A Novel Spatial Correlation Analysis of Peripheral Hemodynamics in a Murine Model of Vascular Calcification Using NIRS Imaging

Abstract Vascular calcification (VC) is a major contributor to cardiovascular diseases (CVD) and progresses rapidly in patients with chronic kidney disease (CKD). Recently, we developed a low-cost, near-infrared spectroscopy (NIRS)-based imaging device (near-infrared optical scanner–NIROS) and used it to detect VC in the aortae via peripheral vascular imaging of the tail in mouse models. Our initial studies indicated distinct hemodynamic changes in the murine tail with and without the presence of VC. This study aims to assess the overall changes in peripheral hemodynamic flow patterns in mice with and without VC using NIROS. The tails of CKD mice with and without VC were imaged using NIROS to obtain the diffuse reflected signals, which were in turn used to calculate the spatiotemporal hemodynamic maps. Pearson’s correlation analysis was performed to obtain the flow correlation maps based on hemodynamic parameters and the NIR diffuse reflectance signals. Results demonstrated a significant decrease ( p -value < 0.05) in hemodynamic flow correlation in the VC group as compared to those without VC. In addition, the flow correlations obtained from both NIRS wavelengths, 682 nm and 826 nm, showed a distinct decrease in correlation ( p -value < 0.05), suggesting a disruption in the flow pattern once the mice developed VC. These results demonstrate the potential of peripheral flow correlation patterns using hemodynamic or NIRS diffuse reflectance signals as an indicator for aortic calcification detection. Future work will focus on correlating these peripheral hemodynamic changes, both peripheral and aortic VC, in a larger cohort of mice.