Singular value decomposition of microbubbles echoes for skull aberration corrections in ultrasound localization microscopy

Objective.Non-invasive imaging of the brain vascular system is key for the understanding and monitoring of cerebral small vessel disease and neurological disorders. ultrasound localization microscopy (ULM) is emerging as a powerful modality for the cerebral angiographic and hemodynamic imaging up to the microscopic scale in preclinical and clinical settings. However, the skull bone induces aberrations during ultrasonic propagation leading to distortions and shadowed regions.Approach.Here, we introduce an aberration correction method for ULM data able to extract the phase aberration from the singular value decomposition (SVD) of signals backscattered by microbubbles (MBs). Without anya prioriknowledge, SVD processing extracts several correction time delays laws associated with different isoplanetic patches. To highlight the efficiency of this correction method, we first simulated the full ULM data pipeline numerically to characterize the impact of transcranial propagation on acoustic image reconstruction and then validated it onin vivorodent data. The simulation generates synthetic backscattered signals from a rat vasculature mimicking model using real ULM position and velocity data acquired on a trepanned rat and virtually aberrated by 'ground truth' aberrators.Main results.The correction algorithm correctly retrieves this virtual aberration law in simulation. Then, applied toin vivodata, it improves image quality and enhance the number of detected MB for ULM imaging by up to 15%.Significance.This simple and fast correction method may open the way for a more widespread use of transcranial ULM in rodents and could be further extended to humans.