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Technological Innovations in Osteoporosis Diagnosis and their Implications for Bone Metastases Management in Oncology

Year: 2024

Type: article

Abstract: Advances in technology are revolutionizing osteoporosis diagnosis, with significant implications for managing bone metastases in oncology. This review examines cutting-edge diagnostic innovations, including high-resolution imaging techniques like peripheral quantitative computed tomography (HR-pQCT), and their role in detecting subtle changes in bone microarchitecture. It highlights the integration of artificial intelligence (AI) and machine learning for improving diagnostic precision, particularly in distinguishing between osteoporotic fractures and cancer- induced bone damage. Furthermore, the paper explores the intersection of osteoporosis and oncology, focusing on how emerging technologies can facilitate early detection of metastatic bone disease, enhance treatment planning, and improve patient outcomes. By bridging the fields of osteoporosis diagnosis and oncology, this study emphasizes the need for interdisciplinary approaches to address shared challenges in bone health. Future directions for research and clinical applications are also discussed, paving the way for innovations that could transform patient care in both domains.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.14547476

Authors: David Oche Idoko, Moyosoore Mopelola Adegbaju, Abdulrahman Abdullateef, Grace Chinenye Okafor, Nduka Ijeoma

Language: English

Topic: Bone health and osteoporosis research

Subfield: Orthopedics and Sports Medicine

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

OpenAlex ID: W6911833149

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