A distributed model of the human arterial tree including all main systemic arteries coupled to a heart model is developed. The one-dimensional (1-D) form of the momentum and continuity equations is solved numerically to obtain pressures and flows throughout the systemic arterial tree. Intimal shear is modeled using the Witzig-Womersley theory. A nonlinear viscoelastic constitutive law for the arterial wall is considered. The left ventricle is modeled using the varying elastance model. Distal vessels are terminated with three-element windkessels. Coronaries are modeled assuming a systolic flow impediment proportional to ventricular varying elastance. Arterial dimensions were taken from previous 1-D models and were extended to include a detailed description of cerebral vasculature. Elastic properties were taken from the literature. To validate model predictions, noninvasive measurements of pressure and flow were performed in young volunteers. Flow in large arteries was measured with MRI, cerebral flow with ultrasound Doppler, and pressure with tonometry. The resulting 1-D model is the most complete, because it encompasses all major segments of the arterial tree, accounts for ventricular-vascular interaction, and includes an improved description of shear stress and wall viscoelasticity. Model predictions at different arterial locations compared well with measured flow and pressure waves at the same anatomical points, reflecting the agreement in the general characteristics of the "generic 1-D model" and the "average subject" of our volunteer population. The study constitutes a first validation of the complete 1-D model using human pressure and flow data and supports the applicability of the 1-D model in the human circulation.

Abstract-The controversy as to whether Doppler ultrasonic methods should play a role in clinical decision-making in the prevention of stroke is attributable to reported disagreement between angiographic and ultrasonic results and the lack of internationally accepted ultrasound criteria for describing the degree of stenosis. Foremost among the explanations for both is the broad scatter of peak systolic velocities in the stenosis, the criterion that has so far received most attention. Grading based on a set of main and additional criteria can overcome diagnostic errors. Morphological measurements (B-mode images and color flow imaging) are the main criteria for low and moderate degrees of stenosis. Increased velocities in the stenosis indicate narrowing, but the appearance of collateral flow and decreased poststenotic flow velocity prove a high degree stenosis (Ն70%), additionally allowing the estimation of the hemodynamic effect in the category of high-degree stenosis. Additional criteria refer to the effect of a stenosis on prestenotic flow (common carotid artery), the extent of poststenotic flow disturbances, and derived velocity criteria (diastolic peak velocity and the carotid ratio). This multiparametric approach is intended to increase the reliability and the standard of reporting of ultrasonic results for arteriosclerotic disease of the carotid artery. Key Words: carotid stenosis Ⅲ degree of stenosis Ⅲ duplex sonography Ⅲ peak systolic velocity Ⅲ transcranial sonography Ⅲ ultrasound diagnosis

Changes in cerebral blood flow are associated with stroke, aneurysms, vascular cognitive impairment, neurodegenerative diseases and other pathologies. Brain angiograms, typically performed via computed tomography or magnetic resonance imaging, are limited to millimetre-scale resolution and are insensitive to blood-flow dynamics. Here, we show that ultrafast ultrasound localization microscopy of intravenously injected microbubbles enables transcranial imaging of deep vasculature in the adult human brain at microscopic resolution and the quantification of haemodynamic parameters. Adaptive speckle tracking to correct for micrometric brain-motion artefacts and for ultrasonic-wave aberrations induced during transcranial propagation allowed us to map the vascular network of tangled arteries, to functionally characterize blood-flow dynamics at a resolution of up to 25 μm, and to detect blood vortices in a small deep-seated aneurysm in a patient. Ultrafast ultrasound localization microscopy may facilitate the understanding of brain haemodynamics and of how vascular abnormalities in the brain are related to neurological pathologies.

The aim of this study is to develop and validate a patient-specific distributed model of the systemic arterial tree. This model is built using geometric and hemodynamic data measured on a specific person and validated with noninvasive measurements of flow and pressure on the same person, providing thus a patient-specific model and validation. The systemic arterial tree geometry was obtained from MR angiographic measurements. A nonlinear viscoelastic constitutive law for the arterial wall is considered. Arterial wall distensibility is based on literature data and adapted to match the wave propagation velocity of the main arteries of the specific subject, which were estimated by pressure waves traveling time. The intimal shear stress is modeled using the Witzig-Womersley theory. Blood pressure is measured using applanation tonometry and flow rate using transcranial ultrasound and phase-contrast-MRI. The model predicts pressure and flow waveforms in good qualitative and quantitative agreement with the in vivo measurements, in terms of wave shape and specific wave features. Comparison with a generic one-dimensional model shows that the patient-specific model better predicts pressure and flow at specific arterial sites. These results obtained let us conclude that a patientspecific one-dimensional model of the arterial tree is able to predict well pressure and flow waveforms in the main systemic circulation, whereas this is not always the case for a generic one-dimensional model. wave propagation; cerebral circulation; noninvasive measurements techniques; phase-contrast-magnetic resonance imaging; Doppler AT PRESENT, one-dimensional models are best suited to study flow and pressure waveforms along the whole or extensive parts of the systemic and pulmonary circulation. They can provide insight regarding wave propagation and reflection phenomena and allow for characterization of ventricular-arterial coupling. Because of their relatively low computational cost and complexity, one-dimensional models have been extensively used in the past to study different pathologies, such as hypertension by Westerhof et al. (30,31), arteriosclerosis by Raines et al. (22), stenoses by many authors (2,5,7,10,13,17,21,25,26,32), anatomical variations of cerebral arteries, arterial occlusion by Alastruey et al. (1), or to study surgery plans by Wan et al. (28). The main characteristics of previous one-dimensional models have been published in a previous article from our laboratory (23).The primary question addressed in this article was the validity of the generic one-dimensional model predictions. The approach we followed was to compare the predictions of the generic one-dimensional model with the average pressure and flow waveforms measured noninvasively in a group of healthy young individuals. The underlying hypothesis was that although the generic model would not represent precisely a specific individual it should represent reasonably well the average of the group. Hence, the model validation was strictly qualitative. Reymond et al. 2009...

Singular value decomposition of ultrafast imaging ultrasonic data sets has recently been shown to build a vector basis far more adapted to the discrimination of tissue and blood flow than the classical Fourier basis, improving by large factor clutter filtering and blood flow estimation. However, the question of optimally estimating the boundary between the tissue subspace and the blood flow subspace remained unanswered. Here, we introduce an efficient estimator for automatic thresholding of subspaces and compare it to an exhaustive list of thirteen estimators that could achieve this task based on the main characteristics of the singular components, namely the singular values, the temporal singular vectors, and the spatial singular vectors. The performance of those fourteen estimators was tested in vitro in a large set of controlled experimental conditions with different tissue motion and flow speeds on a phantom. The estimator based on the degree of resemblance of spatial singular vectors outperformed all others. Apart from solving the thresholding problem, the additional benefit with this estimator was its denoising capabilities, strongly increasing the contrast to noise ratio and lowering the noise floor by at least 5 dB. This confirms that, contrary to conventional clutter filtering techniques that are almost exclusively based on temporal characteristics, efficient clutter filtering of ultrafast Doppler imaging cannot overlook space. Finally, this estimator was applied in vivo on various organs (human brain, kidney, carotid, and thyroid) and showed efficient clutter filtering and noise suppression, improving largely the dynamic range of the obtained ultrafast power Doppler images.