Evoked Component Analysis (ECA): Decomposing the Functional Ultrasound Signal with GLM-Regularization.

Analysis of functional neuroimaging data aims to unveil spatial and temporal patterns of interest. Existing analysis methods fall into two categories: fully data-driven approaches and those reliant on prior information, e.g. the stimulus time course. While using the stimulus signal directly can help identify the activated brain areas, it is known that the relationship between stimuli and the brain's response exhibits nonlinear and time-varying characteristics. As such, relying completely on the stimulus signal to describe the brain's temporal response leads to a restricted interpretation of the brain function. In this paper, we present a new technique called Evoked Component Analysis (ECA), which leverages prior information up to a defined extent. This is achieved by including the general linear model (GLM) design matrix as a regulatory term and estimating the factor matrices in both space and time through an alternating minimization approach. We apply ECA to 2D and swept-3D functional ultrasound (fUS) experiments conducted with mice. When decomposing 2D fUS data, we employ GLM regularization at various intensities to emphasize the role of prior information. Furthermore, we show that incorporating multiple hemodynamic response functions within the design matrix can provide valuable insights into region-specific characteristics of evoked activity. Finally, we use ECA to analyze swept-3D fUS data recorded from five mice engaged in two distinct visual tasks. Swept-3D fUS images the 3D brain sequentially using a moving probe, resulting in different slice acquisition time instants. We show that ECA can estimate factor matrices with a fine resolution at each slice acquisition time instant and yield higher t-statistics compared to GLM and correlation analysis for all subjects.

Patient-Specific Vascular Flow Phantom for MRI- and Doppler Ultrasound Imaging.

OBJECTIVE: Intraoperative Doppler ultrasound imaging of human brain vasculature is an emerging neuro-imaging modality that offers vascular brain mapping with unprecedented spatiotemporal resolution. At present, however, access to the human brain using Doppler Ultrasound is only possible in this intraoperative context, posing a significant challenge for validation of imaging techniques. This challenge necessitates the development of realistic flow phantoms outside of the neurosurgical operating room as external platforms for testing hardware and software. An ideal ultrasound flow phantom should provide reference-like values in standardized topologies such as a slanted pipe, and allow for measurements in structures closely resembling vascular morphology of actual patients. Additionally, the phantom should be compatible with other clinical cerebrovascular imaging modalities. To meet these criteria, we developed and validated a versatile, multimodal MRI- and ultrasound Doppler phantom. METHODS: Our approach incorporates the latest advancements in phantom research using tissue-mimicking material and 3D-printing with water-soluble resin to create wall-less patient-specific lumens, compatible for ultrasound and MRI. RESULTS: We successfully produced three distinct phantoms: a slanted pipe, a y-shape phantom representing a bifurcating vessel and an arteriovenous malformation (AVM) derived from clinical Digital Subtraction Angiography (DSA)-data of the brain. We present 3D ultrafast power Doppler imaging results from these phantoms, demonstrating their ability to mimic complex flow patterns as observed in the human brain. Furthermore, we showcase the compatibility of our phantom with Magnetic Resonance Imaging (MRI). CONCLUSION: We developed an MRI- and Doppler Ultrasound-compatible flow-phantom using customizable, water-soluble resin prints ranging from geometrical forms to patient-specific vasculature.

Four-dimensional computational ultrasound imaging of brain hemodynamics.

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.

Swept-3-D Ultrasound Imaging of the Mouse Brain Using a Continuously Moving 1-D-Array-Part II: Functional Imaging.

