Diagnostic accuracy of cranial and large vessel giant cell arteritis with digital [18F]FDG PET/CT

[ 18 F]Fluorodeoxyglucose ([ 18 F]FDG) PET/CT has become a standard imaging modality for assessment of large vessel vasculitis. Digital PET/CT enhanced performance may improve evaluation of cranial arteries in giant cell arteritis (GCA). This study assesses digital [ 18 F]FDG PET/CT for the combined evaluation of cranial and large vessel-GCA. [ 18 F]FDG PET/CT scans of patients > 50 years with suspected GCA and elevated inflammatory markers were retrospectively reviewed. Exclusion criteria were corticosteroid therapy > 3 days pre-scan or known vasculitis. Images were visually graded by nuclear physicians blinded to clinical data with guideline-proposed criteria and considered positive for cranial-GCA with grade ≥ 1 uptake (above surrounding tissues) and grade 3 (> liver uptake) for large vessel-GCA. Whole-body semi-quantitative analysis was also performed. Reference standard was final clinical diagnosis after ≥ 6-month follow-up based on clinical course, biochemical evolution, imaging and biopsy results, or if followed for < 6 months, definitive non-GCA diagnosis such as infection or spontaneously resolved symptoms with normalization of inflammatory markers. Fifty-six patients (mean age 78 ± 12 years, 36 female) were included. Among 24 patients (43%) with final GCA diagnosis, 21 scans (38%) were true positives (62% cranial-GCA, 5% large vessel-GCA, 33% combined). Three false negatives included patients receiving intravenous corticosteroids with altered [ 18 F]FDG biodistribution (demonstrating decreased brain uptake). Four false positives included grade 3 aortic or grade 1-2 vertebral artery uptake. Eight out of 32 patients (25%) without GCA had alternative PET/CT diagnoses. Combined cranial and large vessel-GCA assessment yielded 88% sensitivity and specificity (95% CI 68-97% and 71-96% respectively). Reclassifying grade-2 large vessel uptake as negative improved specificity from 63% to 88% without reducing sensitivity. Target-to-background-ratios outperformed SUV max on evaluation of large vessels and combined assessments but had similar accuracy for cranial arteries. Digital [ 18 F]FDG PET/CT demonstrated high diagnostic accuracy for cranial and large vessel-GCA while identifying alternative aetiologies of inflammation, highlighting its potential as a first-line imaging modality.

Authors

Institutions

Publication Details

Journal
EANM Innovation
Published
2026-03-17
DOI
https://doi.org/10.1016/j.eanmi.2026.100165
Primary Topic
Vasculitis and related conditions
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Diagnostic accuracy of cranial and large vessel giant cell arteritis with digital [18F]FDG PET/CT

Noah Ben-Ezra, Peter George Maliha, Gad Abikhzer, Laeora Berkson et al.
EANM Innovation
Vasculitis and related conditions
article

Diagnostic accuracy of cranial and large vessel giant cell arteritis with digital [18F]FDG PET/CT

Noah Ben-Ezra, Peter George Maliha, Gad Abikhzer, Laeora Berkson, Pen Yin, Murray Baron, Marie Hudson
article en

Abstract

[ 18 F]Fluorodeoxyglucose ([ 18 F]FDG) PET/CT has become a standard imaging modality for assessment of large vessel vasculitis. Digital PET/CT enhanced performance may improve evaluation of cranial arteries in giant cell arteritis (GCA). This study assesses digital [ 18 F]FDG PET/CT for the combined evaluation of cranial and large vessel-GCA. [ 18 F]FDG PET/CT scans of patients > 50 years with suspected GCA and elevated inflammatory markers were retrospectively reviewed. Exclusion criteria were corticosteroid therapy > 3 days pre-scan or known vasculitis. Images were visually graded by nuclear physicians blinded to clinical data with guideline-proposed criteria and considered positive for cranial-GCA with grade ≥ 1 uptake (above surrounding tissues) and grade 3 (> liver uptake) for large vessel-GCA. Whole-body semi-quantitative analysis was also performed. Reference standard was final clinical diagnosis after ≥ 6-month follow-up based on clinical course, biochemical evolution, imaging and biopsy results, or if followed for < 6 months, definitive non-GCA diagnosis such as infection or spontaneously resolved symptoms with normalization of inflammatory markers. Fifty-six patients (mean age 78 ± 12 years, 36 female) were included. Among 24 patients (43%) with final GCA diagnosis, 21 scans (38%) were true positives (62% cranial-GCA, 5% large vessel-GCA, 33% combined). Three false negatives included patients receiving intravenous corticosteroids with altered [ 18 F]FDG biodistribution (demonstrating decreased brain uptake). Four false positives included grade 3 aortic or grade 1-2 vertebral artery uptake. Eight out of 32 patients (25%) without GCA had alternative PET/CT diagnoses. Combined cranial and large vessel-GCA assessment yielded 88% sensitivity and specificity (95% CI 68-97% and 71-96% respectively). Reclassifying grade-2 large vessel uptake as negative improved specificity from 63% to 88% without reducing sensitivity. Target-to-background-ratios outperformed SUV max on evaluation of large vessels and combined assessments but had similar accuracy for cranial arteries. Digital [ 18 F]FDG PET/CT demonstrated high diagnostic accuracy for cranial and large vessel-GCA while identifying alternative aetiologies of inflammation, highlighting its potential as a first-line imaging modality.

EANM InnovationVol. 3
Jewish General Hospital (CA), Centre Hospitalier de l’Université de Montréal (CA), McGill University (CA)
Openalex Percentile: Top 20%
Vasculitis and related conditions
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.