Dynamic vascular changes on long-term ultrasound monitoring predict relapse in large-vessel giant cell arteritis

Color duplex ultrasound (CDUS) is increasingly used to assess disease activity in large-vessel giant cell arteritis (LV-GCA), but its role in long-term monitoring and relapse prediction remains unclear. We aimed to evaluate dynamic changes in ultrasound findings during follow-up and their prognostic value for relapse. In this retrospective longitudinal study, 43 newly diagnosed LV-GCA patients from a fast-track clinic underwent serial color duplex ultrasound (CDUS) of temporal, axillary, subclavian, and carotid arteries during follow-up. Several semiquantitative ultrasound indices were assessed. The validated OMERACT GCA Ultrasonography Score (OGUS) included temporal and axillary arteries, while two extended indices, OGUS-10LV and OGUS-12LV, were specifically developed for this study to include subclavian and carotid arteries, respectively. Halo count indices (HC8, HC10, HC12) represented the number of arteries showing a halo sign. Patients were stratified by relapse status, and the predictive value of early ultrasound changes was tested using receiver operating characteristic (ROC) analysis. Relapse occurred in 26 of 43 patients (60.5%), within 24 months (mean 10.2 ± 5.7). Non-relapsing patients showed progressive OGUS indices reductions, with differences at 9 months for OGUS and 6 months for OGUS-10LV/12LV. Values < 1 from month 6 were consistently observed only in non-relapsing patients. HC normalization (no halo in any arteries) occurred earlier in non-relapsing patients (HC8: 18 vs. 24 months; HC10: 18 vs. 30; HC12: 36 vs. not reached). ROC analysis identified ΔOGUS-12LV ≤ 0.07 at 6 months as the optimal cutoff for predicting relapse at 12 months (AUC 0.944). OGUS and its extended variants demonstrate sensitivity to change and prognostic value in LV-GCA. Early dynamic changes predict relapse, while delayed HC normalization characterizes relapsing patients. These findings support imaging remission as a meaningful endpoint and CDUS as a biomarker for individualized monitoring.