Functional ultrasound (fUS) using a 1-D-array transducer normally is insufficient to capture volumetric functional activity due to being restricted to imaging a single brain slice at a time. Typically, for volumetric fUS, functional recordings are repeated many times as the transducer is moved to a new location after each recording, resulting in a nonunique average mapping of the brain response and long scan times. Our objective was to perform volumetric 3-D fUS in an efficient and cost-effective manner. This was achieved by mounting a 1-D-array transducer to a high-precision motorized linear stage and continuously translating over the mouse brain in a sweeping manner. We show how the speed at which the 1-D-array is translated over the brain affects the sampling of the hemodynamic response (HR) during visual stimulation as well as the quality of the resulting power Doppler image (PDI). Functional activation maps were compared between stationary recordings, where only one functional slice is obtained for every recording, and our swept-3-D method, where volumetric fUS was achieved in a single functional recording. The results show that the activation maps obtained with our method closely resemble those obtained during a stationary recording for that same location, while our method is not restricted to functional imaging of a single slice. Lastly, a mouse brain subvolume of ~6 mm is scanned at a volume rate of 1.5 s per volume, with a functional PDI reconstructed every [Formula: see text], highlighting swept-3-D's potential for volumetric fUS. Our method provides an affordable alternative to volumetric fUS using 2-D-matrix transducers, with a high SNR due to using a fully sampled 1-D-array transducer, and without the need to repeat functional measurements for every 2-D slice, as is most often the case when using a 1-D-array. This places our swept-3-D method as a potentially valuable addition to conventional 2-D fUS, especially when investigating whole-brain functional connectivity, or when shorter recording durations are desired.

Swept-3-D Ultrasound Imaging of the Mouse Brain Using a Continuously Moving 1-D-Array-Part I: Doppler Imaging.

Volumetric 3-D Doppler ultrasound imaging can be used to investigate large scale blood dynamics outside of the limited view that conventional 2-D power Doppler images (PDIs) provide. To create 3-D PDIs, 2-D-matrix array transducers can be used to insonify a large volume for every transmission; however, these matrices suffer from low sensitivity, high complexity, and high cost. More typically, a 1-D-array transducer is used to scan a series of stationary 2-D PDIs, after which a 3-D volume is created by concatenating the 2-D PDIs in postprocessing, which results in long scan times due to repeated measurements. Our objective was to achieve volumetric 3-D Doppler ultrasound imaging with a high Doppler sensitivity, similar to that of a typical stationary recording using a 1-D-array transducer, while being more affordable than using 2-D-matrix arrays. We achieved this by mounting a 1-D-array transducer to a high-precision motorized linear stage and continuously translating over the mouse brain in a sweeping manner. For Part I of this article, we focused on creating the best vascular images by investigating how to best combine filtered beamformed ultrasound frames, which were not acquired at the same spatial locations, into PDIs. Part II focuses on the implications of sampling transient brain hemodynamics through functional ultrasound (fUS) while continuously translating over the mouse brain. In Part I, we show how the speed at which we sweep our 1-D-array transducer affects the Doppler spectrum in a flow phantom. In vivo recordings were performed on the mouse brain while varying the sweeping speed, showing how higher sweeping speeds negatively affect the PDI quality. A weighting vector is found to combine frames while continuously moving over the mouse brain, allowing us to create swept PDIs of similar sensitivity when compared with those obtained using a stationary 1-D-array while allowing a significantly higher 3-D Doppler volume rate and maintaining the benefits of having a low computational and monetary cost. We show that a vascular subvolume of 6 mm can be scanned in 2.5 s, with a PDI reconstructed every [Formula: see text], outperforming classical staged recording methods.

Case report: High-resolution, intra-operative µDoppler-imaging of spinal cord hemangioblastoma.

