Ultrasonic 3-D Vector Flow Method for Quantitative In Vivo Peak Velocity and Flow Rate Estimation.

Current clinical ultrasound (US) systems are limited to show blood flow movement in either 1-D or 2-D. In this paper, a method for estimating 3-D vector velocities in a plane using the transverse oscillation method, a 32×32 element matrix array, and the experimental US scanner SARUS is presented. The aim of this paper is to estimate precise flow rates and peak velocities derived from 3-D vector flow estimates. The emission sequence provides 3-D vector flow estimates at up to 1.145 frames/s in a plane, and was used to estimate 3-D vector flow in a cross-sectional image plane. The method is validated in two phantom studies, where flow rates are measured in a flow-rig, providing a constant parabolic flow, and in a straight-vessel phantom ( ∅=8 mm) connected to a flow pump capable of generating time varying waveforms. Flow rates are estimated to be 82.1 ± 2.8 L/min in the flow-rig compared with the expected 79.8 L/min, and to 2.68 ± 0.04 mL/stroke in the pulsating environment compared with the expected 2.57 ± 0.08 mL/stroke. Flow rates estimated in the common carotid artery of a healthy volunteer are compared with magnetic resonance imaging (MRI) measured flow rates using a 1-D through-plane velocity sequence. Mean flow rates were 333 ± 31 mL/min for the presented method and 346 ± 2 mL/min for the MRI measurements.

Safety Assessment of Advanced Imaging Sequences I: Measurements.

A method for rapid measurement of intensities (I(spta)), mechanical index (MI), and probe surface temperature for any ultrasound scanning sequence is presented. It uses the scanner's sampling capability to give an accurate measurement of the whole imaging sequence for all emissions to yield the true distributions. The method is several orders of magnitude faster than approaches using an oscilloscope, and it also facilitates validating the emitted pressure field and the scanner's emission sequence software. It has been implemented using the experimental synthetic aperture real-time ultrasound system (SARUS) scanner and the Onda AIMS III intensity measurement system (Onda Corporation, Sunnyvale, CA, USA). Four different sequences have been measured: a fixed focus emission, a duplex sequence containing B-mode and flow emissions, a vector flow sequence with B-mode and flow emissions in 17 directions, and finally a SA duplex flow sequence. A BK8820e (BK Medical, Herlev, Denmark) convex array probe is used for the first three sequences and a BK8670 linear array probe for the SA sequence. The method is shown to give the same intensity values within 0.24% of the AIMS III Soniq 5.0 (Onda Corporation, Sunnyvale, CA, USA) commercial intensity measurement program. The approach can measure and store data for a full imaging sequence in 3.8-8.2 s per spatial position. Based on I(spta), MI, and probe surface temperature, the method gives the ability to determine whether a sequence is within U.S. FDA limits, or alternatively indicate how to scale it to be within limits.

Volume flow in arteriovenous fistulas using vector velocity ultrasound.

Volume flow in arteriovenous fistulas for hemodialysis was measured using the angle-independent ultrasound technique Vector Flow Imaging and compared with flow measurements using the ultrasound dilution technique during dialysis. Using an UltraView 800 ultrasound scanner (BK Medical, Herlev, Denmark) with a linear transducer, 20 arteriovenous fistulas were scanned directly on the most superficial part of the fistula just before dialysis. Vector Flow Imaging volume flow was estimated with two different approaches, using the maximum and the average flow velocities detected in the fistula. Flow was estimated to be 242 mL/min and 404 mL/min lower than the ultrasound dilution technique estimate, depending on the approach. The standard deviations of the two Vector Flow Imaging approaches were 175.9 mL/min and 164.8 mL/min compared with a standard deviation of 136.9 mL/min using the ultrasound dilution technique. The study supports that Vector Flow Imaging is applicable for volume flow measurements.

A transverse oscillation approach for estimation of three-dimensional velocity vectors, part I: concept and simulation study.

