Optimizing PET Intensity Normalization for the Analysis of Cerebral Metabolism: A Study in Simulated and Real Data from an Alzheimer's Disease Model
Helena Chamberlain‐Alvarado, Marta Cortes‐Canteli, Marta Casquero‐Veiga · 2025
Read Optimizing PET Intensity Normalization for the Analysis of Cerebral Metabolism: A Study in Simulated and Real Data from an Alzheimer's Disease Model by Helena Chamberlain‐Alvarado, Marta Cortes‐Canteli, Marta Casquero‐Veiga (2025) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-11714634.txt.
Description
Helena Chamberlain-Alvarado and co-authors test six ways of normalizing brain PET scans, a scaling step that can make or break metabolic comparisons, in a 2025 study. Alzheimer's disease alters brain metabolism long before symptoms, and PET reads it, but only after intensities are normalized. The team planted known patterns into scans of healthy mice and graded each method on recovery.
No method won everywhere. An iterative histogram method served best when the data carried no strong bias, while a reference-cluster method, anchored on preserved brain regions, won under heavy bias. Guided by the tests, the histogram method then revealed age-shifting genotype effects in a real Alzheimer's mouse model. The authors give simple rules for choosing before scanning patients or animals.
Catalog record
| CREATOR | Helena Chamberlain‐Alvarado, Marta Cortes‐Canteli, Marta Casquero‐Veiga |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 3 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |