SAT0272 THE VALUE OF CLINICAL AND LABORATORY FEATURES TO PREDICT EXTENT OF LARGE VESSEL VASCULITIS ON PET CT
Authors: G. Reynolds, C. Holland, G. Petrides, A. Lorenzi, B. Thompson, J. Heaney, T. Ali
Journal: Annals of the Rheumatic Diseases (2020)

Background: Giant cell arteritis (GCA) is an idiopathic vasculitis affecting large and medium-sized vessels. The pattern of arterial involvement is heterogeneous with two overlapping categories recognised: classical cranial GCA and extra-cranial GCA (or large vessel vasculitis – LVV) that predominantly affects the aorta and its proximal branches. Although LVV is present in around 80% of patients with cranial GCA, and around one third will develop large vessel complications, there are no guidelines for which patients should be screened for it (1). We sought to investigate whether clinical and laboratory features were a useful guide to the severity of LVV on FDG PET-CT. Objectives: To retrospectively analyse whether baseline patient characteristics are able to predict the extent of large vessel vasculitis on PET-CT. Methods: Clinical data for 65 patients referred for a PET-CT scan by Rheumatology at the Freeman Hospital, Newcastle between January 2015 and May 2018 were retrospectively analysed. The most recent full blood count and inflammatory markers prior to the scan were used. Scans were reviewed by a consultant radiologist and trainee. The arterial network was split in to ten potentially involved territories (aortic arch, thoracic aorta, abdominal aorta, iliac vessels, axillary, brachiocephalic, subclavian, carotid, vertebral and femoral arteries. Both the value of highest standardised uptake value (SUV max) and the territory affected was recorded for each positive scan. Results: In the period analysed 65 PET-CT scans were requested, mostly (77%) as baseline investigations for symptoms with LVV in the differential diagnosis. Of these 22 (34%) were positive for LVV and in that group the majority of patients (64%) were female. In those with a negative scan, 47.5% were on concurrent steroid treatment compared to 9% with a positive scan. Regression analysis suggested that the number of systemic features (weight loss, pyrexia, polymyalgia) was weakly correlated with the number of affected territories (p=0.04). In contrast there was no correlation between laboratory tests ((CRP (p=0.91), ESR (p=0.46), Hb (p=0.44), platelets (p=0.74)) and the number of territories affected. The aortic arch (47%) was most commonly the territory with the highest degree of FDG uptake (SUV max) followed by the abdominal aorta (21%) and thoracic (10%) and femoral arteries (10%). There was no correlation between SUV max and laboratory tests ((CRP (p=0.55), ESR (p=0.89), Hb (p=0.82), platelets (p=0.17)) or the number of systemic features (p=0.7). There was no significant difference in the number of territories affected between those on steroid treatment at the time of the scan and steroid-naïve patients, albeit the number of positive scans in those on steroid treatment was low (n=5). Conclusion: These results suggest that clinical and laboratory features are a poor guide to predicting the maximal severity and extent of disease on FDG PET-CT. References: [ 1]Koster MJ, Matteson EL, Warrington KJ. Large-vessel giant cell arteritis: diagnosis, monitoring and management. Rheumatology (Oxford). 2018;57(suppl_2):ii32-ii42. Disclosure of Interests: None declared