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

Cover Image

Cite item

Full Text

Abstract

BACKGROUND: Doppler twinkling artifact is a rapid change of colors seen in CFI-mode in the presence of kidney stones and calculi. Therefore, numerous researchers use the twinkling artifact as a diagnostic sign. However, this phenomenon is under-researched, because most assumptions concerning its causes are made based on pure visual observations of the scanner’s screen leaving the important steps of signal transformation hidden behind the “black box” curtains of ultrasound machines.

MATERIALS AND METHODS: Raw radiofrequency ultrasound signals were recorded in the phantom studies. The recorded echoes were received from objects that create the Doppler twinkling artifact and artificial blood vessels and soft tissues imitators. The data were collected between June 2016 and March 2021. Sonomed-500 with the 7.5 L38 and 3.4 C60 probes served as the research machine for the signal capture.

Data records: We present the database containing raw radiofrequency ultrasound signals from the beam former output of the research ultrasound machine. The dataset consists of CFI and B-mode echoes recorded from twinkling objects. Therefore, this database can be useful for those who test, develop and study ultrasound signal processing algorithms. Furthermore, the database is freely available online. The 10.5 GB database consists of echoes received from five phantoms. Raw radiofrequency signals were stored in the binary files; scanning parameters were stored in text files. The database is available at: https://mosmed.ai/datasets/ultrasound_doppler_twinkling_artifact.

Code availability: The public can visualize the database content with the specially written program TwinklingDatasetDisplay available at: https://github.com/Center-of-Diagnostics-and-Telemedicine/TwinklingDatasetDisplay.git.

Usage notes: The database can be used to test and develop signal-processing algorithms, such as wall filtration, velocity estimation, feature extraction, speckle reduction, etc. Furthermore, the public is free to share (copy, distribute, and transmit) and remix (adapt and do derivative works) the dataset considering appropriate credit is given.

