Deep Learning on Amyloid Positons Emission Tomography (DEEPAMY)

Central Hospital, Nancy, France

Status: Not yet enrolling

Conditions: Alzheimer Disease

Study type: Observational

Funder types: Other

Identifiers

NCT07309107

2025PI190

Details and patient eligibility

About

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.

Enrollment: 40 estimated patients

Sex: All

Ages: 18 to 99 years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• 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 criteria

• Patient have objected to the use of their data.