Brain Tissue Motion Research Articles

A brief history of the development of transcranial tissue Doppler ultrasound.

This article documents the early development of the first transcranial Doppler (TCD)-based ultrasound system for continuous monitoring of brain tissue pulsations (BTPs). Transcranial tissue Doppler (TCTD) uses a lightweight, wearable single-element ultrasound probe to track tissue motion perpendicular to the skin's surface, providing tissue displacement estimates along a single beam line. Feasibility tests using an adapted TCD system confirmed that brain tissue motion data can be obtained from existing TCD hardware. Brain Tissue Velocimetry (Brain TV), a TCTD data acquisition system, was then developed to provide a lightweight and portable means of continuously recording TCTD data in real-time. Brain TV measurements are synchronized to a 3-lead electrocardiogram and can be recorded alongside other physiological measurements, such as blood pressure, heart rate and end-tidal carbon dioxide. We have shown that Brain TV is able to record BTPs from sample depths ranging from 22 to 80 mm below the probe's surface and from multiple positions on the head. Studies in healthy volunteers, stroke patients and ultrasound phantom brain models demonstrate how TCTD might provide insights into the relationships between physiological measurements and brain tissue motion and show promise for rapid clinical assessment and continuous monitoring of BTPs.

3D Quantitative-Amplified Magnetic Resonance Imaging (3D q-aMRI).

Amplified MRI (aMRI) is a promising new technique that can visualize pulsatile brain tissue motion by amplifying sub-voxel motion in cine MRI data, but it lacks the ability to quantify the sub-voxel motion field in physical units. Here, we introduce a novel post-processing algorithm called 3D quantitative amplified MRI (3D q-aMRI). This algorithm enables the visualization and quantification of pulsatile brain motion. 3D q-aMRI was validated and optimized on a 3D digital phantom and was applied in vivo on healthy volunteers for its ability to accurately measure brain parenchyma and CSF voxel displacement. Simulation results show that 3D q-aMRI can accurately quantify sub-voxel motions in the order of 0.01 of a voxel size. The algorithm hyperparameters were optimized and tested on in vivo data. The repeatability and reproducibility of 3D q-aMRI were shown on six healthy volunteers. The voxel displacement field extracted by 3D q-aMRI is highly correlated with the displacement measurements estimated by phase contrast (PC) MRI. In addition, the voxel displacement profile through the cerebral aqueduct resembled the CSF flow profile reported in previous literature. Differences in brain motion was observed in patients with dementia compared with age-matched healthy controls. In summary, 3D q-aMRI is a promising new technique that can both visualize and quantify pulsatile brain motion. Its ability to accurately quantify sub-voxel motion in physical units holds potential for the assessment of pulsatile brain motion as well as the indirect assessment of CSF homeostasis. While further research is warranted, 3D q-aMRI may provide important diagnostic information for neurological disorders such as Alzheimer's disease.

Dynamic Ultrasound Localization Microscopy Without ECG-Gating

ObjectiveDynamic Ultrasound Localization Microscopy (DULM) has first been developed for non-invasive Pulsatility measurements in the rodent brain. DULM relies on the localization and tracking of microbubbles (MBs) injected into the bloodstream, to obtain highly resolved velocity and density cine-loops. Previous DULM techniques required ECG-gating, limiting its application to specific datasets, and increasing acquisition time. The objective of this study is to eliminate the need for ECG-gating in DULM experiments by introducing a motion-matching method for time registration. MethodsWe developed a motion-matching algorithm based on tissue Doppler that leverages the cyclic tissue motion within the brain. Tissue Doppler was estimated for each group of frames in the acquisitions, at multiple locations identified as local maxima in the skin above the skull. Subsequently, each group of frames was time-registered to a reference group by delaying it based on the maximum correlation value between their respective tissue Doppler signals. This synchronization ensured that each group of frames aligned with the brain tissue motion of the reference group, and consequently, with its cardiac cycle. As a result, velocities of MBs could be averaged to retrieve flow velocity variations over time. ResultsInitially validated in ECG-gated acquisitions in a rat model (n = 1), the proposed method was successfully applied in a mice model in 2D (n = 3) and in a feline model in 3D (n = 1). Performing time-registration with the proposed motion-matching method or by using ECG-gating leads to similar results. For the first time, dynamic velocity and density cine-loops were extracted without the need for any information on the animal ECG, and complex dynamic markers such as the Pulsatility index were estimated. ConclusionResults suggest that DULM can be performed without external gating, enabling the use of DULM on any ULM dataset where enough MBs are detectable. Time registration by motion-matching represents a significant advancement in DULM techniques, making DULM more accessible by simplifying its experimental complexity.

