Imagine being able to study the human brain in real-world scenarios while the subject displays natural behaviors such as locomotion, social interaction, or spatial navigation. The advent of ultrafast ultrasound imaging brings us closer to this goal with functional ultrasound imaging (fUSi), a mobile neuroimaging technique. Here, we present real-time fUSi monitoring of brain activity during walking in a subject with a clinically approved sonolucent skull implant. Our approach uses personalized 3D-printed fUSi helmets for stability, optical tracking for cross-modal validation with functional magnetic resonance imaging, advanced signal processing to estimate hemodynamic responses, and facial tracking of a lick licking paradigm. These combined efforts allowed us to show consistent fUSi signals over 20 months, even during high motion activities such as walking. These results demonstrate the feasibility of fUSi for monitoring brain activity in real-world contexts, marking an important milestone for fUSi-based insights in clinical and neuroscientific research.

Ultrasonography could allow operator-independent examination and continuous monitoring of the carotid artery (CA) but normally requires complex and expensive transducers, especially for 3-D. By employing computational ultrasound imaging (cUSi), using an aberration mask and model-based reconstruction, a monitoring device could be constructed with a more affordable simple transducer design comprising only a few elements. We aim to apply the cUSi concept to create a CA monitoring system. The system’s possible configurations for the 2-D imaging case were explored using a linear array setup emulating a cUSi device in silico, followed by in vitro testing and in vivo CA imaging. Our study shows enhanced reconstruction performance with the use of an aberrating mask, improved lateral resolution through proper choice of the mask delay variation, and more accurate reconstructions using least-squares with QR (LSQR) decomposition compared to matched filtering (MF). Together, these advancements enable B-mode reconstruction and power Doppler imaging (PDI) of the CA with sufficient quality for monitoring using a configuration of 12 transceivers coupled with a random aberration mask with a maximum delay variation of four wave periods (WPs).

Four-dimensional ultrasound imaging of complex biological systems such as the brain is technically challenging because of the spatiotemporal sampling requirements. We present computational ultrasound imaging (cUSi), an imaging method that uses complex ultrasound fields that can be generated with simple hardware and a physical wave prediction model to alleviate the sampling constraints. cUSi allows for high-resolution four-dimensional imaging of brain hemodynamics in awake and anesthetized mice.

Computational ultrasound imaging (cUSi) offers high-resolution 3D imaging with simpler hardware by relying on computational power. Central to cUSi is a large model matrix that stores all pulse-echo signals. For 3D imaging this matrix easily surpasses 1 terabyte, hindering in-memory storage and real-time processing. This paper presents a solution for cUSi through an aberrating layer by introducing a virtual array concept, which uses transfer functions to map data from the real to a virtual array, enabling the use of conventional reconstruction techniques like delay-and-sum (DAS). We demonstrate the mathematical similarity of this approach to using a full model matrix and validate it with promising imaging results.

It has been previously demonstrated that applying an aberrating mask for 2D compressive imaging using a low number of sensors (elements) can significantly improve image resolution, as evaluated via the point spread function. Here we investigate the potential to apply a similar approach for 3D flow monitoring. We conducted a 3D k-Wave simulation using a 5x5 sensor array coupled to a physical coding mask, performing B-mode and power Doppler imaging on a 3D carotid artery flow model. An approximately three times smaller lateral PSF was achieved at the cost of increased background clutter level and slightly increased axial PSF. A better definition of the vessel border and finer flow speckle were observed in power Doppler imaging. Our results suggest that 3D compressive imaging using a very low sensor count of 25 with spatial coding mask has the potential to monitor 3D carotid artery flow.

We intend to develop an ultrasound compressive imaging device to perform carotid artery (CA) function and flow monitoring/imaging by using just a few single element transducers equipped with spatial coding masks. The spatially unique impulse responses can be exploited in compressive reconstructions. To explore the potential of different configurations, in this study we emulated such a device using a linear array system. We combined its elements with individual digital delays into a small number of groups. The results suggest our spatial coding mask approach based on reconstructions regularized with a least squares method has potential for CA monitoring with only 10 to 12 sensors.