AI model predicts bone mineral density from X-ray images

Development and Evaluation of an Artificial Intelligence Model for Bone Mineral Density Prediction From X-Ray Images

This study is testing a new AI tool that uses X-ray images to predict bone health in people, especially in places like Bangladesh where traditional tests for osteoporosis are hard to get.

Quick facts

• Study type: Observational
• Enrollment: 600 (estimated)
• Ages: 18 Years and up
• Sex: All
• Sponsor: Bangladesh University of Engineering and Technology (Academic / other)
• Locations: 1 site (Dhaka)
• Trial ID: NCT06652061 on ClinicalTrials.gov

What this trial studies

This observational study aims to develop an artificial intelligence model that predicts bone mineral density (BMD) using X-ray images, addressing the challenge of osteoporosis diagnosis in low-resource settings like Bangladesh. By employing deep learning techniques, particularly convolutional neural networks, the study seeks to create a non-invasive screening tool that reduces reliance on dual-energy X-ray absorptiometry (DEXA) scans, which are often scarce. The research involves both prospective and retrospective data collection from patients undergoing X-ray imaging and DEXA scans, aiming to enhance early diagnosis and management of osteoporosis across diverse populations. The study will aggregate data reflecting variations in bone health among different demographics in Bangladesh.

Who should consider this trial

Good fit: Ideal candidates include individuals aged 18 and above who have X-ray images of the hip and spine along with DEXA scan results.

Not a fit: Patients with incomplete or low-quality X-ray images, or those with medical conditions that significantly affect bone density independently of osteoporosis, may not benefit from this study.

Why it matters

Potential benefit: If successful, this AI model could provide a more accessible and cost-effective method for early osteoporosis detection, potentially reducing fracture risks and improving patient outcomes.

How similar studies have performed: While the use of AI in medical imaging is gaining traction, this specific approach to predicting BMD from X-ray images is relatively novel and has not been extensively tested in prior studies.

Eligibility criteria

▪ Inclusion criteria:

* Female and male patients aged 18 and above
* Individuals willing to participate and who have provided informed consent for the use of their X-ray images and clinical data for research purposes.
* Subjects with both X-ray images of hip and spine and DEXA scan results.
* Accessibility to supplementary medical records that may contribute to the model's predictive accuracy, such as historical data on fractures, pregnancies, relevant medical conditions and other osteoporosis-related factors.
* Exclusion criteria:

  * Subjects for whom X-ray images or clinical data are incomplete or of insufficient quality for analysis.
  * Individuals with medical conditions that could significantly alter bone density independently of osteoporosis, such as bone cancers or certain metabolic diseases.
  * Subjects who have undergone treatments or procedures that might significantly impact bone density measurement, such as long-term steroid use or recent orthopaedic surgeries.
  * Pregnant women, given the potential impact on screening results and the need for special considerations during pregnancy.
  * Patients with implant in hip or spine

Where this trial is running

Dhaka

• Ibn Sina Diagnostic Centre, Uttara — Dhaka, Bangladesh (Recruiting)

Study contacts

• Principal investigator: Taufiq Hasan, PhD — Department of Biomedical Engineering, Bangladesh University of Engineering and Technology (BUET), Dhaka - 1205.
• Study coordinator: Taufiq Hasan, PhD

Conditions Osteoporosis; Bone Mineral Density; AI; Radiography; Deep Learning; Hip and Spine X-Rays