A method for 3-D velocity vector estimation using transverse oscillations is presented. The method employs a 2-D transducer and decouples the velocity estimation into three orthogonal components, which are estimated simultaneously and from the same data. The validity of the method is investigated by conducting simulations emulating a 32 × 32 matrix transducer. The results are evaluated using two performance metrics related to precision and accuracy. The study includes several parameters including 49 flow directions, the SNR, steering angle, and apodization types. The 49 flow directions cover the positive octant of the unit sphere. In terms of accuracy, the median bias is -2%. The precision of v(x) and v(y) depends on the flow angle ß and ranges from 5% to 31% relative to the peak velocity magnitude of 1 m/s. For comparison, the range is 0.4 to 2% for v(z). The parameter study also reveals, that the velocity estimation breaks down with an SNR between -6 and -3 dB. In terms of computational load, the estimation of the three velocity components requires 0.75 billion floating point operations per second (0.75 Gflops) for a realistic setup. This is well within the capability of modern scanners.

A transverse oscillation approach for estimation of three-dimensional velocity vectors, part II: experimental validation.

The 3-D transverse oscillation method is investigated by estimating 3-D velocities in an experimental flow-rig system. Measurements of the synthesized transverse oscillating fields are presented as well. The method employs a 2-D transducer; decouples the velocity estimation; and estimates the axial, transverse, and elevation velocity components simultaneously. Data are acquired using a research ultrasound scanner. The velocity measurements are conducted with steady flow in sixteen different directions. For a specific flow direction with [α, ß] = [45, 15]°, the mean estimated velocity vector at the center of the vessel is (v(x), v(y), v(z)) = (33.8, 34.5, 15.2) ± (4.6, 5.0, 0.6) cm/s where the expected velocity is (34.2, 34.2, 13.0) cm/s. The velocity magnitude is 50.6 ± 5.2 cm/s with a bias of 0.7 cm/s. The flow angles α and ß are estimated as 45.6 ± 4.9° and 17.6 ± 1.0°. Subsequently, the precision and accuracy are calculated over the entire velocity profiles. On average for all direction, the relative mean bias of the velocity magnitude is -0.08%. For α and ß, the mean bias is -0.2° and -1.5°. The relative standard deviations of the velocity magnitude ranges from 8 to 16%. For the flow angles, the ranges of the mean angular deviations are 5° to 16° and 0.7° and 8°.

Novel flow quantification of the carotid bulb and the common carotid artery with vector flow ultrasound.

Abnormal blood flow is usually assessed using spectral Doppler estimation of the peak systolic velocity. The technique, however, only estimates the axial velocity component, and therefore the complexity of blood flow remains hidden in conventional ultrasound examinations. With the vector ultrasound technique transverse oscillation the blood velocities of both the axial and the transverse directions are obtained and the complexity of blood flow can be visualized. The aim of the study was to determine the technical performance and interpretation of vector concentration as a tool for estimation of flow complexity. A secondary aim was to establish accuracy parameters to detect flow changes/patterns in the common carotid artery (CCA) and the carotid bulb (CB). The right carotid bifurcation including the CCA and CB of eight healthy volunteers were scanned in a longitudinal plane with vector flow ultrasound (US) using a commercial vector flow ultrasound scanner (ProFocus, BK Medical, Denmark) with a linear 5 MHz transducer transverse oscillation vector flow software. CCA and CB areas were marked in one cardiac cycle from each volunteer. The complex flow was assessed by medical expert evaluation and by vector concentration calculation. A vortex with complex flow was found in all carotid bulbs, whereas the CCA had mainly laminar flow. The medical experts evaluated the flow to be mainly laminar in the CCA (0.82 ± 0.14) and mainly complex (0.23 ± 0.22) in the CB. Likewise, the estimated vector concentrations in CCA (0.96 ± 0.16) indicated mainly laminar flow and in CB (0.83 ± 0.07) indicated mainly turbulence. Both methods were thus able to clearly distinguish the flow patterns of CCA and CB in systole. Vector concentration from angle-independent vector velocity estimates is a quantitative index, which is simple to calculate and can differentiate between laminar and complex flow.

SARUS: A Synthetic Aperture Real-time Ultrasound System.

