Sources of Variability in Normative Cerebral [18F]FDG-PET imaging

[18F]FDG PET outperforms MRI for detecting early tau-related neurodegeneration.

Hypometabolism is a sensitive and early marker of AD-related neurodegeneration, preceding MRI-detectable GM atrophy and more closely reflecting underlying tau pathology across disease stages.

MRI-free amyloid PET quantification using a deep learning model and white matter reference

Deep learning–based amyloid PET segmentation enables accurate MRI-free quantification of gray and white matter SUVRs and simplifies clinical workflow while maintaining diagnostic performance comparable to MRI-based methods for AD diagnosis.

Regional differences in 18F-flutemetamol accumulation between amyloid-positive and -negative brains using high-resolution dedicated head PET scanner.

High-resolution dhPET revealed significantly higher SUVRs in Aβ⁺ compared with Aβ⁻ subjects in supratentorial structures, including cerebral white matter, and in cerebellar gray matter.

Revisiting intensity normalization in brain [18F]FDG PET: What is reliable in autoimmune encephalitis?

Purpose Data-driven intensity normalization has emerged as an alternative to proportional scaling (PS) and reference-region methods in brain [18F]FDG PET. However, no consensus exists for autoimmune encephalitis (AE), whose variable metabolic patterns and lack of a reliable disease-free reference region complicate norm...

Translating SUVR bias correction to amyloid PET enables early imaging and more accurate simplified quantification

Differential associations of tau extent and load with brain metabolic and cognitive dysfunction in Alzheimer's disease

Summary Background Reduced [18F]Fluorodeoxyglucose ([18F]FDG)-PET uptake is a core imaging feature of Alzheimer's disease (AD). While tau load correlates with this metabolic signature, it remains unclear whether the spatial extent of tauopathy (SEOT) more accurately explains brain glucose hypometabolic patterns. Here,...