Performance Tests of Sonographic Instruments for the Measure of Flow Speed

Franco Marinozzi, Fabiano Bini, Annunziata D’Orazio Department of Mechanics and Aeronautics

“Sapienza” University of Rome via Eudossiana 18,00184 Rome, Italy

franco.marinozzi@uniroma1.it

Andrea Scorza Department of Mechanical and Industrial Engineering

University of Rome ROMA TRE via della Vasca Navale 79, 00146 Rome, Italy

Abstract—This paper describes the performance test of the Pulsed Doppler feature of clinical ultrasound platforms of various manufacturers via a blood flow phantom. This is made up by a tissue mimicking material containing a blood mimicking fluid which circulates in a vessel with a constant mean velocity by means of a centrifuge pump. From the digitized images of the Pulsed Doppler spectra over time, the mean and maximum velocities have been computed with a software package developed by the Authors. For laminar flows with a mean velocity ranging from 1,1±0,7 cm/s and 12,7±0,7 cm/s, measurements on the blood mimicking fluid were obtained using 7 different ultrasound scanner platforms, equipped with phased array and convex array probes. The pooled data have shown an overestimation of the mean velocity, from over 200 percent down to about 40 percent, depending on nominal flow rate and ultrasound equipment composition.

Keywords: Performance Testing; Clinical Ultrasound Scanners; Doppler Velocity Measurement.

I. INTRODUCTION Many national and international organizations have been involved for some time in the definition of theoretical and experimental methods for the assessment of the quality of medical ultrasound equipments. Examples are the American Insitute of Ultrasound in Medicine (AIUM) [1,2], the American Association of Physicists in Medicine (AAPM) [3] and the International Electrotechnical Committee [4]. These efforts have not led to internationally accepted quality standards yet. Today ultrasound scanners are the most utilized devices in the world for diagnostic imaging purposes. Their widespread use is justified by the non-invasive nature of the investigation which allows for a limited amount of bioeffects together with an ever growing diagnostic information contents. Diagnostic ultrasound systems can be used to implement various techniques, generally addressed as Echo-Doppler, allow to determine some fluid dynamics parameters of the blood flow in small vessels. The diagnostic quality is related to the accuracy of the measure of the flow velocity. Such an aspect should be checked via specific tests. The lack of a universally accepted directives and that of technical standards which determine the number and the kind of tests to be done in order to estimate the accuracy of the various measures, makes the performance test

of Echo-Doppler equipment a fundamental goal to define the quality of the measures for diagnostic purposes. In the present paper we investigate a performance analysis setup for evaluating the Pulsed Doppler technique of medical ultrasound scanners of various manufacturers. The test system is composed by a commercial ultrasound phantom, which is made up by a volume of tissue mimicking material (v=1490 m/s, attenuation constant 0,5 dB/cm·MHz). Inside this matrix is embedded an hydraulic circuit through which a blood mimicking fluid is pushed by a centrifugal pump. In particular, within the fluid a suspension of particles is present that reproduces the reflection of ultrasound pulses by the Red Blood Cells (RBC). In correspondence of the analyzed portion of the hydraulic circuit, the fluid circulates with nominally constant velocities ranging between 1,1±0,7 cm/s and 12,7±0,7 cm/s, to which correspond a laminar flow, given the cross sectional area of the vessel.

The ultrasound scanner calculates the distribution of fluid velocities within a Gate selected by the user by means of the detection of the Doppler frequency shift of the ultrasound echoes caused by the relative motion of the reflector with respect to the ultrasound field, according the well known approximated formula [5, 6, 7, 8, 9]:

γcos2 ⋅⋅≅cvff 0D (1)

where fD is the Doppler frequency shift, f0 is the transmission frequency of the ultrasonic wave, c the sound speed in the medium, v the velocity of the reflectors and γ the angle formed by v and the ultrasound beam. From (1) we get:

.cos2 D

0

ff

cv ⋅≅γ

(2)

Equation (2) is the relationship that allows the ultrasound scanner to assess the velocity of backscattered particles contained in a given Volume Of Interest (VOI). This is individuated by all the reflectors distributed within the volume

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common to a) the selected gate, b) the ultrasound beam and c) the vessel. The spectrum of the velocities calculated in a given time instant (during which the process can be considered as stationary) is shown on the scanner display as a column of pixels in which the vertical scale represents the velocity of the reflectors and the gray level accounts for the strength of the received echo and thus for the number of reflectors that possess that particular velocity.

An example of representation of individual spectrum is shown in Fig. 1a, where the passage from the conventional spectrum representation to that of stacked pixels is highlighted.

