194. A novel PET/MR score for assessment of disease activity in large vessel vasculitis
Creators: name: Dan Pugh1, 2
name: Patel2, Dilip
name: Basu3, Neil
name: Neeraj Dhaun1, 2
Publisher: name: Zenodo
Year: 2022
Subjects: Vasculitis
ANCA
Abstracts
Giant Cell Arthritis
MPA
GPA
EGPA
Takayasu
IgA vasculitis

description: <strong>Background: </strong>Monitoring disease activity in large vessel vasculitis (LVV) is challenging. Current imaging techniques do not reliably distinguish low-grade inflammation from atherosclerosis. Hybrid PET/MR provides structural and functional vascular imaging, and utilises ~20% of the radiation dose associated with PET/CT, allowing interval scanning.<sup>1</sup> We recently showed the potential utility of PET/MR for LVV disease monitoring. Novel scoring systems for disease quantification that incorporate both PET and MR metrics (as opposed to PET alone) are needed to optimise data extraction and clinical application. Here, we aimed to develop a PET/MR-specific disease activity assessment score for use in LVV. <strong>Methods: </strong>Patients aged ≥18 years with active LVV were recruited to this national, prospective, observational study. The study consisted of 2 visits ≥6 months apart; at each visit clinical evaluation was followed by <sup>18</sup>F-fluorodeoxyglucose (FDG) PET/MR scanning (Siemens 3T Biograph mMR). Clinician’s assessment of disease activity was used as the reference standard. For each of 12 arterial segments, we calculated PET (maximum standardised uptake value (SUV<sub>max</sub>), SUV<sub>mean</sub>, and target-to-background ratios (TBRs) based on comparison with venous bloodpool SUV), and MR metrics (mural thickness, T2 mural signal, and the presence of luminal abnormalities). Logistic regression modelling determined which metrics best predicted disease activity. These were then combined to form a weighted ‘Vasculitis Activity using MR PET (VAMP)’ score. <strong>Results: </strong>Thirty-nine PET/MR scans were performed in 24 patients with LVV (14 GCA, 6 TAK, 4 unspecified; mean age 61±15 years; 17 (71%) were female). 22 patients (56%) had active disease based on clinical assessment at time of scan. In univariate analyses, TBRs using SUV<sub>mean</sub> and T2 mural signal best predicted clinically active disease for PET and MR, respectively. Informed by multivariate analysis, VAMP score was calculated as shown in Figure 1. VAMP score was higher in active disease compared with inactive disease (3.7±3.0 <em>versus</em> 0.9±0.9; <em>P</em>=0.0008). ROC analysis demonstrated an AUC of 0.89 (<em>P</em>=&lt;0.0001) and suggested a cut-off of 0.985 (rounded up to 1) to distinguish active from inactive disease. Using this cut-off, VAMP score distinguished active from inactive disease with a sensitivity of 95% and specificity of 82%, outperforming the established (PET-only) PET Vasculitis Activity Score (PETVAS) (sensitivity 73%, specificity 76%). <strong>Conclusions:</strong> In our LVV cohort, a novel PET/MR-specific scoring system better distinguished active from inactive disease compared with established scoring systems. Validation in a large, independent cohort is now required. <strong>Disclosures: </strong>none <strong>Figure 1. VAMP score calculation equation</strong>