About this trial
This study aims to test a new artificial intelligence (AI) method to create brain scan images without needing an extra scan. Currently, patients with memory problems often undergo two types of PET scans (Amyloid PET and FDG PET) to assess Alzheimer's disease. This study will use existing scan data from patients who already had both scans as part of their routine care.
The AI model will try to generate the FDG PET image using only the Amyloid PET scan and an MRI. If successful, this method could reduce radiation exposure, costs, and time for future patients by eliminating the need for a separate FDG injection and scan.
No new scans, injections, or procedures will be performed for this study. All data will be fully anonymized (personal information removed) before analysis. The study involves approximately 35 adult patients (age 50+) whose data were collected between January 2025 and December 2025 at IRCCS Ospedale San Raffaele in Milan, Italy.
Eligibility criteria
Qualifiers
Age ≥ 50 years at the time of imaging.
Clinically indicated amyloid PET scan performed with Florbetaben or Flutemetamol between January 1, 2025 and December 31, 2025.
Availability of paired structural MRI (3D T1-weighted) and real [18F]FDG PET scan acquired within ±6 months of the amyloid PET.
All three imaging modalities (Amyloid PET, FDG PET, MRI) are of sufficient technical quality for co-registration and quantitative analysis.
Disqualifiers
Presence of other major neurological disorders that may confound FDG metabolism (e.g., Parkinson's disease, frontotemporal dementia, brain tumor, or recent stroke).
Severe motion artifacts or technical failures in any of the three imaging modalities that prevent reliable co-registration or SUVR calculation.
Incomplete or irreversibly corrupted DICOM data preventing anonymization or conversion to analysis-ready format.
Trial design
Treatments tested in this trial
- Not listed