Association between resistance to cerebrospinal fluid flow and cardiac-induced brain tissue motion for Chiari malformation type I.

Chiari malformation type I (CMI) patients have been independently shown to have both increased resistance to cerebrospinal fluid (CSF) flow in the cervical spinal canal and greater cardiac-induced neural tissue motion compared to healthy controls. The goal of this paper is to determine if a relationship exists between CSF flow resistance and brain tissue motion in CMI subjects. Computational fluid dynamics (CFD) techniques were employed to compute integrated longitudinal impedance (ILI) as a measure of unsteady resistance to CSF flow in the cervical spinal canal in thirty-two CMI subjects and eighteen healthy controls. Neural tissue motion during the cardiac cycle was assessed using displacement encoding with stimulated echoes (DENSE) magnetic resonance imaging (MRI) technique. The results demonstrate a positive correlation between resistance to CSF flow and the maximum displacement of the cerebellum for CMI subjects (r = 0.75, p = 6.77 × 10-10) but not for healthy controls. No correlation was found between CSF flow resistance and maximum displacement in the brainstem for CMI or healthy subjects. The magnitude of resistance to CSF flow and maximum cardiac-induced brain tissue motion were not statistically different for CMI subjects with and without the presence of five CMI symptoms: imbalance, vertigo, swallowing difficulties, nausea or vomiting, and hoarseness. This study establishes a relationship between CSF flow resistance in the cervical spinal canal and cardiac-induced brain tissue motion in the cerebellum for CMI subjects. Further research is necessary to understand the importance of resistance and brain tissue motion in the symptomatology of CMI.

3D amplified MRI (aMRI).

PurposeAmplified MRI (aMRI) has been introduced as a new method of detecting and visualizing pulsatile brain motion in 2D. Here, we improve aMRI by introducing a novel 3D aMRI approach.Methods3D aMRI was developed and tested for its ability to amplify sub‐voxel motion in all three directions. In addition, 3D aMRI was qualitatively compared to 2D aMRI on multi‐slice and 3D (volumetric) balanced steady‐state free precession cine data and phase contrast (PC‐MRI) acquired on healthy volunteers at 3T. Optical flow maps and 4D animations were produced from volumetric 3D aMRI data.Results3D aMRI exhibits better image quality and fewer motion artifacts compared to 2D aMRI. The tissue motion was seen to match that of PC‐MRI, with the predominant brain tissue displacement occurring in the cranial‐caudal direction. Optical flow maps capture the brain tissue motion and display the physical change in shape of the ventricles by the relative movement of the surrounding tissues. The 4D animations show the complete brain tissue and cerebrospinal fluid (CSF) motion, helping to highlight the “piston‐like” motion of the ventricles.ConclusionsHere, we introduce a novel 3D aMRI approach that enables one to visualize amplified cardiac‐ and CSF‐induced brain motion in striking detail. 3D aMRI captures brain motion with better image quality than 2D aMRI and supports a larger amplification factor. The optical flow maps and 4D animations of 3D aMRI may open up exciting applications for neurological diseases that affect the biomechanics of the brain and brain fluids.

Diagnostic Ability of Radiofrequency Ultrasound in Parkinson's Disease Compared to Conventional Transcranial Sonography and Magnetic Resonance Imaging.

We aimed to estimate tissue displacements’ parameters in midbrain using ultrasound radiofrequency (RF) signals and to compare diagnostic ability of this RF transcranial sonography (TCS)-based dynamic features of disease affected tissues with conventional TCS (cTCS) and magnetic resonance imaging (MRI) while differentiating patients with Parkinson’s disease (PD) from healthy controls (HC). US tissue displacement waveform parametrization by RF TCS for endogenous brain tissue motion, standard neurological examination, cTCS and MRI data collection were performed for 20 PD patients and for 20 age- and sex-matched HC in a prospective manner. Three logistic regression models were constructed, and receiver operating characteristic (ROC) curve analyses were applied. The model constructed of RF TCS-based brain tissue displacement parameters—frequency of high-end spectra peak and root mean square—revealed presumably increased anisotropy in the midbrain and demonstrated rather good diagnostic ability in the PD evaluation, although it was not superior to that of the cTCS or MRI. Future studies are needed in order to establish the true place of RF TCS detected tissue displacement parameters for the evaluation of pathologically affected brain tissue.

