Integrating carotid Doppler, greyscale US, and aortic oscillometry to evaluate macroangiopathy in myositides: the MYOCARD cohort.

Abstract

To evaluate the combination of novel colour Doppler US (CDUS), greyscale US (GSUS), and oscillometric indices of macroangiopathy in patients with idiopathic inflammatory myopathies (IIM). Second, to explore the associations between these imaging markers and both patient-related and disease-related characteristics, as well as traditional cardiovascular (CV) risk factors. We conducted CDUS to evaluate arterial compliance markers, specifically the resistance (RI) and pulsatility (PI) indices, both in the common (CCA) and internal carotid arteries (ICA) of patients with IIM and healthy controls. Additionally, we performed GSUS examinations to measure carotid intima-media thickness (cIMT), identify plaques, and quantify cumulative carotid calcification surface. Oscillometric assessments determined aortic stiffness using carotid-femoral pulse wave velocity (cfPWV). We recruited 82 IIM patients and 88 healthy controls. Patients showed significantly higher cIMT (Padj = 0.032), CCA-RI (Padj = 0.015), CCA-PI (Padj = 0.013), ICA-RI (Padj = 0.012), and ICA-PI (Padj = 0.039), compared with controls. RI and PI of CCA and ICA were higher in patients with lower lung function vital capacity, respectively (all Ps < 0.05). cfPWV correlated positively with traditional CV risk factors including age (ρ = 0.546, P < 0.001), mean arterial pressure (ρ = 0.331, P = 0.003), diabetes (P = 0.007), and hyperlipidaemia (P = 0.032), and associated negatively with lung carbon monoxide (CO) diffusion (ρ = -0.329, P = 0.031). In one of the largest CV surrogate marker studies in IIM, patients exhibited increased carotid pulsatility, resistance, and atherosclerosis compared with controls. Lower lung function parameters predicted aortic stiffness and Doppler indices, suggesting a possible link between lung involvement and increased CV risk. Angiopathy markers may reveal significant vascular abnormalities in IIM patients, enhancing CV screening and risk classification.