Why ULM has not yet been integrated in clinical practice?

Ultrasound Localization Microscopy (ULM) has emerged as a promising ultrasound-based technique to characterize microvascular structures, due to its ability to overcome the ultrasound diffraction limit. The enhanced resolution capability is a consequence of precise localizations of microbubbles (MBs) injected in the circulatory system. These localizations can be used to track MBs over time to obtain not only geometrical, but also dynamic information of microvascular flow. ULM combines its ability to achieve a micrometric resolution with the advantages of ultrasound (i.e. low-cost, non-ionizing, portability). Thus, the technique might represent an indispensable clinical tool for understanding various diseases, such as cancer and stroke, which are known to be associated with changes in vascular structures. However, ULM clinical translation is hindered by various requirements, including high frame rates (FR), low MB concentrations, leading to prolonged acquisition times, and lack of validation methods. This thesis addresses these challenges by showing how to reduce the FRs of a factor 10 and reduce the acquisition times to 1/4 while maintaining similarity with original ULM-generated images. Furthermore, the thesis addresses the constraint of low concentrations by introducing a bi-disperse MB population. The uncoupling of this population, characterized by a couple of monodisperse MBs populations, allows to increase MB concentrations, and, potentially decreasing the acquisition times. Finally, we demonstrate the feasibility of 3D printing vascular phantoms for ULM image generation. With the goal of bridging the gap between various critical ULM trade-offs and clinical practice, this research is presented.