Condition: Osteoporosis · Sponsor: Bangladesh University of Engineering and Technology
Osteoporosis, a pervasive skeletal disorder characterized by diminished bone strength predisposing individuals to an increased risk of fractures, presents a substantial public health challenge globally. It's estimated that osteoporosis and its consequent increase in fracture risk significantly contribute to morbidity, mortality, and economic costs. Despite the availability of effective treatments, the condition often remains undiagnosed and untreated until a fracture occurs, underscoring the critical need for early detection and intervention. Dual-energy X-ray absorptiometry (DEXA) is the gold standard for assessing bone mineral density (BMD) and fracture risk. However, its utility is hampered by limited availability, especially in rural and low-resource settings, such as Bangladesh, where osteoporosis prevalence is notably high. The scarcity of DEXA units exacerbates the challenge of osteoporosis screening and management, leaving a significant portion of the population at risk In this context, plain X-ray imaging, widely available even in resource-constrained settings, emerges as a promising alternative for osteoporosis screening. Recent advancements in deep learning and computer vision offer the potential to automate the analysis of X-ray images for BMD estimation. The primary objective is to curate a comprehensive dataset of X-ray images of hip and spine as well as BMD reports and relevant clinical information sourced from local health facilities in Bangladesh encompassi…
This description comes directly from the study's public registry record.
Taufiq Hasan, PhD · +8801817579844 · taufiq@bme.buet.ac.bd
Farihin Rahman, B.Sc · +8801315091686 · farihinrahman34@gmail.com
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| Ibn Sina Diagnostic Centre, Uttara | Dhaka, Bangladesh | Recruiting |
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Source record: clinicaltrials.gov/study/NCT06652061