Doppler twinkling artifact observations: an open-access database of raw ultrasonic signals

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BACKGROUND

A twinkling artifact in the color flow mapping (CFM) mode appears as a fast chaotic change of colored pixels on the screen of ultrasonic medical devices. This artifact is observed in the modes that were originally designed to assess blood flow, with marking of areas where blood motion is excluded. The clinical significance of the problem is related to the potential use of a twinkling artifact as an additional diagnostic sign when searching for stones in the kidney, ureter and bladder, and gallbladder and bile duct. Moreover, this artifact may be useful for detecting micro calcifications in breast neoplasms [1–8]. The high prevalence and social significance of these diseases and possible difficulties in their detection using traditional ultrasonic imaging require additional diagnostic options, such as the skillful use of the twinkling artifact. The detectability and intensity of the twinkling artifact varied and depend on the scanning equipment and its settings.

Several competing and weakly related hypotheses have tried to explain the cause of the twinkling artifact [9–16]. To prove their hypotheses, most authors have cited images from the screen of the ultrasonic device. The ultrasonic device was a “black box” for the authors of these hypotheses. Assumptions about the causes of the twinkling artifact were made without studying all signal processing steps. Thus, most hypotheses cannot be substantiated.

Unfortunately, the majority of available studies on the twinkling artifact did not analyze radiofrequency (RF) data, which carry more information compared with sonograms. Thus, hard-to-reach research instruments that provide access to raw RF signals are needed to obtain such data. Currently, no datasets exist in the public domain that contains ultrasonic Doppler signals with signs of the twinkling artifact.

This article presents an open-access database of RF signals, which were obtained from the beamformer output of the preprocessing path of a research ultrasonic device, and a tool for its viewing and analysis.

METHODS

Eligibility criteria

The database contains RF signals of observations of artificial objects (phantoms) that contain signs of the twinkling artifact. Only after the appearance of the stable twinkling artifact on two ultrasound machines was achieved, the corresponding signals were included in the database. The database also includes records of a blood mimicking fluid from a Doppler flow phantom, which imitates the normal blood flow in the vessel.

Data collection

The study was conducted between July 2016 and July 2021.

Ultrasonic equipment

Data were obtained from the CFI- and B-mode channels of the Sonomed-500 ultrasonic device (Spectromed, Moscow) by using linear (7.5 L38) and convex (3.4 C60) transducers.

 

Fig. 1. Data capture scheme

 

RF signals from which the database was formed are shown in Fig. 1. The 64 elements of the phased array transducer were used to form a beam for each scanning direction. At the transmission stage, all selscted elements emit pulses with specific delays to focus ultrasound at a predetermined depth. Pulses of approximately 1 µs and 4 µs duration for the B-mode and Doppler mode, respectively, were emitted. Echoes were received separately by each array element, further amplified in an analog receiver module, and digitized at a frequency of 50 MHz. Digital signals of individual channels were coherently summarized in the beamformer with delays that provide dynamic focusing. Each signal or the formed beam was subjected to decimation, that is, the frequency of digitization was reduced to 10 MHz. The scanning direction was selected by reconnecting the active elements of the transducer.

An auxiliary ultrasound scanner Medison SA-8000 EX (South Korea), which does not provide access to raw data, was used to control the reliability of observations. This scanner was with used a linear L5-9EC transducer and a convex C3-7ED transducer. The use of the control machine ensured that the artifact appeared as a result of objective physical processes occurring in the examined objects. This reduces the probability of situations in which the twinkling artifact results not from the properties of the object under investigation but from some unknown features of one of the devices.

Principles of CFM Data Acquisition

The size of the CFM area was determined interactively by the examiner. Each direction (beam) in the selected area was sonified N times. A group of N signals obtained by sonifying the same area of tissue is called a Doppler pulse train. The time within the pulse train is called “slow” time, it is measured for a single spatial position, as opposed to the “fast” time, which is directly proportional to the depth. Blood flow and other processes are tracked by changes in “slow” time signals within a single pulse train. If there are no changes in the examined object, these signals are almost identical, the slight difference is the contribution of the noise.

 

Fig. 2. Explanation of the scanning scheme in the color flow mapping mode. The color coding of the vertical bars corresponds to the number of the beam in the sweep. Red color shows the examined vessel.

 

If the same direction is sonified sequentially to obtain a pulse train, a pulse repetition rate of approximately 5 kHz may be obtained, which is not appropriate for most medical applications. To reduce the pulse repetition rate, the examined area was divided into S scanning subareas (sweeps), each of which consisted of M beams (Fig. 2). When obtaining a pulse train, the beams of one subarea were sequentially irradiated from the 1st to the M-th beam. Thus, Doppler pulse trains were formed in parallel for M beams of one subarea. Subsequently, the process was repeated for other subareas, whereas the pulse repetition rate was decreased by M times.

