Integrated near-infrared fluorescence imaging of vascular morphology and function using indocyanine green: A phantom-based validation study

Indocyanine green (ICG)-based near-infrared (NIR) fluorescence imaging is widely used for vascular morphology visualization but lacks functional information, such as blood flow velocity and perfusion. Here, we present a prototype NIR ICG imaging system combined with a quantitative framework to simultaneously measure vascular structure and function. The system, incorporating a 785 nm laser, high-sensitivity charge-coupled device camera, and motorized stage, was validated using tissue-mimicking phantoms with vessel diameters of 1 and 2 mm under physiological flow rates. Blood-mimicking fluids circulated via a peristaltic pump simulated realistic hemodynamics. Image processing employed adaptive histogram equalization, bilateral filtering, and Otsu's segmentation within a semi-automated workflow to extract vessel diameter, flow velocity, and perfusion rate with reduced user intervention. The relative errors were below 7% for diameter and flow velocity measurements. By integrating morphological and functional quantification into a unified framework, the proposed approach improves reproducibility over conventional manual ICG analysis. Laser irradiance remained within safe exposure limits. This quantitative and integrated imaging strategy demonstrates promising translational potential for intraoperative vascular assessment.