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

  1. Masch WR, Cohan RH, Ellis JH, et al. Clinical effectiveness of prospectively reported sonographic twinkling artifact for the diagnosis of renal calculus in patients without known urolithiasis. Am J Roentgenol. 2016;206:326–331. doi: 10.2214/ajr.15.14998
  2. Fujimoto Y, Shimono C, Shimoyama N, Osaki M. Twinkling artifact of microcalcifications in breast ultrasound. Ultrasound Med Biol. 2017;43(Suppl. 1):S21. doi: 10.1016/j.ultrasmedbio.2017.08.1010
  3. Bennett J.M., Estrada J.C., Shoemaker M.B., Pretorius M. Twinkling Artifact Associated with Guidewire Placement. Anesth Analg. 2015;121(1):69–71. doi: 10.1213/ane.0000000000000683
  4. Sen V, Imamoglu C, Kucukturkmen I, et al. Can Doppler ultrasonography Twinkling artifact be used as an alternative imaging modality to non-contrast-enhanced computed tomography in patients with ureteral stones? A prospective clinical study. Urolithiasis. 2017;45(2):215–219. doi: 10.1007/s00240-016-0891-8
  5. Winkel RR, Kalhauge A, Fredfeldt KE. The usefulness of ultrasound colour-Doppler twinkling artefact for detecting urolithiasis compared with low dose nonenhanced computerized tomography. Ultrasound Med Biol. 2012;38(7):1180–1187. doi: 10.1016/j.ultrasmedbio.2012.03.003
  6. Yavuz A, Ceken K, Alimoglu E, Kabaalioglu A. The reliability of color Doppler "twinkling" artifact for diagnosing millimetrical nephrolithiasis: comparison with B-Mode US and CT scanning results. J Med Ultrasonics. 2015;42(2):215–222. doi: 10.1007/s10396-014-0599-8
  7. Tian J, Xu L. Color Doppler Twinkling artifact in diagnosis of tuberculous pleuritis: A comparison with gray-scale ultrasonography and computed tomography. Ultrasound Med Biol. 2018;44(6): 1291–1295. doi: 10.1016/j.ultrasmedbio.2018.01.003
  8. Relea A, Alonso JA, González M, et al. Usefulness of the twinkling artifact on Doppler ultrasound for the detection of breast microcalcifications. Radiología. 2018;60(5):413–423. doi: 10.1016/j.rx.2018.04.004
  9. Lu W, Sapozhnikov OA, Bailey MR, et al. Evidence for trapped surface bubbles as the cause for the twinkling artifact in ultrasound imaging. Ultrasound Med. 2013;39(6):1026–1038. doi: 10.1016/j.ultrasmedbio.2013.01.011
  10. Aytac SK, Ozcan H. Effect of color Doppler system on the «twinkling» sign associated with urinary tract calculi. J Clin Ultrasound. 1999;27(8):433–439. doi: 10.1002/(sici)1097-0096(199910)27:8<433::aid-jcu4>3.0.co;2-1
  11. Rahmouni A, Bargoin R, Herment A, et al. Color Doppler Twinkling artifactin hyperechoic regions. Radiology. 1996;199(1):269–271. doi: 10.1148/radiology.199.1.8633158
  12. Kamaya A, Tuthill T, Rubin JM. Twinkling artifact on color Doppler sonography: dependence on machine parameters and underlying cause. Am J Roentgenol. 2003;180(1):215–222. doi: 10.2214/ajr.180.1.1800215
  13. Weinstein SP, Seghal C, Conant EF, Patton JA. Microcalcifications in breast tissue phantoms visualized with acoustic resonance coupled with power doppler US: initial observations. Radiology. 2002:224(1):265–269. doi: 10.1148/radiol.2241010511
  14. Seghal C. Apparatus for imaging an element within a tissue and method therefor. United States Patent. 1999;477(5):997.
  15. Li T, Khokhlova TD, Sapozhnikov OA, et al. A new active cavitation mapping technique for pulsed HIFU applications–bubble Doppler. IEEE Trans Ultrason Ferroelectr Freq Control. 2014;61(10): 1698–1708. doi: 10.1109/TUFFC.2014.006502
  16. Simon JC, Sapozhnikov OA, Kreider W, et al. The role of trapped bubbles in kidney stone detection with the color Doppler ultrasound twinkling artifact. Phys Med Biol. 2018;63(2):025011. doi: 10.1088/1361-6560/aa9a2f
  17. Leonov DV, Kulberg NS, Gromov AI, et al. Diagnostic mode detecting solid mineral inclusions in medical ultrasound imaging. Acoust Phys. 2018;64(5):624–636. doi: 10.1134/S1063771018050068
  18. Yu AC, Johnston KW, Cobbold RS. Frequency-based signal processing for ultrasound color flow imaging. Canadian Acoustics. 2007;35(2):11–23.
  19. Yu AC, Løvstakken L. Eigen-based clutter filter design for ultrasound color flow imaging: a review. IEEE Trans Ultrason Ferroelectr Freq Control. 2010;57(5):1096–1111. doi: 10.1109/TUFFC.2010.1521
  20. Yu AC, Cobbold RS. Single-ensemble-based eigen-processing methods for color flow imaging ― Part I. The Hankel-SVD filter. IEEE Trans Ultrason Ferroelectr Freq Control. 2008;55(3):559–572. doi: 10.1109/TUFFC.2008.682
  21. Shen Z, Feng N, Shen Y, Lee CH. An improved parametric relaxation approach to blood flow signal estimation with single-ensemble in color flow imaging. J Med Biomed Engineering. 2013;33(3):309–318. doi: 10.5405/jmbe.1368
  22. Yoo YM, Managuli R, Kim Y. Adaptive clutter filtering for ultrasound color flow imaging. Ultrasound Med Biol. 2003;29(9): 1311–1320. doi: 10.1016/S0301-5629(03)01014-7
  23. Torp H. Clutter rejection filters in color flow imaging: a theoretical approach. IEEE Trans Ultrason Ferroelectr Freq Control. 1997;44(2):417–424. doi: 10.1109/58.585126
  24. Wang PD, Shen Y, Feng NZ. A novel clutter rejection scheme in color flow imaging. Ultrasonics. 2006;44( Suppl 1):e303–305. doi: 10.1016/j.ultras.2006.06.017
  25. Bjærum S, Torp H. Statistical evaluation of clutter filters in color flow imaging. Ultrasonics. 2000;38(1-8):376–380. doi: 10.1016/s0041-624x(99)00153-5
  26. Kargel C, Hoebenreich G, Plevnik G, et al. Velocity estimation and adaptive clutter filtering for color flow imaging. WSEAS. 2002. Р. 1711–1716.
  27. Kargel C, Höbenreich G, Trummer B, Insana MF. Adaptive clutter rejection filtering in ultrasonic strain-flow imaging. IEEE Trans Ultrason Ferroelectr Freq Control. 2003;50(7):824–835. doi: 10.1109/tuffc.2003.1214502
  28. Lo MT, Hu K, Peng CK, Novak V. Multimodal pressure flow analysis: application of hilbert huang transform in carabral blood flow regulation. EURASIP J Adv Signal Process. 2008;2008:785243. doi: 10.1155/2008/785243
  29. Gerbands JJ. On the relationships between SVD, KLT and PCA. Pattern Recognition. 1981;14:375–381. doi: 10.1016/0031-3203(81)90082-0
  30. Løvstakken L. Signal processing in diagnostic ultrasound: algorithms for real-time estimation and visualization of blood flow velocity. Doctoral thesis, norwegian university of science and technology. Trondheim; 2007. Available from: https://pdfslide.net/ documents/signal-processing-in-diagnostic-ultrasound-algorithms-for-real-time-.html. Accessed: 14.08.2021.
  31. XRAD C++ software library. Available from: https://github.com/ Center-of-Diagnostics-and-Telemedicine/xrad.git. Accessed: 14.08.2021.
  32. Leonov DV, Kulberg NS, Gromov AI., et al. Causes of ultrasound doppler twinkling artifact. Acoust Phys. 2018;64(1):105–114. doi: 10.1134/S1063771018010128
  33. Mari JM, Cachard C. Acquire real-time RF digital ultrasound data from a commercial scanner. Electronic J Technical Acoustics. 2007;3:28–43.
  34. Leonov DV, Kulberg NS, Gromov AI, Morozov SP. Detection of microcalcifications using the ultrasound Doppler twinkling artifact. Biomedical Engineering. 2020;54(3):174–178. doi: 10.1007/s10527-020-09998-y
  35. Leonov DV, Kulberg NS, Fin VA, et al. Clutter filtering for diagnostic ultrasound color flow imaging. Biomedical Engineering. 2019;53(3):217–221. doi: 10.1007/s10527-019-09912-1
  36. Leonov DV, Kulberg NS, Fin VA, et al. Comparison of filtering techniques in ultrasound color flow imaging. Biomedical Engineering. 2019;53(2):97–101. doi: 10.1007/s10527-019-09885-1
  37. Song P, Manduca A, Trzasko JD, Chen S. Ultrasound small vessel imaging with block-wise adaptive local clutter filtering. IEEE Trans Med Imaging. 2017;36(1):251–262. doi: 10.1109/TMI.2016.2605819
  38. Li YL, Hyun D, Abou-Elkacem L, et al. Visualization of small-diameter vessels by reduction of incoherent reverberation with coherent flow power doppler. IEEE Trans Ultrason Ferroelectr Freq Control. 2016;63(11):1878–1889. doi: 10.1109/TUFFC.2016.2616112
  39. Chee AJ, Alfred CH. Receiver operating characteristic analysis of eigen-based clutter filters for ultrasound color flow imaging. IEEE Trans Ultrason Ferroelectr Freq Control. 2017;65(3):390–399. doi: 10.1109/TUFFC.2017.2784183
  40. Chee AJ, Yiu BY, Alfred CH. A GPU-Parallelized eigen-based clutter filter framework for ultrasound color flow imaging. IEEE Trans Ultrason Ferroelectr Freq Control. 2017;64(1):150–163. doi: 10.1109/TUFFC.2016.2606598