The total size of the range of interest determined the number of beams (S×M). One beam consisted of P complex samples. The Q beam density was sometimes changed to increase the frame rate. Thus, if Q = 2, the CFM window was updated twice as fast; however, the information about every second beam was lost.

All these steps were repeated F times; thus, a cine loop was formed, which consisted of F frames. The received signals were recorded in a binary file, and the scanning parameters were placed in a text file of the same name (Table).

 

Table. Main scanning parameters displayed in the .par file

Parameters	Description	Symbols
Number of frames	Number of frames	F
Raw frame size	Memory size in bytes occupied by the RF data that is required to build one frame in the duplex B+CFM mode	-
Header size	Memory size in bytes that is reserved in front of each beam	-
Number of B-beams	Number of beams that are used to obtain a gray-scale image	B
Size of B-beam in samples	Number of samples that are used when obtaining a gray-scale image, which depends on the scanning depth	G
Number of CF shots	Number of pulses in a Doppler pulse train	N
Number of sweeps	Number of beam groups in the CFM mode. A group of beams is called a sweep. The CFM-frame consists of several sweeps	S
Beams in sweep	Number of beams in each sweep	M
Size of CFM beam in samples	Number of samples in the CFM mode	P
First scan CFM beam	CFM window position by B-image width	-
CFM density	Beam density in the CFM mode is determined by the formula (b-a)/c, where a and b are the numbers of B-beams, which define the left and right borders of the CFM window, and c is the number of CFM beams	Q
Number of CFM beams	Number of beams in the CFM mode	S×M
Number of first CFM sample	Depth position of the CFM window relative to the B-image	-

Note. CFM, color flow mapping.

 

Examined objects and observations

Most of the items in the database contain signals that were reflected from objects on which a twinkling artifact is observed in Doppler modes. Artificial objects included rough and smooth wire made of low carbon raw steel, and rods made of plastic (ABS), aluminum, and wood. The objects were placed in fixed positions in the body of a specially designed phantom. The body was filled with agar-agar, water, and ethyl alcohol. A Doppler phantom Gammex 1430 LE Mini-Doppler Flow System (USA) was used to record signals from the flowing fluid.

The Doppler pulse train consisted of 5, 9, or 17 pulses. Examinations with a linear transducer were conducted at a carrier frequency of 7.5 MHz and a power of 74% for B- mode. For the CFM mode, the carrier frequency, power, and pulse repetition rate were 6.3 MHz, 97%, and 750 Hz, respectively. Examinations with a convex transducer were conducted at a carrier frequency and power of 3.3 MHz and 95% in B-mode and 3.3 MHz and 98%, respectively, with a pulse repetition rate of 1 kHz, in the CFM mode. The sampling rate in all cases was 10 MHz. Other settings, such as interframe averaging and wall filter settings, did not affect the data, since the data were obtained from the preprocessing path.

Database contents

Summary of database contents

Records of digital RF signals with twinkling artifact features were collected and placed in the public domain (https://mosmed.ai/datasets/ultrasonic_doppler_twinkling_artifact). The database also contains signals from areas with vessels in the Gammex phantom, specialized phantoms of proprietary design, and reflections from tissue-imitating materials. This database will be useful to researchers who study algorithms for B-mode and CFM signal processing.

 

Fig. 3. Composition of the database.

 

The database includes five sets of examinations, which differ in the object of study (Fig. 3). Each examination is a pair of files with the same name and.dat and.par extensions. “Raw” data records are accompanied by images and videos that illustrate the appearance of the twinkling artifact. The examined objects and environments are specified in the directory names of the database. In the directory name, the word “linear” indicates the use of the 7.5 L38 linear transducers, while “convex” indicates the use of the 3.4 C60 convex transducers.

Database file format

RF signals were recorded in binary form in a file with .dat extension (Fig. 4). This file contained complex data for building a frame in the B-mode (B-frame) and CFM mode (CFM-frame). The real and imaginary parts of each dataset were written in a “32-bit little-endian (LE) signed integer” format. Initially, a 20-bit header was recorded, which is denoted in Fig. 4 as H symbol. Afterward, the samples of the first beam of the B-image, which are denoted as B-sample 1 to B, the header, and the samples of the second and subsequent beams of the B-image were recorded.

 

Fig. 4. Scheme for storing “raw” radio frequency data in a *.dat file.

