Aug 2026· European Journal of Nuclear Medicine and Molecular Imaging· 0 citations· 20 references
Medicine
TL;DR
Amyloid PET positivity consistently predicted conversion to AD regardless of interpretation method, and visual and semiquantitative approaches showed numerically higher prognostic discrimination, while expert structured visual reading remained clinically reliable.
Abstract
Purpose
This study assessed the prognostic value and inter-/intra-observer reliability of three amyloid PET interpretation methods-conventional visual reading, assisted visual interpretation and standardized uptake value ratio (SUVR)-based quantification-for predicting conversion to Alzheimer's disease (AD).
Methods
This retrospective longitudinal study included 145 patients with amnestic mild cognitive impairment who underwent amyloid PET and were followed for up to 8 years at a single memory clinic. Two certified nuclear medicine physicians performed structured visual reads and assisted visual interpretations. Semiquantitative SUVR thresholds validated in prior studies were applied as a third method. Inter- and intra-observer agreement was assessed using Cohen's kappa (κ). Cox regression models estimated the association of conversion to AD in PET-positive versus PET-negative patients for each method, adjusting for age, sex and education.
Results
Inter-observer agreement was excellent for structured visual reading (κ = 0.877) and assisted visual interpretation (κ = 0.904). Intra-observer reliability was also high (κ = 0.891 for Reader 1; κ = 0.859 for Reader 2). Consensus agreement for the assisted method reached κ = 0.936. Amyloid PET positivity was strongly associated with progression to AD across all methods. Hazard ratios were highest for assisted visual interpretation (HR = 3.23, 95% CI 1.94-5.38, p < 0.0001), followed by SUVR quantification (HR = 2.19, 95% CI 1.55-3.10, p < 0.0001) and structured visual reading (HR = 1.83, 95% CI 1.10-3.06, p = 0.02).
Conclusion
Amyloid PET positivity consistently predicted conversion to AD regardless of interpretation method. Assisted visual and semiquantitative approaches showed numerically higher prognostic discrimination, while expert structured visual reading remained clinically reliable.
BackgroundAlzheimer's disease (AD) is increasingly defined biologically. Amyloid positron emission tomography (PET) is a validated biomarker; however, evidence from truly consecutive, real-world memory-clinic cohorts spanning subjective cognitive decline (SCD), mild cognitive impairment (MCI), and early AD remains limi...
Heii Arai, Satoko Aiba, Hideo Yamamoto et al.· Journal of Alzheimer's Disea...· 0 citations
Abstract INTRODUCTION Longitudinal evidence on amyloid positron emission tomography (PET) for Alzheimer's disease (AD) diagnosis in Taiwan and Asian memory clinics remains limited. This study evaluated the diagnostic and prognostic impact of florbetaben PET in a Taiwanese cohort. METHODS This prospective cohort study e...
Visual interpretation of amyloid PET can be performed in a real-world clinical setting with high reliability, and lower concordance between local and expert reads was associated with low local reader confidence.
Konstantinos Chiotis, C. Windon, B. Siegel et al.· Journal of Nuclear Medicine· 0 citations
Quantitative T1 mapping (qT1) is a magnetic resonance imaging (MRI) biomarker of brain microstructural changes; however, its application in Alzheimer disease (AD) remains limited. We compared cortico-limbic qT1 values between patients with AD and healthy controls (HCs) and examined their relationship with amyloid burde...
L. Gualco, N. Montobbio, M. Losa et al.· European Radiology Experimen...· 0 citations
Background Ordered-subset expectation-maximization (OSEM) PET reconstruction is limited by spatial resolution and partial-volume effects, contributing to interreader variability and false positives and highlighting the need for more comprehensive alternative approaches. Purpose To evaluate whether MRI-guided brain PET...
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Cortical gray matter provides the most stable reference region and supports harmonized, covariate-adjusted normative datasets for clinical and research applications and is the major sources of variance in brain [¹⁸F]FDG-PET quantification in CN subjects.
Giordana Salvi de Souza, G. Povala, G. G. S. Peixoto et al.· bioRxiv· 0 citations
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