Figure 1. Spectral representation of Pulsed Doppler signal. In (a) conventional representation of Doppler spectrum P(f), obtained by investigation of the VOI for a short period of time (e.g. 10 ms). Each value of P(f) is proportional to the number of the scatterers which causes a given Doppler shift f and thus with a given velocity. In (b) to different values of the spectrum P(f) are associated different gray levels. In (c) a single spectrum is represented by a column of pixels, also known as spectral line, where the vertical position of each pixel is representative of the Doppler shift fD (velocity) while the gray level is representative of the strength of the received echo. Finally, the position of the column on a horizontal axis indicates the time instant in which the received echo have been acquired.

For diagnostic purposes it is useful to detect the evolution of the Doppler spectrum over time, which corresponds to the time history of the distribution of velocities of the RBC within the VOI [10] (Fig. 2). For this purpose, the ultrasound equipment converts the intensities of the Doppler signal P(f) in gray levels, and builds a spectral line (Fig. 1b): this is a column of pixels, where each pixel represents a different velocity (Doppler shift) whose gray level is representative of the number of reflectors having that velocity (Fig. 1c). From each spectral line it is possible to calculate quantities of diagnostic interest as the maximum velocity vMAX and the mean velocity v . The maximum velocity is computed as the vertical position of the last (non black) pixel of the spectral line, while v is computed from the mean value of the Doppler shift

Df utilizing (2) and (3), which follows.

∫

∫∞+

∞−

+∞

∞−

⋅

=

dffP

dffPf

f D

)(

)(

(3)

Figure 2. Example of the evolution over time of the Doppler spectrum image showed by a diagnostic equipment when investigating a laminar flow of constant value, produced by the phantom utilized in this work. In this case the fluid average velocity was v = 8,3 cm/s, nominal frequency ultrasound transducer = 2,5 MHz, depth of the Gate = 8 cm, amplitude of the Gate = 7,5 mm. In the picture is shown the relationship between the single spectral line as presented by the scanner and the velocity spectrum at a given instant.

II. PROPOSED APPROACH In the present work, a computer-based procedure is

proposed, able to provide data for technical evaluation of Echo-Doppler devices, even to not experienced customers. Main steps of this procedure are here indicated.

1) Generate one or more Echo-Doppler images by means of the use of an ultrasound flow phantom.

2) Load the filed images. 3) Select the area where the Pulsed Doppler spectral

evolution over time is present, while eliminating all the unwanted elements, such as axes and scales.

4) Determine the zero line corresponding to the zero velocity.

5) Determine the scale factor of the velocity. 6) Determine the scale factor of time. 7) Set the observation time interval. 8) Define the measurement field of positive and

negative velocities. 9) Compute the mean velocity vmean and the maximum

velocity vMAX; project the results. Steps from 3 to 9 are automatically done by the software.

Prior to execute the extraction of the parameter of interest, to each spectrum a threshold was applied in order to eliminate the influence of the noise that appears as simultaneous positive and negative components near the zero velocity line. As a first approach a constant value threshold equal to 10 percent of the maximum value (gth=0,1·gMAX) was chosen.

Estimation of mean velocity is performed on each spectral line of the diagnostic representation. In particular, the following relationship was used:

∑

∑

=

=

⋅= N

k

k

g

g

1k

N

1kkv

v (4)

where is vk the k-th velocity, which is given by the k-th pixel starting from the zero line in the diagnostic representation and gk is the corresponding gray level. The maximum velocity estimation vMAX is performed on each spectral line as well.

(a) (b)

Figure 3. Example of results produced with the automated procedure for a phantom generated flow with nominal average velocity of 2,8 cm/s. In (a) is shown the diagram of the temporal behavior of mean (blue) and maximum velocity vMAX (red). The corresponding velocities are respectively traced in black: 3,41 ± 0,15 cm/s for the mean velocity and 6,68 ± 0,26 cm/s for the maximum velocity. In (b), velocity spectrum averaged over 2 s.

For each acquired image of spectral evolution, both mean and maximum velocities have been computed by averaging these quantities over a time interval of 2 s, corresponding to about 150 spectra.

III. MATERIALS AND METHODS The experimental set-up is constituted by the ultrasound scanners with various probes (ref. to Tab. I) and an ultrasound phantom whose aspect and some features are reported in Fig. 4 and in Tab. II. The average velocity of the blood mimicking fluid can be adjusted in a range between 1 ± 0,7 cm/s and 86 ± 4 cm/s. The latter value and associated uncertainty is related to the use of a vessel of smaller diameter (3,2 mm). In this work only the diagonal tube with 8 mm of diameter was utilized, thus the maximum imposed mean velocity was about 13 cm/s. The probe is applied on the surface of the phantom, hold in place with a proper support. For several flow values imposed by the phantom, images produced by each diagnostic system were acquired and stored directly on the ultrasound scanner and then exported in TIFF format (not packed) or DICOM.