 

Then, the samples for constructing the CFM, which are denoted as a СFM-sample, were recorded. In this case, the H header was recorded first, followed by recording all depth samples, which are obtained for the first pulse in the pulse train and the first beam from the first group (sweep). Thus, we obtained the first line of the CFM data; each subsequent line was also separated by a header.

The second and subsequent frames were recorded in the same way. Each.dat file corresponded to a text file of the same name with the.par extension, which contained information on scanning parameters (Table) and specific F, G, B, F, S, N, M, P, and Q values.

Database viewer

The TwinklingDatasetDisplay program is developed to view and analyze the proposed database. The program is intended only for viewing RF signals and does not include any signal processing algorithms for CFM [17–30]. All software modules are written in C++ using the XRAD library [31]. The program is in the public domain (TwinklingDatasetDisplay.git). The database also included Windows executable files.

The TwinklingDatasetDisplay program allows the following:

• Opening .dat files using information from the .par files.
• Forming a conventional B-mode image from the data.
• Displaying complex signals in the form of graphs depending on both “fast” and “slow” time of the CFM mode.
• Applying elements of spectral analysis thereto.

Examples of “slow” time signals, which determine the Doppler pattern, are shown in Fig. 5. Typical graphs of signals from different areas are shown here:

• The area of the blood-mimicking fluid flow in the Doppler phantom channel of the Gammex 1430 LE Mini-Doppler Flow System (real and imaginary parts of the signal change in quadrature, which is typical for moving objects; Fig. 5a).
• The area of soft tissues in the absence of motion (after filtering the signal from the tissues, only the noise remains; Fig. 5b).
• The observation area of the twinkling artifact on a steel wire (a random signal is observed, which differs from the noise in Fig. 5b by greater dispersion; Fig. 5c).
• The observation area of the twinkling artifact on a smooth object (the signal shows a periodicity resulted from micro-oscillations of the observed object; Fig. 5d).

 

Fig. 5. Examples of visualization of radio frequency signals using the TwinklingDatasetDisplay program: a - fluid flow in the Gammex phantom; b - soft tissue area in the absence of movement; с - signal of a flickering artifact on a rough object; d - signal of a flickering artifact on a smooth object. In the left column, complex signals are presented as a parametric line in polar coordinates (the real part is displayed along the abscissa axis, the imaginary part along the ordinate axis). The right column shows the dependence on "slow" time within the burst.

 

Database composition

1. A set of examinations of the Gammex 1430 LE Mini-Doppler Flow System.

 

Fig. 6. External view and scheme of the Gammex 1430 LE Mini-Doppler phantom.

 

Fig. 6 shows the external view and scheme of the phantom, and Fig. 7 shows examples of sonograms. In transverse scanning, the linear transducer was positioned at an angle of 60° to the vessel, the flow rate was 30 cm/s, data were obtained at 5, 9, and 17 pulses in train, and the pulse repetition frequency was 2.5 kHz. Concurrently, an observed sonogram in the phantom was very much alike that of the in vivo carotid artery.

In the course of longitudinal scanning with a linear transducer, the flow velocity was set to 50 cm/s, and the study was conducted with 17 probing pulses and a frequency of 1 kHz. The velocity projection, which was displayed in the Doppler mode, was close to zero. Such a study may be useful for debugging mapping algorithms.

Longitudinal scanning with a convex transducer was also performed, while three examinations were conducted at different flow rates (i.e., 30 cm/s, 65 cm/s, and 100 cm/s) at a pulse repetition frequency of 2 kHz. For these examinations, a convex transducer was used. The estimated value of the flow velocity projection along a horizontal vessel varied from a negative value, passing through zero, to a positive value; the vessel was colored in the whole palette of the CFM mode.

 

Fig. 7. Sonograms of the Gammex phantom: a - when examining with a linear transducer at an angle of 60º to the flow; b - parallel to the flow; c - when examining with a convex probe.

 

In Fig. 7 and all subsequent sonograms, both the B-image with the superimposed CFM imaging and the B-image without CFM are placed side by side. Subsequent examinations were conducted using a linear transducer, since it is commonly used in small depth examinations. Preference was given to small values of the pulse repetition frequency since both types of twinkling artifact signals be registered in this case [32].

2. A set of examinations of the custom phantom (Fig. 8; a detailed description of the phantom is available in [32]).

 

Fig. 8. Photo and drawings of the specialized phantom with dimensions in millimeters and measurement positions.

