A functional ultrasound brain GPS for automatic vascular-based neuronavigation

Abstract

Recent advances in ultrasound imaging triggered by transmission of ultrafast plane waves have rendered functional ultrasound (fUS) imaging a valuable neuroimaging modality capable of mapping cerebral vascular networks, but also for the indirect capture of neuronal activity with high sensitivity thanks to the neurovascular coupling. However, the expansion of fUS imaging is still limited by the difficulty to identify cerebral structures during experiments based solely on the Doppler images and the shape of the vessels. In order to tackle this challenge, this study introduces the vascular brain positioning system (BPS), a GPS of the brain. The BPS is a whole-brain neuronavigation system based on the on-the-fly automatic alignment of ultrafast ultrasensitive transcranial Power Doppler volumic images to common templates such as the Allen Mouse Brain Common Coordinates Framework. This method relies on the online registration of the complex cerebral vascular fingerprint of the studied animal to a pre-aligned reference vascular atlas, thus allowing rapid matching and identification of brain structures. We quantified the accuracy of the automatic registration using super-resolution vascular images obtained at the microscopic scale using Ultrasound Localization Microscopy and found a positioning error of 44 µm and 96 µm for intra-animal and inter-animal vascular registration, respectively. The proposed BPS approach outperforms the manual vascular landmark recognition performed by expert neuroscientists (inter-annotator errors of 215 µm and 259 µm). Using the online BPS approach coupled with the Allen Atlas, we demonstrated the capability of the system to position itself automatically over chosen anatomical structures and to obtain corresponding functional activation maps even in complex oblique planes. Finally, we show that the system can be used to acquire and estimate functional connectivity matrices automatically. The proposed functional ultrasound on-the-fly neuronavigation approach allows automatic brain navigation and could become a key asset to ensure standardized experiments and protocols for non-expert and expert researchers.

Large scale in vivo acquisition, segmentation, and 3D reconstruction of cortical vasculature using open-source functional ultrasound imaging platform

“…Moreover, the brain-wide skeleton could help improve the registration by providing a better fit with the reference atlas of the model investigated (Macé et al, 2018; Brunner et al, 2020, 2022; Takahashi et al, 2021) either by the means of vascular landmarks combined with automatic alignment approaches (Nouhoum et al, 2021) or markerless CNN-based deep learning classification (Lambert et al, 2022).…”

Functional ultrasound imaging of recent and remote memory recall in the associative fear neural network in mice

“…After animal fixation, scalp preparation and infusion, the scalp was covered with an isotonic coupling gel and the ultrasonic probe was lowered to 1 mm from the scalp for complete immersion into the gel. Probe position was calculated via the Iconeus Brain Positioning System [34] over an oblique plane that enabled imaging coverage of the majority of neuroanatomical regions of interest (ROIs) linked with fear networks (Fig. 2) [9,10].…”

“…Nonetheless, the capability to image animals during FC acquisition would open a new line of study and could shed light into the phenomenon of memory formation, an endeavor that would be logistically and technically very difficult with other imaging modalities. Also, we used a linear array ultrasonic probe with a dedicated global positioning system [34] to isolate a single cross-sectional imaging plane; volumetric coverage of the whole brain would allow empirical evaluation of a more distributed network. The development of matrix arrays will overcome this limitation, although they currently suffer a sacrifice in spatial resolution [66,67].…”

“…Temporal Power Doppler signal was extracted from ROIs defined via the Allen Mouse Brain Common Coordinate Framework (CCFv3) [35] individually aligned to each animal and imaging session (Fig. 2B) [34]. Power Doppler signal was processed using a similar method to [21,26,36], as follows.…”

A deep learning classification task for brain navigation during functional ultrasound imaging

“…This topic has been recently addressed in ref. 24 , who developed an automated ultrasound-based neuro-navigation system to roughly identify their position in the brain. In their approach, they couple online registration of the recorded micro-Doppler volume to a pre-registered reference volume acquired at the start of every experiment.…”