Department of Orthopaedics, The Second Hospital of Lanzhou University, China; Gansu Orthopaedic Clinical Medical Research Centre, China; Gansu Intelligent Orthopaedic Industry Technology Centre, China.
Department of Orthopaedics, The Second Hospital of Lanzhou University, China; Gansu Orthopaedic Clinical Medical Research Centre, China; Gansu Intelligent Orthopaedic Industry Technology Centre, China.
Clin Nutr ESPEN. 2024 Dec;64:207-214. doi: 10.1016/j.clnesp.2024.10.001. Epub 2024 Oct 11.
This review aims to explore the strengths and dilemmas of existing osteoporosis screening tools and suggest possible ways of optimization, in addition to exploring the potential of AI-integrated X-ray imaging in osteoporosis screening, especially its ability to improve accuracy and applicability to different populations. To break through the dilemma of low accessibility, poor clinical translation, complexity of use, and apparent limitations of screening results of existing osteoporosis screening tools.
A comprehensive literature search was performed using PubMed, Web of Science, and CNKI databases. The search included articles published between 2000 and 2023, focusing on studies evaluating osteoporosis screening tools, Artificial intelligence applications in medical imaging, and implementing AI technologies in clinical settings.
The Osteoporosis Risk Assessment Tool for Asians (OSTA), the Simple Calculated Osteoporosis Risk Estimator (SCORE), age, body size, one or no estrogen ever (ABONE), and the Osteoporosis Risk Index (OSIRIS) are the six commonly used screening tools for osteoporosis that are discussed in this review. In addition, the performance of AI-integrated imaging systems is explored in light of relevant research advances in Artificial intelligence in osteoporosis screening. Studies of the use of these tools in different populations and their advantages and disadvantages were included in the selection criteria.
The results highlight that AI-integrated X-ray imaging technologies offer significant improvements over traditional osteoporosis screening tools. Artificial intelligence systems demonstrated higher accuracy by incorporating complex clinical data and providing personalized assessments for diverse populations. The studies showed that AI-driven imaging could enhance sensitivity and specificity, particularly in detecting early-stage bone density loss in patients with complex clinical profiles. The findings also suggest that Artificial intelligence technologies have the potential to be effectively applied in resource-limited settings through the use of mobile devices and remote diagnostics.
AI-integrated X-ray imaging technology significantly advances osteoporosis screening, offering more accurate and adaptable solutions than traditional tools. Its ability to incorporate complex clinical data and apply it across various demographic groups makes it particularly promising in diverse and resource-limited environments. Further research is needed to explore the full potential of AI in enhancing screening accessibility and effectiveness, particularly in underserved populations.
本综述旨在探讨现有骨质疏松症筛查工具的优势和困境，并提出可能的优化方法，同时探讨人工智能集成 X 射线成像在骨质疏松症筛查中的应用潜力，特别是其提高准确性和适用于不同人群的能力。旨在突破现有骨质疏松症筛查工具的低可及性、临床转化差、使用复杂和筛查结果明显局限性的困境。
通过 PubMed、Web of Science 和中国知网（CNKI）数据库进行全面的文献检索。检索时间跨度为 2000 年至 2023 年，重点评估骨质疏松症筛查工具、医学影像人工智能应用以及在临床环境中实施人工智能技术的相关研究。
本综述讨论了六种常用的骨质疏松症筛查工具，包括亚洲人骨质疏松风险评估工具（OSTA）、简单计算骨质疏松风险估计器（SCORE）、年龄、体型、曾经或从未使用过雌激素（ABONE）和骨质疏松风险指数（OSIRIS）。此外，还根据人工智能在骨质疏松症筛查方面的相关研究进展，探讨了人工智能集成成像系统的性能。研究中纳入了这些工具在不同人群中的使用情况及其优缺点。
结果表明，人工智能集成 X 射线成像技术在骨质疏松症筛查方面具有显著优势。人工智能系统通过纳入复杂的临床数据并为不同人群提供个性化评估，提高了准确性。研究表明，人工智能驱动的成像可以提高敏感性和特异性，特别是在检测具有复杂临床特征的患者的早期骨密度损失方面。研究结果还表明，人工智能技术具有通过使用移动设备和远程诊断在资源有限的环境中有效应用的潜力。
人工智能集成 X 射线成像技术显著推进了骨质疏松症筛查，提供了比传统工具更准确和适应性更强的解决方案。它能够纳入复杂的临床数据并应用于各种人群，使其在多样化和资源有限的环境中具有特别广阔的应用前景。需要进一步研究以探索人工智能在提高筛查可及性和有效性方面的全部潜力，特别是在服务不足的人群中。
