Evaluation of an Artificial Intelligence Algorithm Reducing Noise on Fast Whole-body Bone Tomoscintigraphy Acquisitions Recorded by a 360 Degree Cadmium-Zinc-Tellurid Camera
IATOS2
1 other identifier
observational
20
1 country
1
Brief Summary
Recently, artificial intelligence algorithms reducing noise by deep learning have been developed with application to SPECT and PET images. Many studies have reported the possibility of reducing the recording time in bone scintigraphy by applying artificial intelligence algorithms reducing noise
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at below P25 for all trials
Started Feb 2025
Shorter than P25 for all trials
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
January 7, 2025
CompletedFirst Posted
Study publicly available on registry
January 17, 2025
CompletedStudy Start
First participant enrolled
February 27, 2025
CompletedPrimary Completion
Last participant's last visit for primary outcome
March 15, 2025
CompletedStudy Completion
Last participant's last visit for all outcomes
March 30, 2025
CompletedMarch 4, 2025
February 1, 2025
16 days
January 7, 2025
February 28, 2025
Conditions
Outcome Measures
Primary Outcomes (1)
To compare imaging treated by the intelligence artificial algorithm with imaging treated with the traditionnal filter artificial algorithm
Quantification value on imaging measured with intelligence artificial algorithm compared with quantification value measured with conventional filter
one day
Interventions
to apply an artificial intelligence algorithm to treat the imaging
Eligibility Criteria
Patients who had a whole-body thee dimensions bone scan for rheumatological or oncological indications and non opposed to th use of their data
You may qualify if:
- Patients who had a whole-body thee dimensions bone scan for rheumatological or oncological indications.
You may not qualify if:
- Patients opposed to the use of their data
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Nuclear Medicine Department
Vandœuvre-lès-Nancy, 54511, France
Related Publications (1)
Bahloul A, Rajadhas F, Doyen M, Lamash Y, Roth N, Roch V, Marie PY, Imbert L. A deep-learning noise reduction algorithm outperforms the spatial filters previously required for bone SPECT on a high-speed whole-body 360 degrees CZT-camera. EJNMMI Res. 2025 Dec 31. doi: 10.1186/s13550-025-01344-1. Online ahead of print.
PMID: 41474536DERIVED
Central Study Contacts
Study Design
- Study Type
- observational
- Observational Model
- OTHER
- Time Perspective
- RETROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- PRINCIPAL INVESTIGATOR
- PI Title
- Principal investigator
Study Record Dates
First Submitted
January 7, 2025
First Posted
January 17, 2025
Study Start
February 27, 2025
Primary Completion
March 15, 2025
Study Completion
March 30, 2025
Last Updated
March 4, 2025
Record last verified: 2025-02