Ultrasonic Assessment of the Medial Temporal Lobe Tissue Displacements in Alzheimer's Disease.

We aim to estimate brain tissue displacements in the medial temporal lobe (MTL) using backscattered ultrasound radiofrequency (US RF) signals, and to assess the diagnostic ability of brain tissue displacement parameters for the differentiation of patients with Alzheimer’s disease (AD) from healthy controls (HC). Standard neuropsychological evaluation and transcranial sonography (TCS) for endogenous brain tissue motion data collection are performed for 20 patients with AD and for 20 age- and sex-matched HC in a prospective manner. Essential modifications of our previous method in US waveform parametrization, raising the confidence of micrometer-range displacement signals in the presence of noise, are done. Four logistic regression models are constructed, and receiver operating characteristic (ROC) curve analyses are applied. All models have cut-offs from 61.0 to 68.5% and separate AD patients from HC with a sensitivity of 89.5% and a specificity of 100%. The area under a ROC curve of predicted probability in all models is excellent (from 95.2 to 95.7%). According to our models, AD patients can be differentiated from HC by a sharper morphology of some individual MTL spatial point displacements (i.e., by spreading the spectrum of displacements to the high-end frequencies with higher variability across spatial points within a region), by lower displacement amplitude differences between adjacent spatial points (i.e., lower strain), and by a higher interaction of these attributes.

Ultrasound measurement of brain tissue movement in humans: A systematic review.

It has long been suggested that ultrasound could be used to measure brain tissue pulsations in humans, but potential clinical applications are relatively unexplored. The aim of this systematic review was to explore and synthesise available literature on ultrasound measurement of brain tissue motion in humans. Our systematic review was designed to include predefined study selection criteria, quality evaluation, and a data extraction pro-forma, registered prospectively on PROSPERO (CRD42018114117). The systematic review was conducted by two independent reviewers. Ten studies were eligible for the evidence synthesis and qualitative evaluation. All eligible studies confirmed that brain tissue motion over the cardiac cycle could be measured using ultrasound; however, data acquisition, analysis, and outcomes varied. The majority of studies used tissue pulsatility imaging, with the right temporal window as the acquisition point. Currently available literature is largely exploratory, with measurements of brain tissue displacement over a narrow range of health conditions and ages. Explored health conditions include orthostatic hypotension and depression. Further studies are needed to assess variability in brain tissue motion estimates across larger cohorts of healthy subjects and in patients with various medical conditions. This would be important for informing sample size estimates to ensure future studies are appropriately powered. Future research would also benefit from a consistent framework for data analysis and reporting, to facilitate comparative research and meta-analysis. Following standardisation and further healthy participant studies, future work should focus on assessing the clinical utility of brain tissue pulsation measurements in cerebrovascular disease states.

Quantifying cardiac-induced brain tissue expansion using DENSE.

Brain tissue undergoes viscoelastic deformation and volumetric strain as it expands over the cardiac cycle due to blood volume changes within the underlying microvasculature. Volumetric strain measurements may therefore provide insights into small vessel function and tissue viscoelastic properties. Displacement encoding via stimulated echoes (DENSE) is an MRI technique that can quantify the submillimetre displacements associated with brain tissue motion. Despite previous studies reporting brain tissue displacements using DENSE and other MRI techniques, a complete picture of brain tissue volumetric strain over the cardiac cycle has not yet been obtained. To address this need we implemented 3D cine‐DENSE at 7 T and 3 T to investigate the feasibility of measuring cardiac‐induced volumetric strain as a marker for small vessel blood volume changes. Volumetric strain over the entire cardiac cycle was computed for the whole brain and for grey and white matter tissue separately in six healthy human subjects. Signal‐to‐noise ratio (SNR) measurements were used to determine the voxel‐wise volumetric strain noise. Mean peak whole brain volumetric strain at 7 T (mean ± SD) was (4.5 ± 1.0) × 10−4 (corresponding to a volume expansion of 0.48 ± 0.1 mL), which is in agreement with literature values for cerebrospinal fluid that is displaced into the spinal canal to maintain a stable intracranial pressure. The peak volumetric strain ratio of grey to white matter was 4.4 ± 2.8, reflecting blood volume and tissue stiffness differences between these tissue types. The mean peak volumetric strains of grey and white matter tissue were found to be significantly different (p < 0.001). The mean SNR at 7 T and 3 T of the DENSE measurements was 22.0 ± 7.3 and 7.0 ± 2.8 respectively, which currently limits a voxel‐wise strain analysis at both field strengths. We demonstrate that tissue specific quantification of volumetric strain is feasible with DENSE. This metric holds potential for studying blood volume pulsations in the ageing brain in healthy and diseased states.