 

In the phantom study, the linear transducer was applied in fixed numbered positions. Cylinders, with a diameter of 1.75 mm, made of metal (positions 1, 4, and 8), plastic (positions 2, 5, and 7), and wooden rods (positions 3 and 6) in various media (water, alcohol, and agar-agar) were assessed. The set contains examinations that were conducted using a linear transducer at nine probing pulses and a pulse repetition rate of 1 kHz. Typical sonograms are shown in Fig. 9. If the phantom was filled with ethanol, the twinkling artifact was manifested much less frequently in contrast to other media used. In water, the artifact was also noticeable on the air bubbles that rose from the wooden rod. In addition, the twinkling intensity on aluminum rods was noticeably greater than that on plastic and wooden rods.

 

Fig. 9. Examples of sonograms of a specialized phantom with positions and a filling medium: a, position 2 (four plastic rods, which are located parallel to the sensor plane); b, position 3 (four wooden rods with their sides facing the sensor); c, position 4 (four aluminum rods with their sides facing the sensor); d, position 10 (wood, aluminum, and plastic rods with their sides facing the sensor).

 

3. A set of examinations of elastographic breast Blue Phantom with the data that have been taken with a linear transducer at 5, 9, and 17 pulses in sequence for a pulse repetition frequency of 150 Hz and at 17 pulses and repetition frequencies of 300 Hz, 500 Hz, 750 Hz, and 1 kHz.

 

Fig. 10. Phantom of the mammary gland Blue Phantom: a - appearance; b - connection diagram; c - sections of a computed tomogram (the arrow indicates the area under study); d - sonogram.

 

The phantom (photo and scheme shown in Fig. 10 a, b) contains inclusions that simulate micro calcifications, which are indicated by an arrow in a slice of the computer tomogram in Fig. 10c. On these inclusions, a twinkling artifact was observed at a low pulse repetition frequency in the CFM mode (Fig. 10d). With increasing frequency, the intensity of the artifact decreased until it completely disappeared at frequencies above 1 kHz.

4. A set of approximately 200-μm micro calcifications that were artificially grown in agar-agar jelly.

Two samples were examined with a linear sensor at a repetition rate of 500 Hz with nine pulses per pulse train. Typical sonograms are shown in Fig. 11.

 

Fig. 11. Sonograms of phantoms with microcrystals grown in agar jelly: a - sample section under a microscope; b - microcrystals during growth; c - insert with microcrystals in an agar-agar phantom.

 

5. A study of a steel rough wire and a wooden rod in agar-agar jelly.

The study was conducted with a linear transducer at nine pulses. In contrast to the experiment presented in Fig. 9, the wood was subjected to prolonged pre-wetting and degassing. Both objects produced an acoustic shadow and had the same echogenicity in the B-image (Fig. 12). However, the twinkling artifact appeared on the metal, but not on the wood. The difference in observations allows associating one of the twinkling types with air microbubbles in the wood structure.

Notes on the database use

In most studies [1–8, 10–13], which were devoted to the twinkling artifact, examinations were conducted using commonly available ultrasonic diagnostic devices with no access to the signal processing path. The ultrasonic device can be considered a “black box” in such examinations, and the analysis based only on sonograms on the device screen was not informative enough and created problems with reproducibility, since the algorithms of processing devices of different manufacturers are unique.

Collection of raw data is a prerequisite for developing new ultrasonic imaging tools. However, RF signals from the processing path are commonly not available because of the closed architecture of commercial instruments. A previous study [33] demonstrated a possible solution to this problem, which required a manual modification of the equipment. The proposed database provides all information on signals without the need for self-modification of the commercial equipment with the inevitable loss of warranty and other undesirable consequences.

The proposed database may have great practical value, since it allows the creation of new tools [17] for the detection of kidney stones and other objects, which are associated with a twinkling artifact.

Using the database, we conducted several examinations, as shown below:

1) The signals of the twinkling artifact and blood flow were differentiated and two physical causes of the twinkling artifact were investigated. The image on the device screen looks the same; however, different physical processes are involved therein, which are visible at the signal level [32].

2) A special mode was developed, which allowed displaying twinkling not as a Doppler error, which happens to be useful, but as a special diagnostic option [17, 34]. Using this mode, the twinkling may be “pulled out” where a conventional device will not show this artifact. Twinkling and blood flow may be displayed separately or together using different color scales.

3) A comparative analysis of filtration algorithms for vessel wall motion (wall filters) was conducted [35, 36]. New filtering algorithms appeared in the literature [37–40], their fresh review and comparative analysis are in demand and can be done using our database.

In the future, we would like to complement the database with in vivo signals as well as signals that were obtained in other modes (e.g., spectral Doppler mode and vector flow).

