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)
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
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Detailed Description
Only two studies compared images denoised by a Deep Learning algorithm to those denoised by conventional filters (Gaussian and median filters). The first study was conducted only on patients, without phantom analysis and without taking into account the size of the lesions. The second study included an analysis on phantom and patients, but with application to planar images rather than to SPECT images that are increasingly used today
The hypothesis of our study conducted on phantom and patients is that an artificial intelligence algorithm reducing noise could replace the conventional filters usually used in bone SPECT for the denoising of scintigraphic images.
Study Type
Study Type
Enrollment (Actual)
Enrollment
Contacts and Locations
Study Contact
Study Contact
- Name: VERONIQUE ROCH, MSc
- Phone Number: +33 0383154276
- Email: v.roch@chru-nancy.fr
Study Contact Backup
- Name: Achraf BAHLOUL, MD
- Phone Number: +33 0383153911
- Email: a.bahloul@chru-nancy.fr
Study Locations
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Vandœuvre-lès-Nancy, France, 54511
- Nuclear Medicine Department
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Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
Patients who had a whole-body thee dimensions bone scan for rheumatological or oncological indications.
Exclusion Criteria:
Patients opposed to the use of their data
Study Plan
How is the study designed?
Design Details
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
To compare imaging treated by the intelligence artificial algorithm with imaging treated with the traditionnal filter artificial algorithm
Time Frame: one day
|
Quantification value on imaging measured with intelligence artificial algorithm compared with quantification value measured with conventional filter
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one day
|
Collaborators and Investigators
Sponsor
Sponsor
Publications and helpful links
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Actual)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Other Study ID Numbers
Other Study ID Numbers
- 2024PI241
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
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