Surgical resection of spinal cord hemangioblastomas remains a challenging endeavor: the neurosurgeon's aim to reach total tumor resections directly endangers their aim to minimize post-operative neurological deficits. The currently available tools to guide the neurosurgeon's intra-operative decision-making consist mostly of pre-operative imaging techniques such as MRI or MRA, which cannot cater to intra-operative changes in field of view. For a while now, spinal cord surgeons have adopted ultrasound and its submodalities such as Doppler and CEUS as intra-operative techniques, given their many benefits such as real-time feedback, mobility and ease of use. However, for highly vascularized lesions such as hemangioblastomas, which contain up to capillary-level microvasculature, having access to higher-resolution intra-operative vascular imaging could potentially be highly beneficial. µDoppler-imaging is a new imaging modality especially fit for high-resolution hemodynamic imaging. Over the last decade, µDoppler-imaging has emerged as a high-resolution, contrast-free sonography-based technique which relies on High-Frame-Rate (HFR)-ultrasound and subsequent Doppler processing. In contrast to conventional millimeter-scale (Doppler) ultrasound, the µDoppler technique has a higher sensitivity to detect slow flow in the entire field-of-view which allows for unprecedented visualization of blood flow down to sub-millimeter resolution. In contrast to CEUS, µDoppler is able to image high-resolution details continuously, without being contrast bolus-dependent. Previously, our team has demonstrated the use of this technique in the context of functional brain mapping during awake brain tumor resections and surgical resections of cerebral arteriovenous malformations (AVM). However, the application of µDoppler-imaging in the context of the spinal cord has remained restricted to a handful of mostly pre-clinical animal studies. Here we describe the first application of µDoppler-imaging in the case of a patient with two thoracic spinal hemangioblastomas. We demonstrate how µDoppler is able to identify intra-operatively and with high-resolution, hemodynamic features of the lesion. In contrast to pre-operative MRA, µDoppler could identify intralesional vascular details, in real-time during the surgical procedure. Additionally, we show highly detailed post-resection images of physiological human spinal cord anatomy. Finally, we discuss the necessary future steps to push µDoppler to reach actual clinical maturity.

Deconvolution of the Functional Ultrasound Response in the Mouse Visual Pathway Using Block-Term Decomposition.

Functional ultrasound (fUS) indirectly measures brain activity by detecting changes in cerebral blood volume following neural activation. Conventional approaches model such functional neuroimaging data as the convolution between an impulse response, known as the hemodynamic response function (HRF), and a binarized representation of the input signal based on the stimulus onsets, the so-called experimental paradigm (EP). However, the EP may not characterize the whole complexity of the activity-inducing signals that evoke the hemodynamic changes. Furthermore, the HRF is known to vary across brain areas and stimuli. To achieve an adaptable framework that can capture such dynamics of the brain function, we model the multivariate fUS time-series as convolutive mixtures and apply block-term decomposition on a set of lagged fUS autocorrelation matrices, revealing both the region-specific HRFs and the source signals that induce the hemodynamic responses. We test our approach on two mouse-based fUS experiments. In the first experiment, we present a single type of visual stimulus to the mouse, and deconvolve the fUS signal measured within the mouse brain's lateral geniculate nucleus, superior colliculus and visual cortex. We show that the proposed method is able to recover back the time instants at which the stimulus was displayed, and we validate the estimated region-specific HRFs based on prior studies. In the second experiment, we alter the location of the visual stimulus displayed to the mouse, and aim at differentiating the various stimulus locations over time by identifying them as separate sources.

High-resolution micro-Doppler imaging during neurosurgical resection of an arteriovenous malformation: illustrative case.

OBJECTIVE: Given the high-risk nature of arteriovenous malformation (AVM) resections, accurate pre- and intraoperative imaging of the vascular morphology is a crucial component that may contribute to successful surgical results. Surprisingly, current gold standard imaging techniques for surgical guidance of AVM resections are mostly preoperative, lacking the necessary flexibility to cater to intraoperative changes. Micro-Doppler imaging is a unique high-resolution technique relying on high frame rate ultrasound and subsequent Doppler processing of microvascular hemodynamics. In this paper the authors report the first application of intraoperative, coregistered magnetic resonance/computed tomograpy, micro-Doppler imaging during the neurosurgical resection of an AVM in the parietal lobe. OBSERVATIONS: The authors applied intraoperative two-dimensional and three-dimensional (3D) micro-Doppler imaging during resection and were able to identify key anatomical features including draining veins, supplying arteries and microvasculature in the nidus itself. Compared to the corresponding preoperative 3D-digital subtraction angiography (DSA) image, the micro-Doppler images could delineate vascular structures and visualize hemodynamics with higher, submillimeter scale detail, even at significant depths (>5 cm). Additionally, micro-Doppler imaging revealed unique microvascular morphology of surrounding healthy vasculature. LESSONS: The authors conclude that micro-Doppler imaging in its current form has clear potential as an intraoperative counterpart to preoperative contrast-dependent DSA, and the microvascular details it provides could build new ground to further study cerebrovascular pathophysiology.