TABLE I. ULTRASOUND SCANNERS.

ALOKA SSD-5500SV with convex array UST9126 and phased array UST52101

ESAOTE TECHNOS MPX with convex array CA430 and phased array PA230

PHILIPS HDI5000 with convex array C5-2 and phased array P4-2

SIEMENS-ACUSON SEQUOIA with convex array 4C1, phased arrays 3V2C-S and 4V1-C

TOSHIBA APLIO with convex array PVM375BT and phased array PST30BT

GENERAL ELECTRIC VIVID7 with phased array M3S PHILIPS SONOS7500 with phased array S3

Figure 4. Flow phantom used in the experimental set-up. The picture shows the geometry and size of the vessels, the rotameter for adjusting the fluid velocity, a fluid reservoir and the upper area for the application of the transducer (measurement window).

TABLE II TECHNICAL SPECIFICATION OF ULTRASOUND PHANTOM

Phantom Type DANSK 453

Sound speed in the material 1490 ± 15 m/s @ 23°C Attenuation constant 0,5 ± 0,05 dB/cm·MHz @ 5 MHz

Density 1055 ± 20 kg/m3 Inner diameter of diagonal

vessel 8 mm

Wall thickness of diagonal vessel 1,6 mm

Inclination of diagonal vessel 35 degrees

Blood mimicking fluid

Water based fluid composition Glycerol, Orgasol, Triton CF54 (2%), NaBenzoat, K2EDTA

Sound speed in the fluid 1548 ± 5 m/s Attenuation constant 0,05±0,01dB/cm·MHz

The experimental data are derived from 7 different platforms (see Tab. I) with a total of 13 probes. When on the same ultrasound scanner are installed two different probes, i.e.

phased array or convex arrays, the combination is considered as two different diagnostic systems. The parameters of various equipments were set as much as possible in a similar manner, compatibly with their technical specifications. These settings are reported in Tab. III.

TABLE III COMMON SETTINGS ADOPTED FOR THE VARIOUS EQUIPMENTS.

A. Parameter B. Setting

Nominal frequency transducer (f0)

Low (1,6 ÷ 4 MHz)

Power transmission Maximum Dynamic Range (image B-mode) Maximum

Size of the Gate 8 mm Depth of the Gate ≅ 80 mm

Angle of incidence of the gate 35°÷40°

Scale of velocity Variable depending on the flow regime

Wall Filter Minimum Time to refresh the image

(duplex) Average

Window time observation of the spectrum Doppler 1,5 ÷ 4s

Pre Processing Minimize the effects of smoothing and edge enhancement in image

Post Processing Linear Gain Average

Regime flow set on phantom (vm r

average velocity in vessel)

1,1 ± 0,7 cm/s 2,8 ± 0,7 cm/s 5,5 ± 0,7 cm/s 8,3 ± 0,7 cm/s

11,1 ± 0,7 cm/s 12,7 ± 0,7 cm/s

Since the paper is not aimed to a competition among various manufacturer and models, in the following the tested combinations of scanners together with their probes will be anonymously addressed using characters from A to L.

IV. RESULTS Experimental results for different diagnostic ultrasound systems are shown in Fig. 5 and Fig. 6. The standard deviation bars have been computed with 95 percent of confidence level by summing in quadrature the three contributions due to (a) “phantom uncertainty” (±0,7 cm/s) declared by the manufacturer (b) standard deviation of temporal evolution of the mean and maximum velocities as computed by the image analysis software (see Fig. 3a) and (c) standard deviation due to quantization error of both velocity and gray level scales. This latter contribute was definitely neglegible, i.e. well below 1 percent in all the various experimental conditions. In Fig. 5 bar graphs refer to the measurements of mean and maximum flow velocity for 5 diagnostic systems (A, B, C, D and E), at 6 different values vm r set on the phantom (1,1 cm/s, 2,8 cm/s, 5,5 cm/s, 8,3 cm/s, 11,1 cm/s and 12,7 cm/s) where the subscript r denotes the reference value. Uncertainty bars,

calculated as mentioned above, are superimposed to the bar graphs. In Fig. 5a and 5e every bar represents the averaged mean velocity evalued by the ultrasound scanner, when a phased array probe and convex array probe is used respectively. Such averages are done over 150 spectral lines. In Fig. 5c and 5g graphs refer to the percentual difference between the average mean velocity vm measured by the diagnostic device and the velocity vm r set on the Doppler phantom. Similar diagrams are plotted for the maximum velocity vMAX m in Fig. 5b and Fig. 5f, with the correspondent percentual deviation from values set on the phantom (Fig. 5d and Fig. 5h). The value of vm r was read on the graduated scale of the flow measurement device of the phantom (the rotameter in Fig. 4), while the value of vMAX m r was assumed equal to 2 vm r, given the laminar behavior of the flow.

