Current status and dilemmas of osteoporosis screening tools: A narrative review

Abstract

Objective

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.

Data sources

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.

Study selection

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.

Results

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.

Conclusions

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.