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A non-invasive method for estimating 2-D pressure gradients from ultrasound vector velocity data is presented. The method relies on in-plane vector velocity fields acquired using the Transverse Oscillation method. The pressure gradients are estimated by applying the Navier-Stokes equations for isotropic fluids to the estimated velocity fields. The velocity fields were measured for a steady flow on a carotid bifurcation phantom (Shelley Medical, Canada) with a 70% constriction on the internal branch. Scanning was performed with a BK8670 linear transducer (BK Medical, Denmark) connected to a BK Medical 2202 UltraView Pro Focus scanner. The results are validated through finite element simulations of the carotid flow model where the geometry is determined from MR images. This proof of concept study was conducted at nine ultrasound frames per second. Estimated pressure gradients along the longitudinal direction of the constriction varied from 0 kPa/m to 10 kPa/m with a normalized bias of -9.1% for the axial component and -7.9% for the lateral component. The relative standard deviation of the estimator, given in reference to the peak gradient, was 28.4% in the axial direction and 64.5% in the lateral direction. A study made across the constriction was also conducted. This yielded magnitudes from 0 kPa/m to 7 kPa/m with a normalized bias of -5.7% and 13.9% for the axial and lateral component, respectively. The relative standard deviations of this study were 45.2% and 83.2% in the axial and lateral direction, respectively.

This paper demonstrates how pressure gradients in a pulsatile flow environment can be measured non-invasively using ultrasound. The proposed method relies on vector velocity fields acquired from ultrasound data. 2-D flow data are acquired at 18-23 frames/sec using the Transverse Oscillation approach. Pressure gradients are calculated from the measured velocity fields using the Navier-Stokes equation. Velocity fields are measured during constant and pulsating flow on a carotid bifurcation phantom and on a common carotid artery in-vivo. Scanning is performed with a 5 MHz BK8670 linear transducer using a BK Medical 2202 UltraView Pro Focus scanner. The calculated pressure gradients are validated through a finite element simulation of the constant flow model. The geometry of the flow simulation model is reproduced using MRI data, thereby providing identical flow domains in measurement and simulation. The proposed method managed to estimate pressure gradients that varied from 0 kPa/m–7 kPa/m during constant flow and from 0 kPa/m–200 kPa/m in the pulsatile flow environments. The estimator showed, in comparison to the simulation model, a bias of -9% and -8% given in reference to the peak gradient for the axial and lateral gradient component, respectively.

This paper presents a model environment for construction of patient-specific computational fluid dynamic (CFD) models for the abdominal aorta (AA). Realistic pulsatile velocity waveforms are employed by using in vivo ultrasound blood flow measurements. Ultrasound is suitable for acquisition of blood velocity profiles, but these are influenced by noise, which will cause convergence problems in CFD simulations. Therefore, physiological smoothing of the velocity profiles is needed. This paper uses the Womersley-Evans model for physiological smoothing of measured blood velocity profiles in the AA. The geometry for the CFD simulation model was obtained by segmentation of MRI scans using a 3 Tesla scanner (Magnetom Trio, Siemens Healthcare, Erlangen, Germany). Spectral velocity data were obtained from a BK Medical ProFocus scanner using a research interface. All data were obtained from healthy volunteers. The estimated and smoothed velocity profiles were quantitatively compared. The energy contained in the velocity profile after smoothing is 65% larger relative to the noise contaminated estimated profiles. In conclusion, a model environment that produces realistic patient-specific CFD simulation models without convergence issues has been developed. The data processing for the model environment can be performed within six hours which is fast enough to be used in the clinical setting.

The abdominal aorta (AA) is predisposed to development of abdominal aneurysms (AAA), a focal dilatation of the artery with fatal consequences if left untreated. The blood flow patterns in the AA is thought to play an important role in the development of AAA. The purpose of this work is to investigate the blood flow pat- terns within a group of healthy volunteers (4 females, 7 males) aged 23 to 76 years to identify changes and differences related to age and gender. The healthy volunteers were categorized by gender (male/female) and age (below/above 35 years). Subject-specific flow and geometry data were acquired using the research interface on a medical ultrasound scanner and segmentation of 3D magnetic resonance angiography respectively. The largest average diameter was among the elderly males (19.7 (± 1.33) mm) and smallest among the young females (12.4 (± 0.605) mm). The highest peak systolic velocity was in the young female group (1.02 (± 0.336) m/s) and lowest in the elderly male group (0.836 (± 0.127) m/s). A geometrical change with age was observed as the AA becomes more bended with age. This also affects the blood flow velocity patterns, which are markedly different from young to elderly. Thus, changes in blood flow patterns in the AA related to age and gender is observed. Further investigations are needed to determine the relation between changes in blood flow patterns and AAA development.