Ultrasound Localization Microscopy (ULM) has emerged as a promising technique for imaging microvascular networks at subwavelength resolution. However, its 3D translation in clinics for complex organs like the brain remains limited due to technological and experimental challenges, including probe design constraints, motions artifacts, and both acoustic attenuation and aberrations caused by the skull. In this study, we present a fast and versatile simulation framework for 3D ULM based on a realistic human brain vasculature model that includes small vessels down to the precapillary scale, along with its hemodynamics driven by conservation and Murray's law. This novel framework enables comparison of ultrasound probe configurations, ULM algorithm performance, and experimental parameters such as microbubble (MB) concentration, subpixel motion, and skull-induced aberrations in transcranial imaging conditions. To illustrate a range of case scenarios, three matrix array probes were evaluated including a matrix probe with large elements combined with diverging lenses. We evaluated localization accuracy, tracking performance, velocity distribution and the extent of the field of view. As expected, the simulations also highlighted the negative impact of high MB concentration and motions artifacts on detection performance, as well as the significant effect of skull-induced aberrations. The proposed framework provides a robust interface for developing, testing and optimizing 3D ULM systems, with potential applications extending to other organs and clinical scenarios.
Reydet et al. (2025) studied this question.