Ultrasound Molecular Imaging of Inflammation in Mouse Abdominal Aorta

Abstract

Objectives: The aim of this study was to demonstrate a new clinically translatable ultrasound molecular imaging approach, modulated acoustic radiation force-based imaging, which is capable of rapid and reliable detection of inflammation as validated in mouse abdominal aorta.

Materials and methods: Animal studies were approved by the Institutional Animal Care and Use Committee at the University of Virginia. C57BL/6 mice stimulated with tumor necrosis factor α, or fed with a high-fat diet, were used as inflammation (MInflammation) and diet-induced obesity (DIO) (MDIO) models, respectively. C57BL/6 mice, not exposed to tumor necrosis factor α or DIO, were used as controls (MNormal). P-selectin-targeted (MBP-selectin), vascular cell adhesion molecule (VCAM)-1-targeted (MBVCAM-1), and isotype control (MBControl) microbubbles were synthesized by conjugating anti-P-selectin, anti-VCAM-1, and isotype control antibodies to microbubbles, respectively. The abdominal aortas were imaged for 180 seconds during a constant infusion of microbubbles. A parameter, residual-to-saturation ratio (RSR), was used to assess P-selectin and VCAM-1. Statistical analysis was performed with the Student t test.

Results: For the inflammation model, RSR of the MInflammation + MBP-selectin group was significantly higher (40.9%, P < 0.0005) than other groups. For the DIO model, RSR of the MDIO + MBVCAM-1 group was significantly higher (60.0%, P < 0.0005) than other groups. Immunohistochemistry staining of the abdominal aorta confirmed the expression of P-selectin and VCAM-1.

Conclusions: A statistically significant assessment of P-selectin and VCAM-1 in mouse abdominal aorta was achieved. This technique yields progress toward rapid targeted molecular imaging in large blood vessels and thus has the potential for early diagnosis, treatment selection, and risk stratification of atherosclerosis.

Figure 1. The modulated ARF-based imaging

A, Schematic diagram illustrating the imaging sequence (top), microbubble dynamic behaviors (middle), and the signal intensity curve of adherent microbubbles and RSR (bottom). B, Mouse was placed in the prone position with the ultrasound transducer imaging the abdominal aorta. Microbubble infusion was administered via a tail vein catheter connected to a syringe pump. C, A sample B-mode image of the mouse abdominal aorta.

Figure 2. A depiction of data processing in the study

A, A stack of all B-mode image frames obtained using the modulated ARF pulse sequence showing the mouse abdominal aorta. Scale bars are applicable to all three sub-figures. B, The sum of all image frames. The green window (2 mm × 0.8 mm) shows a zoomed-in region on the bottom vessel wall used to establish the region of interest (ROI). The area within the green window with signal magnitude greater than approximately 20% of the maximum magnitude was defined as ROI (C). The signal intensity curve of bottom vessel wall was calculated by averaging signal intensities within the ROI.

Figure 3. Example signal intensity curve and corresponding ultrasound images for targeted group

A, Signal intensity curve for one trial from the group of M_Inflammation + MB_P-selectin. ARF was applied from 10 s to 100 s. B to K, Corresponding B-mode images overlaid with color-coded microbubble signal along the bottom vessel wall at different time points.

Figure 4. Example signal intensity curve and corresponding ultrasound images for control group

A, Signal intensity curve for one trial from the group of M_Normal + MB_Control. ARF was applied from 10 s to 100 s. B to K, Corresponding B-mode images overlaid with color-coded microbubble signal along the bottom vessel wall at different time points.

Figure 5. Signal intensity curves and RSRs for inflammation model

Signal intensity curves for the groups of: M_Normal + MB_Control (A), M_Inflammation + MB_Control (B), M_Normal + MB_P-selectin (C), and M_Inflammation + MB_P-selectin (D). Solid lines indicate the mean and dotted lines indicate the error bars (mean ± standard deviation). E, RSR for all groups. RSR for the group of M_Inflammation + MB_P-selectin was significantly higher than that of other groups (p < 0.0005).

Figure 6. Signal intensity curves and RSRs for DIO model

Signal intensity curves for the groups of: M_Normal + MB_Control (A), M_DIO + MB_Control (B), M_Normal + MB_VCAM-1 (C), and M_DIO + MB_VCAM-1 (D). Solid lines indicate the mean and dotted lines indicate the error bars (mean ± standard deviation). E, RSR for all groups. RSR for the group of M_DIO + MB_VCAM-1 was significantly higher than that of other groups (p < 0.0005).

Figure 7. Immunohistochemistry staining of the abdominal aorta

P-selectin staining of M_Normal (A) and M_Inflammaiton (B). VCAM-1 staining of M_Normal (C) and M_DIO (D). Scale bar = 150 μm.