Clinical trial · Observational
Automated Detection of Metastatic Bone Disease on Bone Scintigraphy Scans
In Silico Clinical Trial Comparing the Reading Accuracy of Doctors and a Deep Learning Algorithm for Detection of Metastatic Bone Disease on Bone Scintigraphy Scans.
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
Bone scintigraphy scans are two dimensional medical images that are used heavily in nuclear medicine. The scans detect changes in bone metabolism with high sensitivity, yet it lacks the specificity to underlying causes. Therefore, further imaging would be required to confirm the underlying cause. The aim of this study is to investigate whether deep learning can improve clinical decision based on bone scintigraphy scans.
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Metastatic Bone Tumor | Bone Neoplasm | CURATED_BROADER | 0.78 |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Deep learning based detection of metastatic bone disease on bone scintigraphy scans. | Other | — | UNRESOLVED |
Design
Arms and outcomes
Arms (3)
- label
- BS-UKA
- description
- Patients who underwent bone scintigraphy scanning between 2010 and 2018 at RTWH Aachen university hospital, and had a bone scan report that indicates the presence or absence of metastatic bone disease.
- interventionNames
- Other: Deep learning based detection of metastatic bone disease on bone scintigraphy scans.
- label
- BS-Namur
- description
- Patients who underwent bone scintigraphy scanning between 2010 and 2018 at Namur university hospital, and had a bone scan report that indicates the presence or absence of metastatic bone disease.
- interventionNames
- Other: Deep learning based detection of metastatic bone disease on bone scintigraphy scans.
- label
- BS-Aalborg
- description
- Patients who underwent bone scintigraphy scanning between 2010 and 2018 at Aalborg university hospital, and had a bone scan report that indicates the presence or absence of metastatic bone disease.
Eligibility
Eligibility (as posted)
- Sex
- All
Show eligibility criteria text
Inclusion Criteria: * Patients who underwent a bone scintigraphy scan that is available with the radiologic report between 2010-2018 Exclusion Criteria: * The lack of a bone scan, or corresponding radiologic report
References
Publications (1)
- RESULTIbrahim A, Vaidyanathan A, Primakov S, Belmans F, Bottari F, Refaee T, Lovinfosse P, Jadoul A, Derwael C, Hertel F, Woodruff HC, Zacho HD, Walsh S, Vos W, Occhipinti M, Hanin FX, Lambin P, Mottaghy FM, Hustinx R. Deep learning based identification of bone scintigraphies containing metastatic bone disease foci. Cancer Imaging. 2023 Jan 25;23(1):12. doi: 10.1186/s40644-023-00524-3. PMID 36698217