用统计模型来估计回顾性病例对照队列中的骨折风险,这是朝着未来临床应用迈出的有希望的一步。在过去的 5-6 年中,所有回顾的应用领域都取得了相当大的进展。验证中的异质性阻碍了不同方法之间的彻底比较,是未来需要解决的挑战之一,以实现临床实施。