MRI visualization of Staphyloccocus aureus-induced infective endocarditis in mice

Infective endocarditis (IE) is a severe and often fatal disease, lacking a fast and reliable diagnostic procedure. The purpose of this study was to establish a mouse model of Staphylococcus aureus-induced IE and to develop a MRI technology to characterize and diagnose IE. To establish the mouse model of hematogenous IE, aortic valve damage was induced by placing a permanent catheter into right carotid artery. 24 h after surgery, mice were injected intravenously with either iron particle-labeled or unlabeled S. aureus (strain 6850). To distinguish the effect of IE from mere tissue injury or recruited macrophages, subgroups of mice received sham surgery prior to infection (n = 17), received surgery without infection (n = 8), or obtained additionally injection of free iron particles to label macrophages (n = 17). Cardiac MRI was performed 48 h after surgery using a self-gated ultra-short echo time (UTE) sequence (TR/TE, 5/0.31 ms; in-plane/slice, 0.125/1 mm; duration, 12:08 min) to obtain high-resolution, artifact-free cinematographic images of the valves. After MRI, valves were either homogenized and plated on blood agar plates for determination of bacterial titers, or sectioned and stained for histology. In the animal model, both severity of the disease and mortality increased with bacterial numbers. Infection with 105 S. aureus bacteria reliably caused endocarditis with vegetations on the valves. Cinematographic UTE MRI visualised the aortic valve over the cardiac cycle and allowed for detection of bacterial vegetations, while mere tissue trauma or labeled macrophages were not detected. Iron labeling of S. aureus was not required for detection. MRI results were consistent with histology and microbial assessment. These data showed that S. aureus-induced IE in mice can be detected by MRI. The established mouse model allows for investigation of the pathophysiology of IE, testing of novel drugs and may serve for the development of a clinical diagnostic strategy