Advances in Osteoporosis Diagnosis: A Comprehensive Review of Conventional and Emerging Methods

Abstract

Osteoporosis is a common, chronic, and progressive metabolic bone disorder that is characterized by low bone mass and degeneration of the microarchitecture of the skeleton which predisposes individuals to an increased risk of fractures, particularly among postmenopausal women and elderly individuals. In this review, commonly used and newly developed techniques for the diagnosis of osteoporosis are reviewed. Dual-energy X-ray absorptiometry (DXA) is still the clinical application of choice to date for bone mineral density (BMD) measurement in view of its utility and convenience, whereas quantitative computed tomography (QCT) affords a three-dimensional structural assessment and sensitive probes for trabecular degradation. Magnetic Resonance Imaging (MRI) is an excellent modality for assessing bone microarchitecture and marrow composition, while quantitative ultrasound (QUS) offers a low-cost radiation-free screening solution. Biochemical markers (procollagen type I N-terminal propeptide [P1NP], bone-specific alkaline phosphatase [B-ALP], osteocalcin [OC], C-telopeptide of type I collagen [CTX] have also proven to be useful for the evaluation of bone turnover and treatment response. Digital tools, such as Artificial Intelligence (AI) models and mobile health (mHealth) applications based on emerging digital technologies, are changing our diagnostic paths with increased prediction accuracy, patient involvement, and remote surveillance. However, despite these achievements, diagnostic issues remain due to biological variations as well as the lack of consensus and widespread clinical validation. Combining imaging modalities, biochemical markers, and AI-based analytics appears the most hopeful route toward early, personalized, yet affordable osteoporosis detection