Deep Learning on Amyloid Positons Emission Tomography

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

NOT_YET_RECRUITING

Total Enrollment

40 participants

Study Classification

OBSERVATIONAL

Study Start Date

2026-01-06

Study Completion Date

2026-01-30

Brief Summary

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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.

Detailed Description

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Conditions

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Alzheimer Disease

Study Design

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Observational Model Type

OTHER

Study Time Perspective

RETROSPECTIVE

Eligibility Criteria

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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.

Minimum Eligible Age

18 Years

Maximum Eligible Age

99 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Responsible Party

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Antoine VERGER

Principal Investigator

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Antoine VERGER, MD, PhD

Role: PRINCIPAL_INVESTIGATOR

CHRU of NANCY

Central Contacts

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Ayaz TAHMAROV, MD

Role: CONTACT

Phone: 0383153911

Email: [email protected]

Véronique ROCH, MSc