Development of a simple standardized scoring system for assessing large vessel vasculitis by 18F-FDG PET-CT, and differentiation from atherosclerosis

Abstract Purpose: to develop a structured approach to distinguishing large-artery vasculitis from atherosclerosis using 18-fluorodeoxyglucose positron emission tomography combined with low-dose computed tomography (FDG PET/CT). Methods: We evaluated the FDG PET/CT images of 60 patients, 30 having biopsy-proven giant cell arteritis (GCA; the most common form of large-artery vasculitis), and 30 with atherosclerosis. Twelve nuclear medicine physicians evaluated images using 5 criteria: FDG uptake pattern (intensity, distribution, circularity), the degree of calcification, and co-localization of calcifications with FDG-uptake. Criteria that passed agreement and reliability tests were subsequently analysed for accuracy using receiver operator curve (ROC) analyses. Criteria that showed discriminative ability were then combined in a multi-component scoring system. Observers also reported both initial and final ‘gestalt’ conclusion before and after detailed examination of the images. Results: Agreement and reliability analyses disqualified 3 of the 5 criteria, leaving only FDG uptake intensity and calcification for potential use in a scoring system. ROC analysis showed an area under the curve (AUC) of 0.90 (95%CI 0.87 - 0.92) for FDG uptake intensity. Degree of calcification showed poor discriminative ability on its own (AUC of 0.62 (95%CI 0.58 - 0.66). When combining presence of calcification with FDG uptake intensity into a 6-tiered scoring system, the AUC remained similar at 0.91 (95%CI 0.88-0.93). After exclusion of cases with arterial prostheses, the AUC increased to 0.93 (95%CI 0.91 - 0.95). The accuracy of the ‘gestalt’ conclusion was initially 89% (95%CI 86% - 91%) and increased to 93% (95%CI 91 - 95%) after detailed image examination. Conclusion: Standardised assessment of arterial wall FDG uptake intensity, preferably combined with assessment of arterial calcifications into a scoring method enables accurate distinction between large artery vasculitis and atherosclerosis.