Regional Quantification of Brain Tissue Strain Using Displacement-Encoding With Stimulated Echoes Magnetic Resonance Imaging.

Intrinsic cardiac-induced deformation of brain tissue is thought to be important in the pathophysiology of various neurological disorders. In this study, we evaluated the feasibility of utilizing displacement encoding with stimulated echoes (DENSE) magnetic resonance imaging (MRI) to quantify two-dimensional (2D) neural tissue strain using cardiac-driven brain pulsations. We examined eight adult healthy volunteers with an electrocardiogram-gated spiral DENSE sequence performed at the midsagittal plane on a 3 Tesla MRI scanner. Displacement, pixel-wise trajectories, and principal strains were determined in seven regions of interest (ROI): the brain stem, cerebellum, corpus callosum, and four cerebral lobes. Quantification of small neural tissue motion and strain along with their spatial and temporal variations in different brain regions was found to be feasible using DENSE. The medial and inferior brain structures (brain stem, cerebellum, and corpus callosum) had significantly larger motion and strain compared to structures located more peripherally. The brain stem had the largest peak mean displacement (PMD) (187 ± 50 μm, mean ± SD). The largest mean principal strains in compression and extension were observed in the brain stem (0.38 ± 0.08%) and the corpus callosum (0.37 ± 0.08%), respectively. Measured values in percent strain were altered by as much as 0.1 between repeated scans. This study showed that DENSE can quantify regional variations in brain tissue motion and strain and has the potential to be utilized as a tool to evaluate the changes in brain tissue dynamics resulting from alterations in biomechanical stresses and tissue properties.

Abstracts from The 35th Annual National Neurotrauma Symposium July 7-12, 2017 Snowbird, Utah.

Abstracts from The 35th Annual National Neurotrauma Symposium July 7-12, 2017 Snowbird, Utah.

Measurement of brain tissue motion using extended autocorrelation strain estimator

Pulsatile motion of brain parenchyma results from cardiac and breathing cycles. In this study, transient motion of brain tissue was estimated using an Aixplorer\textregistered imaging system allowing an ultrafast 2D acquisition mode. The strain was computed directly from the ultrafast IQ complex data using the extended autocorrelation strain estimator (EASE), which provides great SNRs regardless of depth. The EASE first evaluates the autocorrelation function at each depth over a set of successive IQ pairs. This estimates the mean change in phase over time, which is proportional to the velocity. A second autocorrelation is evaluated on the results of the first autocorrelation. This estimates the mean change in phase over depth, which is proportional to the strain rate. The developed algorithm was first validated on “in vivo” data acquired at 7.5MHz from the carotid. Tissue velocity and strain rate were estimated on artery wall and adjacent regions. The estimated displacement velocity and displacement of the wall artery were 2.5 cm/s, and 150 μm respectively. The displacement velocity and displacement of the region near the surface were 1 cm/s and 30 μm respectively.

Elderly depression diagnostic of diabetic patients by brain tissue pulsatility imaging

Pulsatile motion of brain parenchyma results from cardiac and breathing cycles and consists in a rapid displacement in systole, with slow diastolic recovery. Based on the vascular depression concept and recent studies where a correlation was found between cerebral haemodynamics and depression in the elderly, we emitted the hypothesis that tissue brain motion due to perfusion is correlated to elderly depression associated with cardiovascular risk factors. Tissue Pulsatlity Imaging (TPI) is a new ultrasound technique developed firstly at the University of Washington to assess the brain tissue motion. We used TPI technique to measure the brain displacement of two groups of elderly patients with diabetes as a vascular risk factor. The first group is composed of 11 depressed diabetic patients. The second group is composed of 12 diabetic patients without depressive symptoms. Transcranial acquisitions were performed with a 1.8 MHz ultrasound phased array probe through the right temporal bone window. The acquisition of six cardiac cycles was realized on each patient with a frame rate of 23 frames/s. Displacements estimation was performed by off-line analysis. A significant decrease in brain pulsatility was observed in the group of depressed patients compared to the group of non depressed patients. Mean displacement magnitude was about 44±7 μm in the first group and 68±13 μm in the second group.