Supplementary files

Supplementary Files
Action
1. JATS XML
Download
2. Fig. 1. Data capture scheme

Download (50KB)
Indexing metadata
3. 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.

Download (97KB)
Indexing metadata
4. Fig. 3. Composition of the database.

Download (207KB)
Indexing metadata
5. Fig. 4. Scheme for storing “raw” radio frequency data in a *.dat file.

Download (175KB)
Indexing metadata
6. 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.

Download (798KB)
Indexing metadata
7. Fig. 6. External view and scheme of the Gammex 1430 LE Mini-Doppler phantom.

Download (213KB)
Indexing metadata
8. 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.

Download (469KB)
Indexing metadata
9. Fig. 8. Photo and drawings of the specialized phantom with dimensions in millimeters and measurement positions.

Download (323KB)
Indexing metadata
10. Fig. 9. Examples of sonograms of a specialized phantom with positions and a filling medium:

Download (591KB)
Indexing metadata
11. 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.

Download (519KB)
Indexing metadata
12. 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.

Download (557KB)
Indexing metadata
13. Fig. 12. Sonogram of a phantom with a wooden rod (left) and steel wire (right).

Download (461KB)
Indexing metadata

Copyright (c) 2021 Leonov D.V., Reshetnikov R.V., Kulberg N.S., Nasibullina A.A., Gromov A.I.

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

This website uses cookies

You consent to our cookies if you continue to use our website.

About Cookies