Deep Learning on Amyloid Positons Emission Tomography
About this study
Reducing injected dose and/or acquisition time in amyloid PET imaging would improve comfort, radiation safety and cost-effectiveness in diagnosis and follow-up of patients. This study evaluates the impact of a deep learning-based noise reduction algorithm on visual analysis and Centiloid quantification when simulating reduced injected doses of \[18F\]flutemetamol.
- Condition
- Alzheimer Disease
- Sponsor
- Central Hospital, Nancy, France
Who can join
- Age
- 18 to 99 years
- Sex
- All sexes
- Healthy volunteers
- Not stated
Inclusion 5
- Minimum age: 18 years
- Maximum age: 99 years
- Study condition: Alzheimer Disease
- Patients with objective cognitive impairment,
- Referred to our department for a cerebral \[¹⁸F\]flutemetamol positron emission tomography scan between January 1, 2023 and July 1, 2025,
Exclusion 1
- Patient have objected to the use of their data.
Where
3 sites, 3 recruiting
CHRU NANCY Brabois, nuclear medicine department
Vandœuvre-lès-Nancy, France
Nancy's hospital
Vandœuvre-lès-Nancy, France
Nuclear medicine department CHRU de NANCY Brabois
Vandœuvre-lès-Nancy, France
Contact
-
Antoine VERGER, MD,PhD
0383155567 a.verger@chru-nancy.fr
-
Veronique Roch, MSc
0383154276 v.roch@chru-nancy.fr
Potential match only. Final eligibility is determined by the study team.