Figure 5. Velocity measurements on five diagnostic systems (A, B, C, D and E) each one equipped with two different probes, phased array and convex array. In (a) and (e) mean velocity vm vs. velocity vm r set on the phantom is plotted, likewise in (b) and (f) for the averaged maximum velocity vMAX m vs vMAX m r. In (c) and (d) percentual deviation for phased array probes on the mean velocity and on the maximum velocity. In (g) and (h) percentual deviation for convex array probes, on the mean velocity and on the maximum velocity.

In Fig. 6 further measurements are shown for other 5 ultrasound systems (F,G, H, I and L) where only phased array probes are used.

Figure 6. Velocity measurements on five ultrasound systems (F, G, H, I and L) each one equipped with a phased array probe. In (a) and (c) mean velocity vm and its percentual deviation from the imposed velocity vm r are plotted. Likewise in (b) and (d) the averaged maximum velocity vMAXm vs vMAX m r and its percentual deviation are plotted.

In Fig. 5 and Fig. 6 the somewhat conspicuous deviations of the results from the nominal velocities can be explained as follows. For the mean vm the following sources of error can be considered (1) the influence of the wall filter on low flow rates (the wall filter eliminates the velocity components below a threshold value), (2) the cited Doppler phantom uncertainty (both reading and instrumental uncertainties, equal to roughly the 5 percent of the full scale range) (3) spectral broadening [11], when particles of same velocity inside the VOI are viewed by the ultrasound probe under different angles γ and different velocity are measured, (4) fill in effects due to the size of measurement volume and the intersection among the ultrasound beam and the cylindrical vessel in the phantom, so velocities are observed in an irregularly shaped volume. The above causes also influence the evaluation of the maximum velocity vMAX m

, except those due to the wall filter and the fixed 10 percent threshold. However, as a systematic behavior, results show that all ultrasound equipments overestimate the value of the flow velocity set by the phantom. In fact, to a first analysis, all the cited causes of error tend to exclude the contribution of low velocity scatterers inside the measurement volume, since they are confined near the vessel walls. Conversely, the high velocity particles are most probably inside the investigated volume, since they are distributed along the vessel axis. Hovever, for velocities greater than or equal to 2,8 cm/s, we just point out that the deviation on the nominal quantities is in most cases below 40 percent. At the lowest velocities (i.e. 1,1 cm/s) much greater deviations are observed. Nevertheless, some ultrasound equipment show some better performance than others (i.e. B and E in Fig. 5, F and G in Fig. 6 ). This latter circumstance could suggest a new criterion

of comparison among devices, i.e., the measure of their performances when analyzing low flow rates. By other hand, the Authors are aware that this principle can not be applied since more accurate phantoms will be available; in fact, there is a high uncertainty on the flows in the hydraulic circuit (± 0,7 cm/s corresponding to more than 50 percent for flows of mean velocity lower than 1,4 cm/s). Under these assumptions, it is sensible to wonder whether the diagnostic ultrasound system characterizes the quality of the flow phantom or vice versa.

CONCLUSIONS

In the present work an analysis of performances of different models of Echo-Doppler systems has been described. In particular, the analysis has been conducted by means of a commercial flow phantom. For stationary flow with a mean velocity range from 1,1 ± 0,7 cm/s and 12,7 ± 0,7 cm/s, various trials have been conducted to evaluate the accuracy of velocity measurements performed by 10 different ultrasound systems, equipped with phased array and convex array probes. For this purpose, a software procedure was developed to extract from the spectral evolution presented on the scanner display, quantities such as mean and maximum velocities. The pooled data are free from human errors since the procedure do not require the judgment of a specialized operator. Results for 7 ultrasound platforms, equipped with phased array and convex array probes, are shown. For nominal velocities lower than about 3 cm/s, the ultrasound scanners overestimate the mean velocity less than 35 percent for the phased array probes and 42 percent for convex array probes. This deviation is much greater at low velocities (about 1 cm/s) where the different performances among the tested systems become noticeable: this would suggest an assessment criterion for the Echo-Doppler diagnostic systems, based on the evaluation of their accuracy at low velocity. Such principle has not been adopted yet because of the relatively high flow uncertainty in the phantom. This circumstance, in a next future, push for the development of a measurement system in which the reference velocities can be generated with lower uncertainty so that low flow regime tests (less than about 3 cm/s) can be exploited.

ACKNOWLEDGEMENTS

The Authors wish to deeply thank prof. Branca for

his support and advices.

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