Revolutionizing Osteoporosis and Bone Fracture Diagnostics: The Emergence of Microwave Antenna Technology

• Published in: IEEE access 2024, Vol.12, p.160418-160440
• Main Authors: Shakhawat Hossen, Md, Tariqul Islam, Mohammad, Hoque, Ahasanul, Alenezi, Abdulmajeed M., Kirawanich, Phumin, Hafiz Baharuddin, Mohd, Faouri, Yanal S., Arafatur Rahman, Md
• Format: Article
• Language: English
• Subjects: biomedical antenna; bone fracture diagnosis; Bone mineral density; Bones; Computed tomography; Costs; Diagnosis; Dielectrics; Fractures; Machine learning; Magnetic resonance imaging; microwave antenna; Microwave antennas; Microwave imaging; microwave machine learning; Microwave measurement; Microwave theory and techniques; Osteoporosis; osteoporosis detection; Parameter identification; S parameters; Sensors; X-ray imaging
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2024.3487858

Osteoporosis, a medical condition distinguished by the reduction of bone mineral density and the consequent degradation of bone structure, poses significant health scrutiny, especially in elderly individuals. The fractures and hospitalisations that occur worldwide are a direct consequence of socioeconomic conditions. Prompt intervention and therapy are crucial for the early stage osteoporosis diagnosis and the detection of bone fractures. Several established methods, including single-energy X-ray absorptiometry (SXA), dual-energy X-ray absorptiometry (DEXA), non-invasive magnetic resonance imaging (MRI), quantitative CT (QCT), quantitative ultrasonography (QUS), and others, are now being employed for diagnostic purposes. Despite the availability of these technologies, microwave sensing has emerged as a feasible approach for early identification of osteoporosis and bone fractures, owing to its numerous advantages. This review paper aims to provide a comprehensive summary of recent advancements in microwave sensing techniques specifically aimed at detecting osteoporosis and diagnosing bone fractures. Various measuring, sensing, and antenna scattering parameter post-processing approaches are classified and assessed for their effectiveness in identifying alterations in bone characteristics associated with osteoporosis. These techniques encompass both traditional non-invasive and invasive scanning procedures, along with more sophisticated machine learning-based prediction approaches. The reliability and efficiency of microwave sensing as a tool for the early detection of osteoporosis stage and bone fractures has been demonstrated by this work. This generates prospects for enhanced patient care and more intricate diagnosis and management strategies.