Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
The goal of this study is to assess the performance of an artificial intelligence software (Osteo Signal) in detecting osteoporosis risk in adults 50 years and older. The main question it aims to answer is: What is the accuracy of the software in detecting osteoporosis risk on chest x-ray images as compared to the standard technique of dual-energy x-ray absorptiometry (DXA)? There is no direct involvement of participants in this study as it will use data from individuals who have already had a chest x-ray and a DXA scan taken in the past.
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Osteo Signal | Device | Artificial Intelligence (AI) software |
| Measure | Description | Time Frame |
|---|---|---|
| Two class bone status classification (osteoporosis/non osteoporosis) | Device output against the lowest DXA as measured by sensitivity, specificity, and area under the ROC curve (AUC) | At a time following the participant having had a chest x-ray and DXA scan within 6 months of each other |
| Measure | Description | Time Frame |
|---|---|---|
| Three class bone status classification (osteoporosis/osteopenia/normal) | Device output against the lowest DXA as measured by area under the ROC curve (AUC), overall per cent agreement, and weighted Cohen's kappa | At a time following the participant having had a chest x-ray and DXA scan within 6 months of each other |
Not provided
Inclusion Criteria:
Age ≥50 years at the time of chest X-ray
Availability of
Complete metadata (sex and age) available on PACS or hospital records.
Exclusion Criteria:
Non-diagnostic Quality or Incomplete Imaging of:
Previous diagnosis or treatment of Osteoporosis prior to the DXA scan used in the Study.
Diagnosis of any metabolic bone disease prior to the DXA scan used in the study.
Diagnosis of metabolic bone disease other than Osteoporosis or Osteopenia, up to a maximum of 3 months (91 days) after the DXA scan.
Major Chest Wall or Spinal Deformities, including but not limited to:
Subject has opted out of confidential data being used for research purposes
Not provided
Not provided
Not provided
Patients selected hospitals in the Netherlands and UK that have previously had chest x-rays and DXA scans
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Kim Bensalem | Contact | +447885369062 | kim@medilife.net | |
| Jung Jinho | Contact | +82 1083113509 | jhjung@promedius.ai |
| Name | Affiliation | Role |
|---|---|---|
| Jacob J Visser, Musculoskeletal Radiologist | Erasmus Medical Center | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Erasmus University Medical Center Rotterdam, | Not yet recruiting | Rotterdam | 3015 GD | Netherlands |
No IPD will be shared. The trial data is proprietary and part of a product development program.
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Classification for osteoporosis and osteopenia |
Positive predictive value (PPV) and negative predictive value (NPV) for osteoporosis and osteopenia classifications |
| At a time following the participant having had a chest x-ray and DXA scan within 6 months of each other |
| Mid and South Essex NHS Foundation Trust | Not yet recruiting | Westcliff-on-Sea | Essex | SS0 0RY | United Kingdom |
|
| Barts Health NHS Trust | Recruiting | London | E1 4DG | United Kingdom |
|
| ID | Term |
|---|---|
| D010024 | Osteoporosis |
| D001851 | Bone Diseases, Metabolic |
| ID | Term |
|---|---|
| D001847 | Bone Diseases |
| D009140 | Musculoskeletal Diseases |
| D008659 | Metabolic Diseases |
| D009750 | Nutritional and Metabolic Diseases |
Not provided
Not provided