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Positron Emission Tomography

Positron Emission Tomography

Positron emission tomography (PET) is a medical imaging technique involving radiopharmaceuticals — substances that emit short-lived radiation. Although the first PET scanner was introduced in 1961, it took 15 more years before radiopharmaceuticals were combined with the technique and revolutionized its potential.
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Related Experiment Video

Updated: Dec 13, 2025

Hybrid PET/MRI Imaging of Alzheimer's Disease Based on 18F-AV-1451

Hybrid PET/MRI Imaging of Alzheimer's Disease Based on ¹⁸F-AV-1451

Published on: April 18, 2025

Determining Amyloid-β Positivity Using ¹⁸F-AZD4694 PET Imaging.

Joseph Therriault^1,2,3, Andrea L Benedet^1,2,3, Tharick A Pascoal^1,2,3

¹Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Quebec, Canada.

Journal of Nuclear Medicine : Official Publication, Society of Nuclear Medicine

|August 2, 2020

Summary

This study establishes a quantitative threshold for amyloid-β PET imaging using 18F-AZD4694, aiding Alzheimer

Keywords:

18F-AZD4694 Alzheimer disease PET amyloid-β

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Detecting Amyloid-β Accumulation via Immunofluorescent Staining in a Mouse Model of Alzheimer's Disease

Detecting Amyloid-β Accumulation via Immunofluorescent Staining in a Mouse Model of Alzheimer's Disease

Published on: April 19, 2021

Area of Science:

Neurology
Nuclear Medicine
Biomarkers

Background:

Amyloid-β plaque deposition is a key pathological marker of Alzheimer's disease (AD), detectable years before symptom onset.
Accurate quantification of amyloid-β burden is crucial for AD diagnosis, clinical management, and clinical trial participant selection.
¹⁸F-AZD4694 is a high-affinity positron emission tomography (PET) ligand for imaging amyloid-β plaques, but quantitative cutoffs are lacking.

Purpose of the Study:

To establish a reliable quantitative threshold for determining amyloid-β positivity using ¹⁸F-AZD4694 PET imaging.
To compare multiple methods for deriving this quantitative cutoff in a diverse cohort.

Main Methods:

176 individuals (young adults, cognitively unimpaired elderly, cognitively impaired) underwent ¹⁸F-AZD4694 PET, lumbar puncture, MRI, and APOE genotyping.
Five methods were used to derive quantitative thresholds: comparison with young-control SUV ratios (SUVRs), ROC curves (clinical and visual classification), Gaussian Mixture Modeling, and comparison with CSF Aβ₄₂/Aβ₄₀ ratio.
¹⁸F-AZD4694 SUVRs were normalized to cerebellar gray matter.

Main Results:

Four methods (ROC curves based on visual/clinical classification, Gaussian Mixture Modeling, CSF Aβ comparison) showed good convergence, yielding optimal cutoffs between 1.51-1.56 SUVR.
A threshold of 1.55 SUVR demonstrated reliable discriminative accuracy across multiple methods.
A method based on young controls' means and 2 SDs produced a lower threshold (1.33 SUVR), disagreeing with other methods.

Conclusions:

Several methods converge to support a quantitative ¹⁸F-AZD4694 PET threshold of 1.55 SUVR for amyloid-β positivity.
This quantitative cutoff offers reliable discriminative accuracy for amyloid-β plaque detection.
While visual assessment is current standard, quantitative thresholds can aid in resolving rater disagreements and evaluating borderline cases in clinical practice.