 

Fig. 12. Sonogram of a phantom with a wooden rod (left) and steel wire (right).

 

Although the programm that we designed for opening the database has a minimal set of options, its open-source C++ code allows plentiful modifications. Moreover, the given in this article description gives sufficient information for opening of the database in any programming environment.

Disadvantages of the database

Among the disadvantages of the proposed database, the most significant is the incompleteness of the following information:

• On the examined objects (e.g., only the approximate size of calcinates that were grown in agar jelly was known, the geometrical parameters of the rough wire surface were not investigated).
• On the experimental conditions (in some examinations, the exact position of the transducer, focal distance, and emittion power were not recorded; the information on the pulse repetition frequency is not always available).

Code availability

The source code of the program (https://github.com/Center-of-Diagnostics-and-Telemedicine/TwinklingDatasetDisplay.git) is available.

Terms of use

The article presents a database, which contains digital records of raw RF signals from the preprocessing path of the Sonomed-500 ultrasonic device. The database with a total volume of 10.5 Gb contains mostly examinations of objects with a twinkling artifact in the CFM mode. The most obvious application of the database is the development and testing of algorithms for signal processing. The database is publicly available on the Internet under the Creative Commons Attribution – Noncommercial – Share Alike (CC BY-NC-SA) license (https://mosmed.ai/datasets/ultrasonic_doppler_twinkling_artifact).

In case of publication of results that were obtained using the database, please refer to this article. The derivative products must be distributed under the same license. Any attempt to gain financial benefit from the use of the database is strictly prohibited.

ADDITIONAL INFORMATION

Funding source. This article was prepared with the support of Moscow Healthcare Department as a part of Program “Scientific Support of the Capital’s Healthcare” for 2020–2022 (Unified State Information System for Accounting of Research, Development, and Technological Works No. АААА-А20-120071090054-9).

Competing interests. The authors declare that they have no competing interests.

Authors’ contribution. Kulberg N.S. and Leonov D.V. — research concept and design, data collection and processing, preparation of illustrations, and writing the text of the manuscript.

Reshetnikov R.V. and Nasibullina A.A. — participation in the formation of the research plan and discussion each chapter of the manuscript, checking the database, and preparing illustrations.

Gromov A.I. — research concept and design, and manuscript editing. All authors confirm the compliance of the authors with the international ICMJE criteria. All authors made a significant contribution to the development of the concept, research, and preparation of the article, read and approved the final version before publication.

About the authors

Denis V. Leonov

Moscow Center for Diagnostics and Telemedicine; National Research University Moscow Power Engineering Institute

Email: strat89@mail.ru
ORCID iD: 0000-0003-0916-6552
SPIN-code: 5510-4075
Scopus Author ID: 56781375200
ResearcherId: P-5266-2017

Cand. Sci. (Tech)

Russian Federation, 24 bld.1, Petrovka street,127051 Moscow; 28-1, Srednyaya Kalitnikovskaya street, Moscow, 109029

Roman V. Reshetnikov

Moscow Center for Diagnostics and Telemedicine; The First Sechenov Moscow State Medical University (Sechenov University)

Email: reshetnikov@fbb.msu.ru
ORCID iD: 0000-0002-9661-0254
SPIN-code: 8592-0558

Cand. Sci. (Phys.-Math.)

Russian Federation, 24 bld.1, Petrovka street,127051 Moscow; 127051 Moscow, Russia; 8 bld.2

Nikolay S. Kulberg

Moscow Center for Diagnostics and Telemedicine; Federal Research Center Computer Science and Control of the Russian Academy of Sciences

Email: kulberg@npcmr.ru
ORCID iD: 0000-0001-7046-7157
SPIN-code: 2135-9543

Cand. Sci. (Phys.-Math.)

Russian Federation, 24 bld.1, Petrovka street,127051 Moscow; 44, buil. 2, st. Vavilova, Moscow 119333

Anastasia A. Nasibullina

National Research University Moscow Power Engineering Institute

Email: nastya.nasibullina@yandex.ru
ORCID iD: 0000-0003-1695-7731
SPIN-code: 2482-3372

Student

Russian Federation, 28-1, Srednyaya Kalitnikovskaya street, Moscow, 109029

Alexandr I. Gromov

A.I. Yevdokimov Moscow State University of Medicine and Dentistry

Author for correspondence.
Email: gromov.ai@medsigroup.ru
ORCID iD: 0000-0002-9014-9022
SPIN-code: 6842-8684

MD, Dr. Sci. (Med.), Professor

Russian Federation, Delegatskaya st., 20, p. 1, 127473, Moscow

References

Supplementary files