Macrophage-mediated inflammation and microcalcification are associated with abdominal aortic aneurysm progression and clinical events.
Abstract
INTRODUCTION Molecular and cellular imaging biomarkers of abdominal aortic aneurysms (AAA) show promise as potential predictors of clinical events. This study assessed long-term clinical outcomes using ultrasmall superparamagnetic particles of iron oxide (USPIO) enhanced magnetic resonance imaging (MRI; ISRCTN76413758) and fluorine-18 sodium fluoride ([18F]NaF) positron emission tomography computed tomography (PET/CT; NCT02229006).
Methods
A prospective multi-centre co-enrolled observational cohort studies of patients with asymptomatic AAA. Evaluation of aortic wall inflammation using USPIO-enhanced MRI in 338 patients was followed by [18F]NaF PET/CT in a sub-group of 72 patients, to evaluate microcalcification. Aneurysms were classified according to aortic wall USPIO enhancement and into tertiles of [18F]NaF uptake. Aneurysm expansion, composite of rupture or repair, and overall survival were compared.
Results
In 338 predominantly elderly (74±7.2 years) men (85%) with mean aneurysm diameter 49.5±7.3 mm, aneurysm expansion was increased in patients with USPIO enhancement (median [inter-quartile interval], 3.3 [2.0-4.6] versus 2.5 [1.4-3.6] mm/y; p=.002) or high [18F]NaF uptake (4.0 [2.6-5.4] versus 1.9 [0.9-3.0] mm/y; p<.001), even when adjusted for hypertension, smoking and baseline AAA diameter (p=.04 and p=.003). After a median follow up of 102 [58-119] months, 63% patients met the composite endpoint of rupture or repair with high [18F]NaF uptake associated with more than two-fold higher risk (72% versus 36%; log rank p=.002). There was no association between USPIO enhancement and future rupture or repair.
Conclusions
Aortic wall USPIO enhancement and [18F]NaF uptake are independently associated with AAA expansion. These non-invasive imaging biomarkers provide an opportunity to identify those are at greatest risk of AAA progression and may help inform further research to determine optimal surveillance intervals.