The Synthetic Aperture Real-time Ultrasound System (SARUS) for acquiring and processing synthetic aperture (SA) data for research purposes is described. The specifications and design of the system are detailed, along with its performance for SA, nonlinear, and 3-D flow estimation imaging. SARUS acquires individual channel data simultaneously for up to 1024 transducer elements for a couple of heart beats, and is capable of transmitting any kind of excitation. The 64 boards in the system house 16 transmit and 16 receive channels each, where sampled channel data can be stored in 2 GB of RAM and processed using five field-programmable gate arrays (FPGAs). The fully parametric focusing unit calculates delays and apodization values in real time in 3-D space and can produce 350 million complex samples per channel per second for full non-recursive synthetic aperture B-mode imaging at roughly 30 high-resolution images/s. Both RF element data and beamformed data can be stored in the system for later storage and processing. The stored data can be transferred in parallel using the system's sixty-four 1-Gbit Ethernet interfaces at a theoretical rate of 3.2 GB/s to a 144-core Linux cluster.

Implementation of a versatile research data acquisition system using a commercially available medical ultrasound scanner.

This paper describes the design and implementation of a versatile, open-architecture research data acquisition system using a commercially available medical ultrasound scanner. The open architecture will allow researchers and clinicians to rapidly develop applications and move them relatively easy to the clinic. The system consists of a standard PC equipped with a camera link and an ultrasound scanner equipped with a research interface. The ultrasound scanner is an easy-to-use imaging device that is capable of generating high-quality images. In addition to supporting the acquisition of multiple data types, such as B-mode, M-mode, pulsed Doppler, and color flow imaging, the machine provides users with full control over imaging parameters such as transmit level, excitation waveform, beam angle, and focal depth. Beamformed RF data can be acquired from regions of interest throughout the image plane and stored to a file with a simple button press. For clinical trials and investigational purposes, when an identical image plane is desired for both an experimental and a reference data set, interleaved data can be captured. This form of data acquisition allows switching between multiple setups while maintaining identical transducer, scanner, region of interest, and recording time. Data acquisition is controlled through a graphical user interface running on the PC. This program implements an interface for third-party software to interact with the application. A software development toolkit is developed to give researchers and clinicians the ability to utilize third-party software for data analysis and flexible manipulation of control parameters. Because of the advantages of speed of acquisition and clinical benefit, research projects have successfully used the system to test and implement their customized solutions for different applications. Three examples of system use are presented in this paper: evaluation of synthetic aperture sequential beamformation, transverse oscillation for blood velocity estimation, and acquisition of spectral velocity data for evaluating aortic aneurysms.

Comparison of real-time in vivo spectral and vector velocity estimation.

The purpose of this study is to show whether a newly introduced vector flow method is equal to conventional spectral estimation. Thirty-two common carotid arteries of 16 healthy volunteers were scanned using a BK Medical ProFocus scanner (DK-2730, Herlev, Denmark) and a linear transducer at 5 MHz. A triplex imaging sequence yields both the conventional velocity spectrum and a two-dimensional vector velocity image. Several clinical parameters were estimated and compared for the two methods: Flow angle, peak systole velocity (PS), end diastole velocity (ED) and resistive index (RI). With a paired t-test, the spectral and vector angles did not differ significantly (p = 0.658), whereas PS (p = 0.034), ED (p = 0.004) and RI (p < 0.0001) differed significantly. Vector flow can measure the angle for spectral angle correction, thus eliminating the bias from the radiologist performing the angle setting with spectral estimation. The flow angle limitation in velocity estimation is also eliminated, so that flow at any angle can be measured.

An active learning approach to the physics of medical imaging.

This paper describes an experimentally oriented medical imaging course where the students record, process and analyse 3D data of an unknown piece of formalin fixed porcine tissue hidden in agar in order to estimate the tissue types present in a selected 2D slice. The recorded planar X-ray, CT, MRI, ultrasound and SPECT images show the tissue in very different ways. The students can only estimate the tissue type by studying the physical principles of the imaging modalities. The true answer is later revealed by anatomical photographs obtained from physical slicing. The paper describes the phantoms and methods used in the course. Sample images recorded with the different imaging modalities are provided. Challenges faced by the students are outlined. Results of the course show high increase in competencies as judged from graded reports, low course drop-out rate, high pass-rate at the exam, high student participation and large student satisfaction.